Physical Therapy- Journal of the APTA- July 2009, Volume 89, Issue 7

July 2009 Research Reports Manual Therapy, Exercise, and Traction for Cervical Radiculopathy 688 643 High-Intensity ...

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July 2009

Research Reports Manual Therapy, Exercise, and Traction for Cervical Radiculopathy

688

643

High-Intensity Laser Therapy Versus Ultrasound Therapy for Subacromial Impingement Syndrome

Perspectives

Paretic–Lower-Extremity Loading and Weight Transfer After Stroke

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Poststroke Muscle Recruitment and Co-contraction During Reaching

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Exercise Testing of Children With Spina Bifida

Number 7

Case Report

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653

Volume 89

Measurement of Poststroke Spasticity and Treatment With Botulinum Toxin

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Interpreting Studies of Responders to Physical Therapy Interventions

705

Assessment of Physical Functioning

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The Bottom Line The Bottom Line is a translation of study findings for application to clinical practice. It is not intended to substitute for a critical reading of the research article. Bottom Lines are written by invitation only. On “Manual Therapy, Exercise, and Traction for Patients With Cervical Radiculopathy: A Randomized Clinical Trial” What problems did the researchers set out to study, and why? Cervical radiculopathy (CR) can be a disabling condition as patients experience pain in the neck and into the arm or hand. Patients with CR have several treatment options available, ranging from surgical procedures to conservative interventions. Investigations into the optimal conservative intervention are few, and current approaches to the physical therapist management of CR are based on incomplete evidence and expert opinion. Thus, the authors set out to perform a randomized clinical trial to assess the effect of intermittent cervical traction, a commonly used intervention for CR, as part of a multimodal treatment program for patients with CR. Who participated in this study? 81 participants. To be included, participants were required to demonstrate signs and symptoms consistent with CR (pain in the hand or arm with or without neck pain) and meet 3 out of 4 criteria (a positive Spurling’s Test, a positive Distraction Test, a positive Upper Limb Tension Test 1, and ipsilateral neck rotation <65°) on a previously established clinical prediction rule that has been shown to identify patients with CR. Exclusion criteria consisted of a history of cervical or thoracic spine surgery, bilateral upper-extremity symptoms, medical red ﬂags, or the use of steroidal medication or injection within the past 2 weeks. What new information does this study offer? The addition of supine intermittent cervical traction to a multimodal treatment program for CR did not produce an added treatment beneﬁt. What new information does this study offer for patients? This trial is another example of research demonstrating that more treatment is not always better. In this case, adding traction to a physical therapy program consisting of postural education, manual therapy, and exercise did not provide an additional beneﬁt. The baseline care was sufﬁcient. This is an important result because, in some settings, adding another treatment to a physical therapy program means the patient will incur additional charges.

For more Bottom Lines on articles in this and other issues, visit www. ptjournal.org.

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How did the researchers go about the study? Participants were randomly assigned to either (1) a multimodal treatment group and sham traction or (2) a multimodal treatment group plus traction. The multimodal treatment consisted of 4 weeks of thrust and non-thrust manipulation to the cervical and thoracic regions, therapeutic exercise, and postural correction. The traction intervention consisted of supine intermittent cervical traction beginning at 20 lb or 10% of the patient’s body weight and was progressed to a maximum of 35 lb. The participants and clinical support staff who collected self-reported outcome measures were blinded to group assignment. How might the results be applied to physical therapist practice? The results of this trial suggest that there is no additional beneﬁt to adding supine intermittent cervical traction to a multimodal treatment approach for patients who have CR.

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The Bottom Line What are the limitations of the study, and what further research is needed? The researchers acknowledged several limitations to this trial. First, the clinical prediction rule used to identify eligible participants has not been validated. Second, the effectiveness of subject blinding was not assessed, and this is important in a trial where the primary outcomes are self-reported. Future studies should investigate different dosages of cervical traction. More research is required to determine the optimal combination of interventions for CR. Eric K. Robertson E.K. Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Medical College of Georgia. This is the Bottom Line for: Young IA, Michener LA, Cleland JA, Aguilera AJ, Snyder AR. Manual Therapy, Exercise, and Traction for Patients With Cervical Radiculopathy: A Randomized Clinical Trial. Phys Ther. 2009;89:632–642. The Bottom Line is a translation of study findings for application to clinical practice. It is not intended to substitute for a critical reading of the research article. Bottom Lines are written by invitation only.

On “Elastic, Viscous, and Mass Load Effects on Poststroke Muscle Recruitment and Co-contraction During Reaching: A Pilot Study“ What problems did the researchers set out to study, and why? Muscle weakness is an important determinant of functional ability in many patient populations. Although resistive exercise training following stroke can increase muscle strength, the effect of the type of resistive load has not been previously studied. The force required to move against a viscous load, such as water, increases with movement speed; the force required to elongate an elastic load, such as elastic bands, increases with the distance as the material is stretched; and acceleration and deceleration forces must be appropriately timed to move and stop the load for mass training. The researchers investigated the effect of load type (viscous, elastic, or mass) on muscle activation and co-contraction during a resisted forward reaching task in paretic and nonparetic arms. Who participated in this study? Twenty participants (10 with hemiplegia and 10 age-matched controls) were included in this pilot study. The experimental subjects were all classiﬁed as having moderate levels of disability on the Fugl-Meyer Motor Assessment, they could follow directions, and they could push a handle away from the body at waist level against resistance. What new information does this study offer? Motor control deﬁcits were present in both paretic and nonparetic arms during a pushing task for all load types in individuals following stroke. The paretic arm demonstrated muscle recruitment and muscle selection deﬁcits: higher levels of muscle activation and co-contraction occurred, compared with the nonparetic arm and control arms, regardless of load type. What new information does this study offer for patients? This study helps physical therapists consider the effect that different types of resistance may have on recruitment of different muscles and amount of muscle activation during a speciﬁc activity. Viscous and elastic loads resulted in higher levels of muscle recruitment July 2009

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The Bottom Line than the mass load for the anterior deltoid muscle in both the control and nonparetic limbs. People with stroke demonstrated different patterns of muscle recruitment and activation in both the involved and the uninvolved limbs compared with age-matched control participants. This information can help direct future research on the optimal type of resistance exercise to prescribe following stroke. How did the researchers go about the study? The participants performed a pushing task with both arms against resistive loads that required equivalent effort across the viscous, elastic, and mass loads. Normalized electromyographic (EMG) data were recorded for prime movers and antagonists of the shoulder and elbow for this task. How might the results be applied to physical therapist practice? Following stroke, motor control deﬁcits should be expected in both the paretic and nonparetic arms when reaching forward with different resistive load types. Based on the nonparetic limb response, the viscous loads elicited a strong muscle activation with minimal co-contraction. This could be a useful method to selectively target muscle strengthening as part of poststroke strength training. What are the limitations of the study, and what further research is needed? The levels of impairment were variable among participants, and the researchers recommended that this be controlled more closely in future work. Additionally, the side on which the lesion occurred was not controlled, and the ability to match load to the participants’ individual strength was limited. Future investigations should look at the effectiveness of different strength training interventions based on load type. The results of this study suggest that using the nonparetic arm as a control may be a ﬂawed assumption, so future studies should investigate this possibility. Eric K. Robertson E.K. Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Medical College of Georgia. This is the Bottom Line for: Stoeckmann TM, Sullivan KJ, Scheidt RA. Elastic, Viscous, and Mass Load Effects on Poststroke Muscle Recruitment and Co-contraction During Reaching: A Pilot Study. Phys Ther. 2009;89:665–678. The Bottom Line is a translation of study findings for application to clinical practice. It is not intended to substitute for a critical reading of the research article. Bottom Lines are written by invitation only.

On “Measurement of Paretic–Lower-Extremity Loading and Weight Transfer After Stroke“ What problems did the researchers set out to study, and why? Stroke is a leading cause of disability, and the resulting hemiparesis can have a signiﬁcant impact on sitting, standing, and walking activities. Impaired loading of the paretic limb and weight transfer between limbs have been associated with functional deﬁcits. Limb loading and weight transfer are key goals in rehabilitation training following stroke for individuals with lower-extremity motor impairments. The standard measure— force platforms—are expensive, so the researchers set out to examine the validity of other clinical tools. Paretic limb load was examined using the Step Test (ST) and the knee extension component of the Upright Motor Control Test (UMCe), and the 630 ■

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The Bottom Line Repetitive Reach Test (RR) served as a measure of weight transfer in individuals in the ﬁrst 6 months following stroke. Who participated in this study? 33 individuals with lower-extremity motor impairment (≤28 on the Fugl-Meyer Assessment) following unilateral noncerebellar stroke. Individuals who were medically stable, who could follow 3-step commands, who could reach in all directions while sitting without support, and who had adequate hearing and vision to complete the study protocol were included. Participants were not included if they had a history of prior stroke, they were not previously independent community ambulators, they had a terminal illness, or they had pain or limitations that interfered with daily activity performance. What new information does this study offer? The ST was a valid measure of paretic limb loading following stroke and had the highest correlation with force platform tests. The correlations in measures of paretic limb loading between the force platform and the UMCe test were less strong than the ST, and the RR test did not correlate strongly with force platform measures of weight transfer. What new information does this study offer for patients? The results of this study suggest that the ST is a valid measure, compared with force platform tests, to assess paretic limb loading. The ST is an easy to administer clinical test. Two other clinical tests are not recommended to examine limb loading or weight transfer. How did the researchers go about the study? Three clinical tests were administered once monthly for 6 months. The ST included placing the nonparetic limb repeatedly on a step over 15 seconds. The UMCe test was performed without an assistive device and required the patient to bend the knees and then attempt to return to an extended knee position using just the paretic limb. The RR test was performed by having the patient reach back and forth repeatedly using the nonparetic arm. These clinical tests were compared to a battery of force platform tests to measure convergent validity. How might the results be applied to physical therapist practice? The ST is a valid, easy-to-administer clinical test that can take the place of more involved force platform testing in assessment of paretic limb loading. What are the limitations of the study, and what further research is needed? This study contained a relatively small sample size and a preponderance of individuals with left-side hemiparesis. Additional research is needed to determine reliable and valid methods to assess weight transfer after stroke. Future studies should aim to identify the relationship between ST scores and physical activity to determine how ﬁndings on the ST may affect other domains. Eric K. Robertson E.K. Robertson, PT, DPT, OCS, is Assistant Professor, Department of Physical Therapy, Medical College of Georgia. This is the Bottom Line for: Stemmons Mercer V, Kues Freburger J, Chang S, Purser JL. Measurement of Paretic–Lower-Extremity Loading and Weight Transfer After Stroke. Phys Ther. 2009;89:653–664. The Bottom Line is a translation of study findings for application to clinical practice. It is not intended to substitute for a critical reading of the research article. Bottom Lines are written by invitation only.

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Physical Therapy Journal of the American Physical Therapy Association

Editorial Office

Editor in Chief

Managing Editor / Associate Director of Publications: Jan P. Reynolds, [email protected]

Rebecca L. Craik, PT, PhD, FAPTA, Philadelphia, PA [email protected]

PTJ Online Editor / Assistant Managing Editor: Steven Glaros

Deputy Editor in Chief

Associate Editor: Stephen Brooks, ELS Production Manager: Liz Haberkorn Manuscripts Coordinator: Karen Darley Permissions / Reprint Coordinator: Michele Tillson Advertising Manager: Julie Hilgenberg Director of Publications: Lois Douthitt

APTA Executive Staff Senior Vice President for Communications: Felicity Feather Clancy Chief Financial Officer: Rob Batarla Chief Executive Officer: John D. Barnes

Advertising Sales Ad Marketing Group, Inc 2200 Wilson Blvd, Suite 102-333 Arlington, VA 22201 703/243-9046, ext 102 President / Advertising Account Manager: Jane Dees Richardson

Board of Directors President: R. Scott Ward, PT, PhD Vice President: Randy Roesch, PT, MBA, DPT Secretary: Babette S. Sanders, PT, MS Treasurer: Connie D. Hauser, PT, DPT, ATC Speaker of the House: Shawne E. Soper, PT, DPT, MBA Vice Speaker of the House: Laurita M. Hack, PT, DPT, MBA, PhD, FAPTA Directors: William D. Bandy, PT, PhD, SCS, ATC; Sharon L. Dunn, PT, PhD, OCS; Kevin L. Hulsey, PT, DPT, MA; Dianne V. Jewell, PT, DPT, PhD, CCS, FAACVPR; Aimee B. Klein, PT, DPT, MS, OCS; Stephen C.F. McDavitt, PT, DPT, MS, FAAOMPT; Paul A. Rockar Jr, PT, DPT, MS; Lisa K. Saladin, PT, PhD; John G. Wallace Jr, PT, MS, OCS

Daniel L. Riddle, PT, PhD, FAPTA, Richmond, VA

Editor in Chief Emeritus Jules M. Rothstein, PT, PhD, FAPTA (1947–2005)

Steering Committee Anthony Delitto, PT, PhD, FAPTA (Chair), Pittsburgh, PA; J. Haxby Abbott, PhD, MScPT, DipGrad, FNZCP, Dunedin, New Zealand; Joanell Bohmert, PT, MS, Mahtomedi, MN; Alan M. Jette, PT, PhD, FAPTA, Boston, MA; Charles Magistro, PT, FAPTA, Claremont, CA; Ruth B. Purtilo, PT, PhD, FAPTA, Boston, MA; Julie Whitman, PT, DSc, OCS, Westminster, CO

Editorial Board Rachelle Buchbinder, MBBS(Hons), MSc, PhD, FRACP, Malvern, Victoria, Australia; W. Todd Cade, PT, PhD, St Louis, MO; James Carey, PT, PhD, Minneapolis, MN; John Childs, PT, PhD, Schertz, TX; Charles Ciccone, PT, PhD, FAPTA (Continuing Education), Ithaca, NY; Joshua Cleland, PT, DPT, PhD, OCS, FAAOMPT, Concord, NH; Janice J. Eng, PT/OT, PhD, Vancouver, BC, Canada; G. Kelley Fitzgerald, PT, PhD, OCS, FAPTA, Pittsburgh, PA; James C. (Cole) Galloway, PT, PhD, Newark, DE; Steven Z. George, PT, PhD, Gainesville, FL; Kathleen Gill-Body, PT, DPT, NCS, Boston, MA; Paul J.M. Helders, PT, PhD, PCS, Utrecht, The Netherlands; Maura D. Iversen, PT, ScD, MPH, Boston, MA; Diane U. Jette, PT, DSc, Burlington, VT; Christopher Maher, PT, PhD, Lidcombe, NSW, Australia; Christopher J. Main, PhD, FBPsS, Keele, United Kingdom; Kathleen Kline Mangione, PT, PhD, GCS, Philadelphia, PA; Patricia Ohtake, PT, PhD, Buffalo, NY; Carolynn Patten, PT, PhD, Gainesville, FL; Linda Resnik, PT, PhD, OCS, Providence, RI; Val Robertson, PT, PhD, Copacabana, NSW, Australia; Patty Solomon, PT, PhD, Hamilton, Ont, Canada

Statistical Consultants Steven E. Hanna, PhD, Hamilton, Ont, Canada; John E. Hewett, PhD, Columbia, MO; Hang Lee, PhD, Boston, MA; Xiangrong Kong, PhD, Baltimore, MD; Paul Stratford, PT, MSc, Hamilton, Ont, Canada; Samuel Wu, PhD, Gainesville, FL

The Bottom Line Committee Eric Robertson, PT, DPT, OCS; Joanell Bohmert, PT, MS; Lara Boyd, PT, PhD; James Cavanaugh IV, PT, PhD, NCS; Todd Davenport, PT, DPT, OCS; Ann Dennison, PT, DPT, OCS; William Egan, PT, DPT, OCS; Helen Host, PT, PhD; Evan Johnson, PT, DPT, MS, OCS, MTC; M. Kathleen Kelly, PT, PhD; Catherine Lang, PT, PhD; Tara Jo Manal, PT, MPT, OCS, SCS; Kristin Parlman, PT, DPT, NCS; Susan Perry, PT, DPT, NCS; Maj Nicole H. Raney, PT, DSc, OCS, FAAOMPT; Rick Ritter, PT; Kathleen Rockefeller, PT, MPH, ScD; Michael Ross, PT, DHS, OCS; Katherine Sullivan, PT, PhD; Mary Thigpen, PT, PhD; Jamie Tomlinson, PT, MS; Brian Tovin, DPT, MMSc, SCS, ATC, FAAOMPT; Nancy White, PT, MS, OCS; Julie Whitman, PT, DSc, OCS

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Subscriptions

Physical Therapy (PTJ) (ISSN 00319023) is published monthly by the American Physical Therapy Association (APTA), 1111 North Fairfax Street, Alexandria, VA 22314-1488, at an annual subscription rate of $15 for members, included in dues. Nonmember rates are as follows: Individual (inside USA)— $99; individual (outside USA)—$119 surface mail, $179 air mail. Institutional (inside USA)—$129; institutional (outside USA)—$149 surface mail, $209 air mail. Periodical postage is paid at Alexandria, VA, and at additional mailing offices. Postmaster: Send address changes to Physical Therapy, 1111 North Fairfax Street, Alexandria, VA 22314-1488. Single copies: $15 USA, $15 outside USA; with the exception of January 2001: $50 USA, $70 outside USA. All orders payable in US currency. No replacements for nonreceipt after a 3-month period has elapsed. Canada Post International Publications Mail Product Sales Agreement No. 0055832.

Members and Subscribers Send changes of address to: APTA, Attn: Membership Dept, 1111 North Fairfax St, Alexandria, VA 22314-1488. Subscription inquiries: 703/684-2782, ext 3124. PTJ is available in a special format for readers who are visually impaired. For information, contact APTA’s Membership Department at 703/684-2782, ext 3124.

Mission Statement

Physical Therapy (PTJ) engages and inspires an international readership on topics related to physical therapy. As the leading international journal for research in physical therapy and related fields, PTJ publishes innovative and highly relevant content for both clinicians and scientists and uses a variety of interactive approaches to communicate that content, with the expressed purpose of improving patient care.

Readers are invited to submit manuscripts to PTJ. PTJ’s content—including editorials, commentaries, letters, and book reviews—represents the opinions of the authors and should not be attributed to PTJ or its Editorial Board. Content does not reflect the official policy of APTA or the institution with which the author is affiliated, unless expressly stated.

Full-text articles are available for free at www.ptjournal.org 12 months after the publication date. Full text also is provided through DataStar, Dialog, EBSCOHost Academic Search, Factiva, InfoTrac, ProFound, and ProQuest.

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PTJ Online at www.ptjournal.org PTJ’s Web site posts articles ahead of print and rapid reader responses to articles. Articles, letters to the editor, and editorials are available in full text starting with Volume 79 (1999) and in searchable PDF format starting with Volume 60 (1980). Entire issues are available online beginning with Volume 86 (2006) and include additional data, video clips, and podcasts.

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July 2009

Technologies. Ingenta provides online document delivery for articles published since September 1988.

Advertisements are accepted by PTJ when they conform to the ethical standards of the American Physical Therapy Association. PTJ does not verify the accuracy of claims made in advertisements, and acceptance does not imply endorsement by PTJ or the Association. Acceptance of advertisements for professional development courses addressing advanced-level competencies in clinical specialty areas does not imply review or endorsement by the American Board of Physical Therapy Specialties.

Statement of Nondiscrimination APTA prohibits preferential or adverse discrimination on the basis of race, creed, color, gender, age, national or ethnic origin, sexual orientation, disability, or health status in all areas including, but not limited to, its qualifications for membership, rights of members, policies, programs, activities, and employment practices. APTA is committed to promoting cultural diversity throughout the profession.

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Editorial PT 2009 Notes, PTJ Welcomes and Thanks

A

s I write this, we’ve just returned from PT 2009 in Baltimore, where PTJ held its fourth annual Rothstein Debate. Our topic this year was “When Does Regulation Become Over-Regulation, and When Does Under-Regulation Invite Abuse?” I extend special thanks to our debaters, Larry Benz, PT, DPT, ECS, and Stephen Levine, PT, DPT, MSHA, and to our moderator, Tony Delitto, PT, PhD, FAPTA, who, along with PTJ’s Steering Committee, determines topics and questions for our debates. Look for the podcast at http://www.ptjournal.org/misc/podcasts.dtl. The debate raised incredibly important issues for the profession, especially as we enter a time of intense health care reform efforts. I was struck by the need for every member of the profession to be informed about the issues related to regulation. Although Drs Benz and Levine started the session in opposition to each other’s point of view, the discussion that emerged showed their agreement on basic principles surrounding the need for regulation. If we all had the facts about professional issues—rather than sound bites, perceptions, and hearsay—our profession might develop a stronger voice at the table with other members of the health care team. How can we get more APTA members to attend sessions that address these types of issues? The conference’s “mega-issue” sessions were important regardless of clinical specialty or practice setting but had only moderate attendance. Such topics as the use of technology, health care reform, negotiating with insurance companies, earning a living and being ethical, and the vision of our future from participants in the Physical Therapy and Society Summit (PASS) require our immediate attention! Take health care reform, for example. Are we going to sit back and let others develop the new model, without providing our input? Are we going to be reactive rather than proactive? And how can we as members be actively involved in the changes that are occurring if we are not familiar with the vocabulary, the data, the opportunities, and APTA’s position? PTJ’s “Essentials of Writing and Reviewing Manuscripts” session at PT 2009 had a special focus on case reports, and guest presenter Irene McEwen, PT, PhD, FAPTA, former Deputy Editor of PTJ, spoke about the hot-off-the-press third edition of Writing Case Reports: A How-to Manual for Clinicians. The book provides a step-by-step guide to writing case reports and is applicable regardless of the journal to which you want to submit. In addition to full traditional case reports, PTJ is looking for case reports that highlight diagnosis/ prognosis, clinical measurement, intervention, application of theory to practice, risk management, and administrative/educational processes. The physical therapy profession still needs rich case reports that describe practice regardless of setting. I strongly urge you to consider writing a case report that describes, for example, a novel way to help students learn in the classroom or in the clinical setting or to help administrators consider a different management model. We will always welcome clinical case reports, but I am encouraging you to think about other types of reports as well.

To comment, submit a Rapid Response to this editorial posted online at www.ptjournal.org.

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I am pleased to announce 2 new Editorial Board members for 2009/2010: James R. Carey, PT, PhD, is professor and director of the Program in Physical Therapy at University of Minnesota, Minneapolis. With his extensive publication record in neuromuscular content, he brings to our table additional expertise in neuroplasticity, neural imaging modalities, and transcranial magnetic stimulation. Jim has served as principal

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Editorial investigator on numerous federal grants, including tracking training to stimulate neuroplasticity in stroke and, currently, rTMS and motor learning training to promote recovery from hemiparesis. Jim will complement the content expertise of Janice Eng, Kathy Gill-Body, Cole Galloway, Paul Helders, and Carolynn Patten. The neuromuscular expertise on our Editorial Board covers the life span, motor control and motor learning theory, neural recovery, assessment, and intervention! I look forward to this team generating topics to attract work that will excite scientists and clinicians alike. Steven Z. George, PT, PhD, is associate professor in the Department of Physical Therapy at the University of Florida, where he also is a member of the Graduate Faculty in the Rehabilitation Science Doctoral Program. He has about 60 peer-reviewed publications, and his awards include the Eugene Michels New Investigator Award and the American Pain Society’s John C. Liebeskind Early Career Scholar Award. His involvement with the Center for Pain Research and Behavioral Health and the Brooks Center for Rehabilitation Studies offers PTJ the opportunity to become a stronger voice in understanding the mechanisms associated with the development and management of pain. His research is focused on the utilization of biopsychosocial models for the prevention and treatment of chronic musculoskeletal pain, and we are excited that he and Editorial Board Member Dr Chris J. Main have already agreed to work together on a PTJ special issue related to pain. I also take this opportunity to thank our outgoing Editorial Board members, all of whom have given so much to PTJ. Andrea Behrman, PT, PhD, FAPTA, is a pioneer in locomotor training in people with incomplete spinal cord injury. Her clinical research focus is on neural recovery versus neural compensation, and she has allowed PTJ to travel on this journey with her as she explored the issues of intervention dose, the effect of context (treadmill vs overground), and retention. She also helped the Journal begin using video as a medium to share methods and illustrate results. Her enthusiasm for the work of the authors whose manuscripts she reviewed was infectious. Thank you, Andrea, and keep up the exciting research path you have selected! Gregory Karst, PT, PhD, who is now assistant dean for academic affairs in addition to being professor in the Division of Physical Therapy Education in the School of Allied Health Professions at the University of Nebraska Medical Center, Omaha, has served on our Editorial Board for almost 10 years. Although his training and research focused on motor control and kinesiological electromyography, Greg has been an incredible team player, reviewing literally hundreds of research manuscripts related to application of a variety of modalities including electrical stimulation, ultrasound, and other thermal devices. Greg’s feedback to authors always included suggestions for how to improve the work for the next phase of research. I wish him well in his role as an administrator but am sorry that we are losing his expertise. Thank you, Greg. Chris Powers, PT, PhD, also has done an excellent job, bringing his biomechanical expertise to our Editorial Board for more than 7 years. His work with authors has helped them to link movement principles to procedures for examination and rationales for intervention. I am delighted that he has become the President of APTA’s Section on Research, but his voice at our table will be missed. On behalf of the entire board, thank you, Chris. As we welcome new contributors and thank those who have helped build PTJ, I encourage you to keep reading the Journal. We are working to provide you with relevant information through a variety of media, and we plan to become even more relevant in the generation of new knowledge and in the refinement of practice as we all move forward. Rebecca L Craik, PT, PhD, FAPTA Editor in Chief [DOI: 10.2522/ptj.2009.89.7.626]

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Research Report Manual Therapy, Exercise, and Traction for Patients With Cervical Radiculopathy: A Randomized Clinical Trial Ian A. Young, Lori A. Michener, Joshua A. Cleland, Arnold J. Aguilera, Alison R. Snyder

I.A. Young, PT, MS, OCS, SCS, Cert MDT, is Physical Therapist, Spine and Sport, Savannah, Georgia, and Affiliate-Associate Professor, Department of Physical Therapy, Virginia Commonwealth University–Medical College of Virginia Campus, Richmond, Virginia. Mailing address: Box 961, Tybee Island, GA 31328 (USA). Address all correspondence to Mr Young at: youngian@spinesport. org.

Background. To date, optimal strategies for the management of patients with cervical radiculopathy remain elusive. Preliminary evidence suggests that a multimodal treatment program consisting of manual therapy, exercise, and cervical traction may result in positive outcomes for patients with cervical radiculopathy. However, limited evidence exists to support the use of mechanical cervical traction in patients with cervical radiculopathy.

L.A. Michener, PT, PhD, ATC SCS, is Associate Professor, Department of Physical Therapy, Virginia Commonwealth University–Medical College of Virginia Campus.

Design. This study was a multicenter randomized clinical trial.

J.A. Cleland, PT, PhD, OCS, FAAOMPT, is Associate Professor, Department of Physical Therapy, Franklin Pierce University, Concord, New Hampshire; Physical Therapist, Rehabilitation Services, Concord Hospital, Concord, New Hampshire; and Faculty, Regis University Manual Therapy Fellowship Program, Denver, Colorado. A.J. Aguilera, MD, is Neurologist, Neurology Associates, Fredericksburg, Virginia. A.R. Snyder, PhD, ATC, is Assistant Professor, Athletic Training Program, A. T. Still University, Mesa, Arizona. [Young IA, Michener LA, Cleland JA, et al. Manual therapy, exercise, and traction for patients with cervical radiculopathy: a randomized clinical trial. Phys Ther. 2009; 89:632– 642.] © 2009 American Physical Therapy Association Post a Rapid Response or find The Bottom Line: www.ptjournal.org 632

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Objective. The purpose of this study was to examine the effects of manual therapy and exercise, with or without the addition of cervical traction, on pain, function, and disability in patients with cervical radiculopathy.

Setting. The study was conducted in orthopedic physical therapy clinics. Patients. Patients diagnosed with cervical radiculopathy (N⫽81) were randomly assigned to 1 of 2 groups: a group that received manual therapy, exercise, and intermittent cervical traction (MTEXTraction group) and a group that received manual therapy, exercise, and sham intermittent cervical traction (MTEX group). Intervention. Patients were treated, on average, 2 times per week for an average of 4.2 weeks.

Measurements. Outcome measurements were collected at baseline and at 2 weeks and 4 weeks using the Numeric Pain Rating Scale (NPRS), the Patient-Specific Functional Scale (PSFS), and the Neck Disability Index (NDI). Results. There were no significant differences between the groups for any of the primary or secondary outcome measures at 2 weeks or 4 weeks. The effect size between groups for each of the primary outcomes was small (NDI⫽1.5, 95% confidence interval [CI]⫽⫺6.8 to 3.8; PSFS⫽0.29, 95% CI⫽⫺1.8 to 1.2; and NPRS⫽0.52, 95% CI⫽⫺1.8 to 1.2).

Limitations. The use of a nonvalidated clinical prediction rule to diagnose cervical radiculopathy and the lack of a control group without treatment were limitations of this study. Conclusions. The results suggest that the addition of mechanical cervical traction to a multimodal treatment program of manual therapy and exercise yields no significant additional benefit to pain, function, or disability in patients with cervical radiculopathy.

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he annual incidence of cervical radiculopathy (CR) has been reported to be 83 cases per 100,000 people in the population, with an increased prevalence noted in the fifth decade of life.1 This disorder is most commonly associated with a cervical disk derangement or other space-occupying lesion, resulting in nerve root inflammation, impingement, or both.1,2 Common signs and symptoms of CR include upper-extremity pain, paresthesia or numbness, weakness, or a combination of these signs and symptoms. Patients also may have scapular pain,3,4 headaches,5 and neck pain.6 Patients with both neck and upperextremity symptoms have been reported to have greater functional limitation and disability than patients with neck pain alone.7 Diagnostic imaging (magnetic resonance imaging) and electrophysiological tests (nerve conduction velocity, electromyography) are commonly used to confirm a diagnosis of CR.8 –11 Using nerve conduction velocity and electromyographic data as a gold standard, a clinical prediction rule (CPR) was derived to identify the presence of CR using a limited subset of variables from the clinical examination.12 The CPR for identifying CR includes the Spurling test, the distraction test, the UpperLimb Tension Test 1 (ULLT1) (median nerve bias), and ipsilateral cervical rotation of less than 60 degrees. The CPR exhibited a specificity of 94% (positive likelihood ratio⫽6.1, 95% confidence interval [CI]⫽2.0 to 18.6) when 3 of 4 criteria were satisfied. Physical therapy interventions often used for the management of CR include cervical traction, postural education, exercise, and manual therapy applied to the cervical spine and thoracic spine.13 Studies indicate that some combination of these interventions may result in improved outJuly 2009

comes for patients with CR.14 –23 Previous controlled clinical trials investigating the treatment of patients with CR have not used the CPR as an inclusion criteria.14,15,17,23,24 To date, only 2 case series18,21 and a cohort study22 have examined standardized treatment programs in patients diagnosed with CR, using the previously defined CPR. The prospective cohort study identified predictor variables that can identify which patients with CR are likely to have short-term successful outcomes.22 A multimodal approach to management including manual therapy, cervical traction, and deep neck flexor strengthening was identified as the set of predictors; however, the study design does not allow for identification of a cause-and-effect relationship. Moreover, the treatment protocol in that study was not standardized. A randomized clinical trial is needed to compare the effectiveness of standardized treatment approaches in a homogenous sample of patients with CR. The clinical use of intermittent cervical traction for CR is common, but its effectiveness has been examined in only one clinical trial.17 Joghataei et al17 found that exercise and intermittent cervical traction were superior to exercise and ultrasound in improving grip strength (forcegenerating capacity) following 5 visits in patients with C7 radiculopathy. However, the lack of a measure of pain or disability limits application of these results. There remains a paucity of quality outcome studies investigating commonly used interventions in a homogenous population of patients with CR. Thus, the purpose of this study was to examine the effects of manual therapy and exercise, with or without the addition of intermittent cervical traction, in patients with CR, as identified by the previously described CPR.

Materials and Method A multicenter randomized clinical trial involving orthopedic physical therapy clinics in Virginia, Georgia, Alabama, and West Virginia (N⫽7 clinics) was conducted between October 2006 and December 2007. A total of 10 physical therapists (9 male, 1 female) with an average of 7 years (range⫽0.5–12) of experience treating patients with spinal conditions participated in data collection. In order maximize standardization, all clinicians were given on-site training by the primary investigator (I.A.Y.) and provided with an instruction manual and video on all examination, treatment, and data collection procedures. Our original sample size estimate for data analysis was 80 subjects. Because the outcome measures used in this study have not been used in previous clinical trials for this patient population, an accurate power analysis based on effect size could not be calculated. With an estimated small effect size ( f⫽0.25), a sample size of 80 would have given the study a power of 94%. Consecutive patients with reports of unilateral upper-extremity pain, paresthesia, or numbness, with or without neck pain, were screened by a physical therapist for study eli-

Available With This Article at www.ptjournal.org • eAppendix: Description of Manual Therapy and Exercise Procedures • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on May 21, 2009, at www.ptjournal.org.

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Figure 1. CONSORT flow diagram of participants through the trial. CPR⫽clinical prediction rule.

gibility. Of the patients screened for participation (N⫽121), 40 were excluded or refused to participate for variety of reasons. A flow diagram of patient recruitment and retention is presented in Figure 1. Patients who satisfied the eligibility criteria (Tab. 1) were invited to participate in the study. All enrolled patients (n⫽81) provided informed consent for participation in the study. Following consent, each patient underwent a standardized history and physical examination, as well as collection of data for all outcome measures.

The physical examination included the items in the CPR, repetitive motion testing (cervical protraction and retraction),25 deep tendon reflexes (biceps, brachioradialis, triceps), myotomal assessment (C5– C8, T1), and grip strength bilaterally. Primary outcome measures were the Numeric Pain Rating Scale (NPRS),26,27 the Neck Disability Index (NDI),28,29 and the PatientSpecific Functional Scale (PSFS).29,30 Secondary outcome measures were the Fear-Avoidance Beliefs Questionnaire (FABQ),31,32 a pain diagram,33 the Global Rating of Change Scale

(GROC),34 patient satisfaction,35 and grip strength.36,37 Each outcome measure and its psychometric properties are described in the Appendix. Data for the outcome measures were collected at baseline and at 2-week and 4-week follow-ups. After the examination, patients were randomly assigned to 1 of 2 treatment groups: a group that received manual therapy, exercise, and intermittent cervical traction (MTEXTraction group) and a group that received manual therapy, exercise, and sham intermittent cervical traction

Table 1. Inclusion and Exclusion Criteria Inclusion Criteria ● ● ●

634

Exclusion Criteria

Age 18–70 y Unilateral upper-extremity pain, paresthesia, or numbness 3 of 4 tests of clinical prediction rule positive: - Spurling test - Distraction test - Upper-Limb Tension Test 1 - Ipsilateral cervical rotation ⬍60°

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● ● ● ● ● ●

History of previous cervical or thoracic spine surgery Bilateral upper-extremity symptoms Signs or symptoms of upper motor neuron disease Medical “red flags” (eg, tumor, fracture, rheumatoid arthritis, osteoporosis, prolonged steroid use) Cervical spine injections (steroidal) in the past 2 wk Current use of steroidal medication prescribed for radiculopathy symptoms

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Manual Therapy, Exercise, and Traction for Cervical Radiculopathy (MTEX group). In order to decrease the potential effect of the clinic on treatment outcomes, concealed randomization, stratified by clinic, was used to place patients into treatment groups. Numbered, sequential, sealed envelopes containing group allocation for each clinic were opened by the evaluating therapist after the baseline examination. Support staff, who were unaware of group assignment, administered all patient self-report measures and grip strength testing as instructed by the therapist. Treatment Patients were treated for an average of 7 visits (SD⫽2.08), over an average of 4.2 weeks, with a standardized treatment protocol. Treatments were performed sequentially to include postural education, manual therapy, and exercise and ended with traction or sham traction. All patients received a home exercise program on their first visit, including one or more of the available exercises used in the standardized treatment protocol. The home exercise program was updated, as needed, on each visit by the physical therapist. Posture education. On the initial treatment visit, patients were educated on importance of correct postural alignment of the spine during sitting and standing activities. Posture was addressed on subsequent visits only if the physical therapist deemed it necessary. Manual therapy. Manual therapy was defined as either high-velocity, low-amplitude thrust manipulation or nonthrust manipulation. Initial treatment included manipulation procedures directed at the upperand mid-thoracic spines of spinal segments identified as hypomobile during segmental mobility testing.38 Thrust manipulation of the thoracic spine could include techniques in a prone, supine, or sitting position July 2009

based on therapist preference. Nonthrust manipulation included posterior-anterior (P-A) glides in the prone position. Therapists were required to perform at least one technique targeting the upper thoracic spine and one technique targeting the mid thoracic spine during each visit. Following treatment directed at the thoracic spine, at least one set (30 seconds or 15–20 repetitions) of a nonthrust manipulation was directed at each desired level of the cervical spine. The cervical spine techniques could include retractions, rotations, lateral glides in the ULTT1 position, and P-A glides. The therapists chose the techniques based on patient response and centralization or reduction of symptoms. Exercise. After completing the manual therapy procedures, the therapist instructed the patient on specific exercises to complement the manual procedures performed. Exercises included cervical retraction, cervical extension, deep cervical flexor strengthening, and scapular strengthening. At least one exercise was used during each treatment visit. All manual therapy and exercise procedures are described in the eAppendix (available online at www.ptjournal.org). Traction and sham traction. After exercise, patients received either mechanical intermittent cervical traction or sham traction for 15 minutes according to their random assignment. Each patient was positioned supine, with the cervical spine placed at an angle of approximately 15 degrees of flexion. The traction force was started at 9.1 kg (20 lb) or 10% of the patient’s body weight (whichever was less) and increased approximately 0.91 to 2.27 kg (2–5 lb) every visit, depending on centralization or reduction of symptoms. The maximum force used was 15.91 kg (35 lb). The on/off cycle was set at 50/10. The sham traction

protocol included the identical setup; however, only 2.27 kg (5 lb) or less of force was applied. All other traction parameters were the same as for the group that received intermittent cervical traction. Data Analysis A separate repeated-measures, mixedmodel analysis was performed for each of the primary and secondary outcomes, with alpha set at .05. Treatment group (MTEX versus MTEXTraction) was the betweenpatient factor, and time (baseline, 2-week follow-up, 4-week follow-up) was defined as the repeated factor. The primary and secondary outcomes were used as the dependent variables. To allow for correlations within participants and of participants within clinics, we modeled patient and clinic as random effects without interactions. The main hypothesis of interest was the group ⫻ time interaction. Linear contrasts were constructed to determine the between-group differences at each time point. The main effects of the interventions were obtained by constructing linear contrasts to compare the mean change in outcome from baseline to each time point. The effect size was calculated from the between-group differences in change score from baseline to the 4-week follow-up in all of the primary outcome measures. Analyses followed intention-to-treat principles. All analyses were performed using SAS statistical software (JMP version 8.0*). Role of the Funding Source This study was funded by a grant from the Saunders Group.

Results Patients (N⫽121) were screened for eligibility, and 81 patients were eligible and agreed to participate (Fig. 1). Twelve patients (n⫽6 in * SAS Institute Inc, PO Box 8000, Cary, NC 27513.

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Manual Therapy, Exercise, and Traction for Cervical Radiculopathy Table 2. Baseline Variables and Treatment Visitsa Variable Age (y)

MTEXTraction Group (nⴝ45)

MTEX Group (nⴝ36)

47.8 (9.9)

46.2 (9.4)

Sex, n (%) Male

14 (31.1)

12 (33.3)

Female

31 (68.9)

24 (66.7)

8 (18.2)

4 (11.8)

Work-related injury, n (%) Duration of symptoms, n (%) ⱕ3 mo

27 (60)

15 (42)

⬎3 mo

18 (40)

21 (58)

Neck movement alters symptoms, n (%)

35 (85.3)

30 (85.7)

Previous symptoms, n (%)

13 (28)

12 (33)

33 (75)

26 (74.3)

Most bothersome symptom, n (%) Pain Numbness/tingling

8 (18.2)

5 (14.3)

Both pain and numbness/tingling

3 (6.8)

4 (11.4)

19.8 (8.7)

17.1 (7.4)

3.5 (1.8)

3.3 (1.8)

Neck Disability Indexb Patient-Specific Functional Scalec Numeric Pain Rating Scale

d

Body diagram (symptom distribution)e

6.3 (1.9)

6.5 (1.7)

22.5 (10.6)

20.7 (9.6)

17.7 (7.4)

18.3 (5.7)

24.1 (17.2)

18.7 (16.2)

7.0 (2.1)

6.9 (2.1)

Fear-Avoidance Beliefs Questionnaire Physical activity subscalef Work subscale

g

No. of treatment visits

Neurological examination,h n (%)

Normal Positive Test Positive Test Normal Positive Test Positive Test Examination Either Category Both Categories Examination Either Category Both Categories 9 (20)

22 (48.9)

14 (31.1)

8 (22.2)

16 (44.4)

12 (33.3)

a

Values are mean (SD) unless otherwise stated. MTEXTraction group⫽patients who received manual therapy, exercise, and intermittent cervical traction; MTEX group⫽patients who received manual therapy, exercise, and sham intermittent cervical traction. b Range of scores⫽0 –50; higher scores represent higher levels of disability. c Range of scores⫽0 –10; higher scores represent greater levels of function. d Range of scores⫽0 –10, where 0⫽“no pain.” e Range of scores⫽0 – 44; higher scores represent greater area of symptom distribution. f Range of scores⫽0 –30; higher scores represent higher levels of fear avoidance. g Range of scores⫽0 – 66; higher scores represent higher levels of fear avoidance. h 2 categories: deep tendon reflexes and myotome assessment.

each group) were lost to follow-up between baseline (pretreatment) measures and the 4-week follow-up. Baseline demographics and data for outcome measures are listed in Table 2. No significant interaction or main effects of group were found for the primary or secondary outcome measures (Tab. 3). There was a significant main effect (P⬍.05) of time 636

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for the NPRS, PSFS, NDI, and body diagram, indicating there were significant improvements in pain, function, disability, and symptom distribution regardless of group assignment (MTEX versus MTEXTraction) from baseline to the 4-week follow-up. The adjusted effect size from the mixed-models analysis for each of the primary outcomes was small (NDI⫽1.5, 95% confidence interval [CI]⫽⫺6.8 to 3.8; PSFS⫽0.29,

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95% CI⫽⫺1.8 to 1.2; and NPRS⫽ 0.52, 95% CI⫽⫺1.8 to 1.2).

Discussion This randomized clinical trial investigated the effects of a multimodal treatment approach including manual therapy and exercise, with and without the addition of intermittent cervical traction, in patients with CR. The results indicate that the addition of supine intermittent cervical July 2009

Manual Therapy, Exercise, and Traction for Cervical Radiculopathy Table 3. Results of Analysis Comparing Outcomes Between Treatment Groupsa Unadjusted Mean (SD) for Each Group

Adjusted Mean (SD) for Each Groupb

Adjusted Mean Difference Between Groupsb (95% CI)

MTEXTraction Group

MTEX Group

Unadjusted Mean Difference Between Groups (95% CI)

2 wk

15.0 (8.2)

13.1 (7.1)

1.9 (⫺1.8 to 5.6)

.31

14.0 (12.3)

12.2 (11.8)

1.8 (⫺7.0 to 3.5)

.34

4 wk

12.1 (9.0)

10.9 (7.8)

1.2 (⫺2.9 to 5.3)

.56

11.1 (12.3)

9.6 (14.1)

1.5 (⫺6.8 to 3.8)

.42

Outcome Measure Neck Disability Index

P

MTEXTraction Group

MTEX Group

P

c

Patient-Specific Functional Scaled 2 wk

5.1 (2.5)

5.2 (2.4)

0.06 (⫺1.2 to 1.1)

.91

5.3 (3.8)

5.6 (3.8)

0.22 (⫺1.2 to 1.7)

.66

4 wk

6.6 (2.4)

6.3 (2.5)

0.27 (0.91 to 1.5)

.66

7.0 (3.8)

6.7 (4.3)

0.29 (⫺1.8 to 1.2)

.57

2 wk

4.5 (2.3)

5.1 (2.4)

0.65 (⫺1.7 to 0.4)

.24

4.2 (3.0)

5.2 (3.0)

0.61 (⫺0.90 to 2.1)

.25

4 wk

3.7 (2.7)

3.2 (2.5)

0.55 (⫺0.68 to 1.7)

.38

3.4 (3.1)

3.2 (3.4)

0.52 (⫺1.8 to 1.2)

.33

2 wk

17.8 (12.5)

16.4 (12.2)

1.5 (⫺4.2 to 7.0)

.60

16.5 (31.4)

16.6 (30.7)

0.04 (⫺8.0 to 8.1)

.98

4 wk

15.2 (13.8)

12.8 (13.5)

2.3 (⫺3.8 to 8.4)

.46

13.1 (31.7)

12.7 (34.7)

0.45 (⫺8.6 to 7.7)

.87

16.4 (7.5)

18.1 (6.0)

1.6 (⫺0.48 to 1.6)

.31

15.5 (10.4)

17.0 (10.5)

1.5 (⫺3.3 to 6.2)

.37

21.9 (18.4)

20.3 (17.2)

1.5 (⫺6.8 to 9.8)

.71

16.8 (28.3)

15.1 (28.2)

1.7 (⫺12.6 to 9.2)

.65

Physical activity subscale

14.0 (7.8)

15.3 (7.9)

1.7 (⫺5.5 to 2.1)

.38

12.4 (10.5)

14.2 (11.9)

1.8 (⫺6.6 to 3.0)

.29

Work subscale

18.5 (16.9)

17.8 (16.8)

0.68 (⫺7.4 to 8.8)

.87

14.5 (28.3)

11.6 (31.7)

2.9 (⫺8.1 to 13.9)

.44

2 wk

5.5 (3.0)

5.6 (2.5)

⫺0.14 (⫺1.4 to 1.2)

.83

6.1 (4.5)

6.2 (4.6)

0.12 (⫺1.5 to 1.2)

.85

4 wk

6.8 (3.0)

6.9 (3.0)

⫺0.30 (⫺1.7 to 1.3)

.83

7.1 (4.6)

7.5 (5.2)

0.44 (⫺1.8 to 0.9)

.52

2 wk

9.7 (2.2)

9.6 (1.9)

0.12 (⫺0.81 to 1.1)

.76

10.1 (3.4)

10.0 (3.4)

0.16 (⫺1.13 to 0.79)

.74

4 wk

10.8 (2.0)

10.5 (2.4)

0.25 (0.81 to 1.3)

.65

11.1 (3.3)

10.8 (3.9)

0.27 (⫺0.70 to 1.2)

.58

68

69

Numeric Pain Rating Scale

e

Body diagram (symptom distribution)f

Fear-Avoidance Beliefs Questionnaireg 2 wk Physical activity subscaleh Work subscale

i

4 wk

Satisfaction ratingj

Global Rating of Change Scalek

Improved at 4 wk (%)

a Values are mean (SD) unless otherwise stated. MTEXTraction group⫽patients who received manual therapy, exercise, and intermittent cervical traction; MTEX group⫽patients who received manual therapy, exercise, and sham intermittent cervical traction; CI⫽confidence interval. b Adjusted values from mixed-models analysis. c Range of scores⫽0 –50; higher scores represent higher levels of disability. d Range of scores⫽0 –10; higher scores represent greater levels of function. e Range of scores⫽0 –10, where 0⫽“no pain.” f Range of scores⫽0 – 44; higher scores represent greater area of symptom distribution. g Range of scores⫽0 –30; higher scores represent higher levels of fear avoidance. h Range of scores⫽0 – 66; higher scores represent higher levels of fear avoidance. i 2 categories: deep tendon reflexes and myotome assessment. j Range of scores⫽0 –10, where 10⫽“completely satisfied.” k Range of scores⫽0 –13; scores ⱖ10 signify clinically meaningful improvement.

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Manual Therapy, Exercise, and Traction for Cervical Radiculopathy traction yielded no additional benefit to a program of manual therapy and exercise. Regardless of group assignment (MTEX versus MTEXTraction), patients with CR experienced significant improvements in both primary and secondary outcomes following 4 weeks of standardized physical therapy intervention. Although there were no significant differences between groups with any of the outcome measures, the precision of the point estimates of the treatment effects must be considered. At the 2-week follow-up, the lower boundary of the 95% CI for the NDI was ⫺7.0 (Tab. 3). This value meets the threshold for meaningful clinically important change of the NDI (7.0). Furthermore, at the 4-week follow-up, the lower boundary of the 95% CI for the NPRS was ⫺1.8 (Tab. 3). This value exceeds the threshold for meaningful clinically important change of the NPRS (1.3) adopted for this study. Thus, we cannot confidently exclude a treatment effect for these variables at these specific time points. Although statistically significant changes over time were found in both groups with all of the primary outcome measures, the threshold for minimum clinically important change was surpassed with the NPRS (n⫽47 [67%]) and the PSFS (n⫽44 [64%]) for those patients who completed the 4-week follow-up. A total of 2 points of change on the PSFS has been found to exceed the threshold for minimal clinically important change in patients with CR.29 A change of 1.3 points on the NPRS recently was found to meet the threshold for minimal clinically important change in patients with neck pain.27 As no study has identified a minimal clinically important change value in patients with CR, this change score (1.3 points) on the NPRS was adopted for this study. Of the patients who completed the 638

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4-week follow-up, only 32 (46%) surpassed the minimal clinically important change of at least 7 points on the NDI.29 A recent study27 suggests that the minimal clinically important change on the NDI may be more than twice as high as the original reported threshold of 7 points in patients with mechanical neck pain. With these inconsistencies regarding the appropriate threshold for clinically important difference, perhaps the responsiveness to change of the NDI may not be sufficient in this patient population. As the NDI is a commonly used self-report measure in patients with all neck-related disorders, future studies with larger sample sizes should investigate to detect change in patient status in conjunction with the NPRS, PSFS, and GROC in patients with CR. The present study used a CPR to identify the presence of CR.12 The CPR has a sensitivity of 0.39 (95% CI⫽0.16 to 0.61), a specificity of 0.99 (95% CI⫽0.97 to 1.00), and a positive likelihood ratio of 30.3 (95% CI⫽1.7 to 538.2) when all 4 test items are positive. The CPR has a sensitivity of 0.24 (95% CI⫽0.05 to 0.43), a specificity of 0.94 (95% CI⫽0.88 to 1.00), and a positive likelihood ratio of 6.1 (95% CI⫽2.0 to 18.6)] when 3 of 4 tests are positive. We used 3 of 4 criteria that are positive for eligibility despite other studies using 4 of 4 criteria, due to the narrower CI and the lower-bound estimate for 3 of 4 criteria. To date, the CPR used in the present study has not been validated. The protocol for the intermittent cervical traction may have been the reason a treatment effect was not identified. Although a multitude of traction parameters are used in the clinical setting, there is no convincing evidence to suggest which parameters are most effective in the management of CR. Cleland et al21 used an on/off cycle of 30/10 and a

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traction angle of approximately 25 degrees, increasing force by 0.45 to 0.91 kg (1–2 lb) per visit, whereas Waldrop et al18 used an on/off cycle of 20/10 and a 15- to 24-degree angle of traction. Each of these case studies started with a traction force of 8.18 kg (18 lb) and monitored the centralization and reduction of symptoms to determine progression of force. Furthermore, both studies performed traction for 15 minutes and used a minimum traction force during the off cycle. In the clinical trial by Joghataei et al,17 a 13.64-kg (30-lb) traction force at a 24-degree angle of pull was used for a period of 20 minutes, with an on/off cycle of 7/5. In the present study, we used a longer duration of pull (on/off cycle of 50/10), a 15degree flexion angle, and no traction force during the off cycle. In this study, the average traction force was 11.64 kg (SD⫽2.8, range⫽9.09 – 14.09) (25.6 lb, SD⫽2.8, range⫽20 – 31) for the MTEXTraction group and an average of 1.65 kg (SD⫽0.70, range⫽0.90 – 4.52) (3.5 lb, SD⫽1.1, range⫽2.0 –5.0) for the MTEX group. Interestingly, Zybergold and Piper24 found no significant difference in pain reduction among groups of patients with CR who received static traction, intermittent traction, manual traction, and treatment without traction. Possibly, more-aggressive traction protocols (more force or greater frequency) may have had a greater effect on the patient sample in the present study. Moreover, we are unable to determine whether the sham traction force of no greater than 2.3 kg (5 lb) had a treatment effect on the patients in this study. Although a control group receiving a “subtherapeutic” traction force has its limitations, we feel this was the best control choice to address the setup, subsequent force production, and treatment time involved with this modality. In this study, there appeared to July 2009

Manual Therapy, Exercise, and Traction for Cervical Radiculopathy be no relationship between the amount of traction force used and perceived recovery (Fig. 2). The manual therapy procedures used in this study were a combination of thrust and nonthrust manipulation techniques designed to centralize and reduce the cervical and upper-extremity symptoms. In order to simulate clinical practice, the therapist was allowed to select individual techniques based on centralization or reduction of symptoms and the patient’s response to treatment. If a manual therapy procedure centralized or reduced the patient’s symptoms, this procedure continued to be used until there was no further benefit. Conversely, if a manual procedure worsened or peripheralized the patient’s symptoms, this procedure was abandoned and another technique was selected. The procedures are modifications of techniques first described by McKenzie,25 Maitland,38 Greenman,39 and Vicenzino et al.40 An average of 2 manual procedures were performed on both the thoracic and cervical spines during each visit. Supine thoracic thrust manipulation, cervical retraction nonthrust manipulation, and cervical retraction exercise were the most commonly used procedures in the study (Fig. 3). Although thoracic manipulation procedures have been shown to have a significant short-term treatment effect on patients with mechanical neck pain,41,42 these techniques have not been studied in patients with CR. Restoration of normal biomechanics to the thoracic spine may have a role in lowering mechanical stresses and improving distribution of joint forces in the cervical spine.41,43,44 Manipulations directed at the cervical spine were not performed in this study, as supporting evidence is sparse in patients with CR45 and considerable attention has been devoted to the risk of serious complications.46 – 48

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Figure 2. Average force of traction (per subject) versus Global Rating of Change Scale (GROC) scores (range⫽0 –13; scores ⱖ10 signify clinically meaningful improvement). There appears to be no relationship between the amount of traction force used and perceived recovery. MTEXTraction group⫽patients who received manual therapy, exercise, and intermittent cervical traction; MTEX group⫽patients who received manual therapy, exercise, and sham intermittent cervical traction.

The exercises used in this study included strengthening of the scapulothoracic and deep neck flexors, as well as cervical retraction and extension exercises. Scapular strengthening and deep neck flexor exercises have provided some benefit in previous studies.21,22 Cervical retraction is thought to improve resting neck posture, relieve neck pain or radicular or referred pain,25 and possibly decompress neural elements in patients with CR.49 An average of 2 exercises per visit were used in the present study. This clinical trial supports previous randomized clinical trials demonstrating effective conservative man-

agement of CR17,23,24 and cervicobrachial pain14,15,24 Prior to the present study, only one randomized clinical trial isolated the effect of intermittent cervical traction, finding that exercise and intermittent cervical traction were superior to exercise (cervical isometrics) and ultrasound on the outcome of grip strength after 5 visits in patients with C7 radiculopathy.17 However, there were no significant differences between groups at 10 visits (discharge from physical therapy).17 We acknowledge several limitations of this study. First, we used a CPR to identify the presence of cervical radiculopathy that has yet to be vali-

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B

C

Figure 3. (A) Supine thoracic thrust manipulation, (B) cervical retraction mobilization, (C) cervical retraction exercise.

dated, which may imply less-thanoptimal diagnostic accuracy of this condition. Second, we are unsure of how effective the blinding was during the course of treatment, as the patients were not asked whether they could identify which group they were in at the 4-week followup. If the patients thought they were receiving the sham treatment, this may have had an influence on their outcome. Third, the lack of a strictly recorded, dose-specific home exercise program maintained during the course of treatment was a limitation. Fourth, without a control group (a group not receiving treatment), we are unsure whether there was a 640

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spontaneous resolution of symptoms over the course of this 4-week treatment.

Conclusion The addition of mechanical intermittent traction does not appear to improve outcomes for patients with CR who are already receiving manual therapy and exercise. Although traction provided no additional benefit in this study, subsequent investigations examining traction at different dosages may be of interest in this patient population. The effect of CR can be disabling, and continued research in the areas of diagnosis and

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treatment of this condition is of paramount importance. Mr Young, Dr Michener, Dr Cleland, and Dr Aguilera provided concept/idea/research design. Mr Young, Dr Michener, Dr Cleland, and Dr Snyder provided writing. Mr Young, Dr Michener, Dr Aguilera, and Dr Snyder provided data analysis. Mr Young and Dr Michener provided project management and fund procurement. Dr Michener, Dr Cleland, Dr Aguilera, and Dr Snyder provided consultation (including review of manuscript before submission). The authors thank Advance Rehabilitation and Fredericksburg Orthopaedics for their support of this study; physical therapists Chris Brown, Dan Walker, Jon Lamb, and Richard Linkonis for their patient recruiting

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Manual Therapy, Exercise, and Traction for Cervical Radiculopathy and treatment efforts; Amee Seitz for her help with data analysis; and Jennifer Chastain for her help with study/data management. A final thanks to Robin Saunders for her support of this study. The study was approved by the Rocky Mountain University of Health Professions Internal Review Board. Platform presentations of this research were given at the Combined Section Meetings of the American Physical Therapy Association; February 6 –9, 2008; Nashville, Tennessee; and February 9 –12, 2009; Las Vegas, Nevada. This study was funded by a grant from the Saunders Group. This article was received September 13, 2008, and was accepted March 25, 2009. DOI: 10.2522/ptj.20080283

References 1 Radhakrishnan K, Litchy WJ, O’Fallon WM, Kurland LT. Epidemiology of cervical radiculopathy: a population-based study from Rochester, Minnesota, 1976 through 1990. Brain. 1994;117(pt 2):325–335. 2 Tanaka N, Fujimoto Y, An HS, et al. The anatomic relation among the nerve roots, intervertebral foramina, and intervertebral discs of the cervical spine. Spine. 2000;25: 286 –291. 3 Cloward RB. Cervical diskography: a contribution to the etiology and mechanism of neck, shoulder and arm pain. Ann Surg. 1959;150:1052–1064. 4 Yoss RE, Corbin KB, MacCarty CS, Love JG. Significance of symptoms and signs in localization of involved root in cervical disk protrusion. Neurology. 1957;7: 673– 683. 5 Persson LC, Carlsson JY. Headache in patients with neck-shoulder-arm pain of cervical radicular origin. Headache. 1999;39: 218 –224. 6 Spurling RG, Scoville WB. Lateral rupture of the cervical intervertebral discs: a common cause of shoulder and arm pain. Surg Gynecol Obstet. 1944;78:350 –358. 7 Daffner SD, Hilibrand AS, Hanscom BS, et al. Impact of neck and arm pain on overall health status. Spine. 2003;28: 2030 –2035. 8 American Association of Electrodiagnostic Medicine, American Academy of Physical Medicine and Rehabilitation. The electrodiagnostic evaluation of patients with suspected cervical radiculopathy: literature review on the usefulness of needle electromyography. Muscle Nerve. 1999; 22:S213–S221. 9 Larsson EM, Holtas S, Cronqvist S, Brandt L. Comparison of myelography, CT myelography and magnetic resonance imaging in cervical spondylosis and disk herniation: Pre- and postoperative findings. Acta Radiol. 1989;30:233–239.

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10 Nardin RA, Patel MR, Gudas TF, et al. Electromyography and magnetic resonance imaging in the evaluation of radiculopathy. Muscle Nerve. 1999;22:151–155. 11 Wilson DW, Pezzuti RT, Place JN. Magnetic resonance imaging in the preoperative evaluation of cervical radiculopathy. Neurosurgery. 1991;28:175–179. 12 Wainner RS, Fritz JM, Irrgang JJ, et al. Reliability and diagnostic accuracy of the clinical examination and patient selfreport measures for cervical radiculopathy. Spine. 2003;28:52– 62. 13 Guide to Physical Therapist Practice. 2nd ed. Phys Ther. 2001;81:9 –746. 14 Allison GT, Nagy BM, Hall T. A randomized clinical trial of manual therapy for cervicobrachial pain syndrome: a pilot study. Man Ther. 2002;7:95–102. 15 Coppieters MW, Stappaerts KH, Wouters LL, Janssens K. The immediate effects of a cervical lateral glide treatment technique in patients with neurogenic cervicobrachial pain. J Orthop Sports Phys Ther. 2003;33:369 –378. 16 Moeti P, Marchetti G. Clinical outcome from mechanical intermittent cervical traction for the treatment of cervical radiculopathy: a case series. J Orthop Sports Phys Ther. 2001;31:207–213. 17 Joghataei MT, Arab AM, Khaksar H. The effect of cervical traction combined with conventional therapy on grip strength on patients with cervical radiculopathy. Clin Rehabil. 2004;18:879 – 887. 18 Waldrop MA. Diagnosis and treatment of cervical radiculopathy using a clinical prediction rule and a multimodal intervention approach: a case series. J Orthop Sports Phys Ther. 2006;36:152–159. 19 Browder DA, Erhard RE, Piva SR. Intermittent cervical traction and thoracic manipulation for management of mild cervical compressive myelopathy attributed to cervical herniated disc: a case series. J Orthop Sports Phys Ther. 2004;34:701–712. 20 Constantoyannis C, Konstantinou D, Kourtopoulos H, Papadakis N. Intermittent cervical traction for cervical radiculopathy caused by large-volume herniated disks. J Manipulative Physiol Ther. 2002;25: 188 –192. 21 Cleland JA, Whitman JM, Fritz JM, Palmer JA. Manual physical therapy, cervical traction, and strengthening exercises in patients with cervical radiculopathy: a case series. J Orthop Sports Phys Ther. 2005;35:802– 811. 22 Cleland JA, Fritz JM, Whitman JM, Heath R. Predictors of short-term outcome in people with a clinical diagnosis of cervical radiculopathy. Phys Ther. 2007;87: 1619 –1632. 23 Walker MJ, Boyles RE, Young BA, et al. The effectiveness of manual physical therapy and exercise for mechanical neck pain: a randomized clinical trial. Spine. 2008;33:2371–2378. 24 Zylbergold RS, Piper MC. Cervical spine disorders: a comparison of three types of traction. Spine. 1985;10:867– 871.

25 McKenzie R. The Cervical and Thoracic Spine: Mechanical Diagnosis and Therapy. Waikanae, New Zealand: Spinal Publications Ltd; 1990. 26 Jensen MP, Karoly P, Braver S. The measurement of clinical pain intensity: a comparison of six methods. Pain. 1986;27: 117–126. 27 Cleland JA, Childs JD, Whitman JM. Psychometric properties of the Neck Disability Index and Numeric Pain Rating Scale in patients with mechanical neck pain. Arch Phys Med Rehabil. 2008;89:69 –74. 28 Vernon H, Mior S. The Neck Disability Index: a study of reliability and validity. J Manipulative Physiol Ther. 1991;14: 409 – 415. 29 Cleland JA, Fritz JM, Whitman JM, Palmer JA. The reliability and construct validity of the Neck Disability Index and PatientSpecific Functional Scale in patients with cervical radiculopathy. Spine. 2006;31: 598 – 602. 30 Chatman AB, Hyams SP, Neel JM, et al. The Patient-Specific Functional Scale: measurement properties in patients with knee dysfunction. Phys Ther. 1997;77:820 – 829. 31 Waddell G, Newton M, Henderson I, et al. A Fear-Avoidance Beliefs Questionnaire (FABQ) and the role of fear-avoidance beliefs in chronic low back pain and disability. Pain. 1993;52:157–168. 32 Landers MR, Creger RV, Baker CV, Stutelberg KS. The use of fear-avoidance beliefs and nonorganic signs in predicting prolonged disability in patients with neck pain. Man Ther. 2008;13:239 –248. 33 Werneke M, Hart DL, Cook D. A descriptive study of the centralization phenomenon: a prospective analysis. Spine. 1999; 24:676 – 683. 34 Jaeschke R, Singer J, Guyatt GH. Measurement of health status: ascertaining the minimal clinically important difference. Control Clin Trials. 1989;10:407– 415. 35 Leggin BG, Michener LA, Shaffer MA, et al. The Penn Shoulder Score: reliability and validity. J Orthop Sports Phys Ther. 2006;36:138 –151. 36 Smidt N, van der Windt DA, Assendelft WJ, et al. Interobserver reproducibility of the assessment of severity of complaints, grip strength, and pressure pain threshold in patients with lateral epicondylitis. Arch Phys Med Rehabil. 2002;83:1145–1150. 37 Smidt N, van der Windt DA, Assendelft WJ, et al. Corticosteroid injections, physiotherapy, or a wait-and-see policy for lateral epicondylitis: a randomised controlled trial. Lancet. 2002;359(9307):657– 662. 38 Maitland GD. Vertebral Manipulation. 5th ed. London, United Kingdom: Butterworth-Heinemann; 1996. 39 Greenman P. Principles of Manual Medicine. 2nd ed. Baltimore, MD: Williams & Wilkins; 1996. 40 Vicenzino B, Neal R, Collins D, Wright A. The displacement, velocity and frequency profile of the frontal-plane motion produced by the cervical lateral glide treatment technique. Clin Biomech (Bristol, Avon) 1999;14:515–521.

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Manual Therapy, Exercise, and Traction for Cervical Radiculopathy 41 Cleland JA, Childs JD, McRae M, et al. Immediate effects of thoracic manipulation in patients with neck pain: a randomized clinical trial. Man Ther. 2005;10:127–135. 42 Cleland JA, Glynn P, Whitman JM, et al. Short-term effects of thrust versus nonthrust mobilization/manipulation directed at the thoracic spine in patients with neck pain: a randomized clinical trial. Phys Ther. 2007;87:431– 440. 43 Norlander S, Nordgren B. Clinical symptoms related to musculoskeletal neckshoulder pain and mobility in the cervicothoracic spine. Scand J Rehabil Med. 1998;30:243–251.

44 Norlander S, Gustavsson BA, Lindell J, Nordgren B. Reduced mobility in the cervicothoracic motion segment—a risk factor for musculoskeletal neck-shoulder pain: a two-year prospective follow-up study. Scand J Rehabil Med. 1997;29:167–174. 45 Schliesser JS, Kruse R, Fallon LF. Cervical radiculopathy treated with chiropractic flexion distraction manipulation: a retrospective study in a private practice setting. J Manipulative Physiol Ther. 2003; 26:E19. 46 Haldeman S, Kohlbeck FJ, McGregor M. Risk factors and precipitating neck movements causing vertebrobasilar artery dissection after cervical trauma and spinal manipulation. Spine. 1999;24:785–794.

47 Haldeman S, Kohlbeck FJ, McGregor M. Stroke, cerebral artery dissection, and cervical spine manipulation therapy. J Neurol. 2002;249:1098 –1104. 48 Haldeman S, Kohlbeck FJ, McGregor M. Unpredictability of cerebrovascular ischemia associated with cervical spine manipulation therapy: a review of sixty-four cases after cervical spine manipulation. Spine. 2002;27:49 –55. 49 Abdulwahab SS, Sabbahi M. Neck retractions, cervical root decompression, and radicular pain. J Orthop Sports Phys Ther. 2000;30:4 –9.

Appendix. Primary and Secondary Outcome Measuresa Measure

a b

Scale and Scoring

Reliability (95% CI)

MCIC Value

Neck Disability Index28,29

Self-report measure containing 10 items (scored 0–5). Total score out of 50 possible points (0⫽“no disability,” 50⫽“severe disability”).

ICC⫽.68 (.03 to .90)

ⱖ7 points

Patient-Specific Functional Scale29,30

Self-report activity limitations rated from 0 (“inability to perform activity”) to 10 (“able to perform activity as well as prior to onset of symptoms”). Activity scores averaged (higher score⫽less disability)

ICC⫽.82 (.54 to .93)

ⱖ2 points

Numeric Pain Rating Scale26,27

Self-report measure with scores ranging from 0 (“no pain”) to 10 (“worst pain imaginable”).

ICC⫽.63 (.28 to .96)

ⱖ1.3 points

Global Rating of Change Scale34

Self-report Likert scale with scores ranging from 0 (“a very great deal worse”) to 7 (“about the same”) to 13 (“a very great deal better”). A score of ⱖ10 signifies improvement.

Pain diagram33

Self-report measure indicating type and location of symptoms on a standardized body chart. Total score is out of 44 points (higher scores indicate greater symptom distribution).

Fear-Avoidance Beliefs Questionnaire31,32

Self-report measure that quantifies fear and avoidance beliefs in patients with low back pain and neck pain. Physical activity subscale: range of scores⫽0–30; Work subscale: range of scores⫽0–66; higher scores represent higher levels of fear avoidance.

Satisfaction rating35

Self-report measure with scores ranging from 0 (“not satisfied”) to 10 (“very satisfied”) with the use of the neck and arm.

ICC⫽.93

Not reported

Grip strength36,37

Average of 2 trials measured with a Jamar hand dynamometerb

ICC⫽.87–.97

Not reported

ⱖ10 points

kappa⫽.92

Not reported

Not reported

CI⫽confidence interval, MCIC⫽minimal clinically important change, ICC⫽intraclass correlation coefficient. Sammons Preston, PO Box 5071, Bolingbrook, IL 60440-5071.

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Research Report Short-term Effects of High-Intensity Laser Therapy Versus Ultrasound Therapy in the Treatment of People With Subacromial Impingement Syndrome: A Randomized Clinical Trial

A. Santamato, MD, is Assistant Professor, Department of Physical Medicine and Rehabilitation, University of Foggia, Foggia, Italy.

Andrea Santamato, Vincenzo Solfrizzi, Francesco Panza, Giovanna Tondi, Vincenza Frisardi, Brian G. Leggin, Maurizio Ranieri, Pietro Fiore

Background. Subacromial impingement syndrome (SAIS) is a painful condition resulting from the entrapment of anatomical structures between the anteroinferior corner of the acromion and the greater tuberosity of the humerus. Objective. The aim of this study was to evaluate the short-term effectiveness of high-intensity laser therapy (HILT) versus ultrasound (US) therapy in the treatment of SAIS.

Design. The study was designed as a randomized clinical trial. Setting. The study was conducted in a university hospital. Patients. Seventy patients with SAIS were randomly assigned to a HILT group or a US therapy group.

Intervention. Study participants received 10 treatment sessions of HILT or US therapy over a period of 2 consecutive weeks. Measurements. Outcome measures were the Constant-Murley Scale (CMS), a visual analog scale (VAS), and the Simple Shoulder Test (SST).

Results. For the 70 study participants (42 women and 28 men; mean [SD] age⫽54.1 years [9.0]; mean [SD] VAS score at baseline⫽6.4 [1.7]), there were no between-group differences at baseline in VAS, CMS, and SST scores. At the end of the 2-week intervention, participants in the HILT group showed a significantly greater decrease in pain than participants in the US therapy group. Statistically significant differences in change in pain, articular movement, functionality, and muscle strength (force-generating capacity) (VAS, CMS, and SST scores) were observed after 10 treatment sessions from the baseline for participants in the HILT group compared with participants in the US therapy group. In particular, only the difference in change of VAS score between groups (1.65 points) surpassed the accepted minimal clinically important difference for this tool.

Limitations. This study was limited by sample size, lack of a control or placebo group, and follow-up period.

Conclusions. Participants diagnosed with SAIS showed greater reduction in pain and improvement in articular movement functionality and muscle strength of the affected shoulder after 10 treatment sessions of HILT than did participants receiving US therapy over a period of 2 consecutive weeks.

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V. Solfrizzi, MD, PhD, is Assistant Professor, Memory Unit, Center for Aging Brain, Department of Geriatrics, University of Bari, Bari, Italy. F. Panza, MD, PhD, is Assistant Professor, Memory Unit, Center for Aging Brain, Department of Geriatrics, University of Bari, Policlinico, Piazza G Cesare, 11, 70124 Bari, Italy. Address all correspondence to Dr Panza at: [email protected]. G. Tondi, MD, is affiliated with the Department of Neurological and Psychiatric Sciences, University of Bari. V. Frisardi, MD, is affiliated with the Memory Unit, Center for Aging Brain, Department of Geriatrics, University of Bari. B.G. Leggin, PT, DPT, OCS, is Advanced Clinician II, Good Shepherd Penn Partners, Penn Presbyterian Medical Center, Philadelphia, Pennsylvania. M. Ranieri, MD, is Assistant Professor, Department of Neurological and Psychiatric Sciences, University of Bari. P. Fiore, MD, is Professor, Department of Physical Medicine and Rehabilitation, University of Foggia. [Santamato A, Solfrizzi V, Panza F, et al. Short-term effects of highintensity laser therapy versus ultrasound therapy in the treatment of people with subacromial impingement syndrome: a randomized clinical trial. Phys Ther. 2009; 89:643– 652.] © 2009 American Physical Therapy Association

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Post a Rapid Response or find The Bottom Line: www.ptjournal.org Physical Therapy f

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S

ubacromial impingement syndrome (SAIS) is the entrapment of the supraspinatus muscle tendon between the anteroinferior corner of the acromion and the greater tuberosity of the humerus.1 This entrapment is responsible for degenerative lesions of the tendon. Several pathoetiological mechanisms have been proposed; these include continuous lesions caused during the movement of the arm by subacromial contact, the subcoracoid space, the coracoacromial ligament, and the coracoacromial articulation; alteration of acromial morphology2; alteration of arterial vascularization of the humeral head3–5; overuse syndrome; and alteration of the tensile properties of the supraspinatus tendon.6 Subacromial impingement syndrome is characterized by severe pain in the anterior-posterior and lateral shoulder, extending to the deltoid and biceps areas. The painful symptoms increase at night and during abduction, forced internal rotation, and resisted motions. Neer7,8 described 3 stages of impingement. Stage I impingement is characterized by edema and hemorrhage of the subacromial bursa and rotator cuff and typically is found in patients who are less than 25 years old. Stage II impingement represents irreversible changes, such as fibrosis and tendinopathy of the rotator cuff, and typically is found in patients who are 25

Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on May 29, 2009, at www.ptjournal.org.

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to 40 years old. Stage III impingement is marked by more-chronic changes, such as partial or complete tears of the rotator cuff, and usually is seen in patients who are more than 40 years old. Management of this pathology includes numerous interventions, depending on pain severity and anatomopathological classification. Analgesic and nonsteroidal antiinflammatory drugs,9 steroid injections,10 and physical therapy (ultrasound [US] therapy, laser therapy, manual therapy, extracorporeal shock wave therapy, interferential current therapy, and acupuncture)11–22 have been reported, often with mixed results. Systematic reviews of clinical trials have demonstrated little benefit from nonsteroidal anti-inflammatory drugs and steroid injections; some studies have suggested various physical agents to be effective in minimizing the symptoms by reducing inflammation.23 Although pain can reduce their efficacy, rehabilitative exercise approaches for the treatment of SAIS include active and passive range of motion (ROM) exercises, stretching, Codman exercises, and isometric and isotonic exercises.19,23,24 The effectiveness of conservative treatment is mixed, and surgical treatment may be indicated in cases resistant to conservative treatment.25 Several systematic reviews have suggested that physical therapy has not provided unequivocal results because of the notable variability of anatomopathological lesions.11–22 In particular, limited evidence has suggested that exercise, joint mobilization, and laser therapy are effective in decreasing pain and improving function in patients with SAIS.20,22 Some systematic reviews have reported the limited effectiveness of US therapy for this condition.20,21 However, other studies have shown US therapy to be effective in improv-

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ing the symptoms.26,27 According to the recommendations of the Philadelphia Panel, an expert panel on selected rehabilitation interventions for shoulder pain, US therapy is an acceptable physical therapy intervention for SAIS.16 Laser therapy is based on the belief that laser radiation (and possibly monochromatic light in general) is able to alter cellular and tissue functions in a manner that is dependent on the characteristics of the light itself (eg, wavelength, coherence).28 By definition, low-intensity laser therapy (LILT) (often also known as “low-energy” or “low-power” laser therapy) takes place at low radiation intensities. Therefore, it is assumed that any biologic effects are secondary to the direct effects of photonic radiation and are not the result of thermal processes.29 More recently, high-intensity laser therapy (HILT), which involves higher-intensity laser radiation and which causes minor and slow light absorption by chromophores, has been used. This absorption is obtained not with concentrated light but with diffuse light in all directions (scattering phenomenon), increasing the mitochondrial oxidative reaction and adenosine triphosphate, RNA, or DNA production (photochemistry effects) and resulting in the phenomenon of tissue stimulation (photobiology effects).30 Some systematic reviews and randomized clinical trials have suggested that LILT could be an effective physical therapy intervention for decreasing pain and functional loss or disability for patients with SAIS20,31,32 or could have analgesic and tissue repair actions.33 Nonetheless, the effectiveness of laser therapy is still in question because LILT has not provided convincing results in patients with shoulder tendinopathies.34,35

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High-Intensity Laser Therapy Versus Ultrasound Therapy for Subacromial Impingement Syndrome Few studies have been conducted to compare the effectiveness of different physical therapies36 because of the difficulty in selecting homogeneous groups of patients to reduce the variability of the results. To our knowledge, no studies to date have been conducted on the possible effects of HILT on SAIS. The aim of the present study was to evaluate the short-term effectiveness of 2 different physical therapy modalities in the treatment of SAIS: HILT and US therapy.

fected shoulder, impaired rotation in the glenohumeral joint (as measured with goniometry), a history of acute trauma, known osteoarthritis in the acromioclavicular or glenohumeral joint, calcifications exceeding 2 cm in the rotator cuff tendons, signs of a rupture of the cuff, cervical myofascial pain syndrome, radicular pain, inflammatory rheumatic disease, systemic lupus erythematosus, diabetes mellitus type I or II, thyroid dysfunctions, pacemaker, neurological pathologies, or anxiety-depression syndromes.

Method Setting and Participants Consecutive outpatients attending the Department of Physical Medicine and Rehabilitation, University of Foggia, from September 2006 to July 2007 were invited to participate in the study. Patients had experienced shoulder pain for at least 4 weeks before the study. Diagnostic criteria for SAIS were the presence of shoulder pain, pain on abduction of the shoulder with a painful arch, a positive impingement sign (Hawkins sign),37 and a positive impingement test (relief of pain within 15 minutes after the injection of a local anesthetic [bupivacaine, 5 mL]) into the subacromial space). All patients also were evaluated by ultrasonography or magnetic resonance imaging of the shoulder to confirm the diagnosis of stage I or II.7 We used the diagnostic criteria for ultrasonography described by Naredo and colleagues.38 This technique included a dynamic examination of the supraspinatus tendon obtained by moving the patient’s arm from a neutral position to 90 degrees of abduction to detect encroachment of the acromion into the rotator cuff. Patients were excluded from the study if they met any of the following criteria: anesthetic or corticosteroid injections within 4 weeks of study enrollment, surgery or previous fractures of the humeral head of the afJuly 2009

Patients received no other physical therapy intervention for shoulder pain during the study or in the 4 to 5 weeks before the study. After a complete description of the study was provided, written informed consent was obtained from all subjects or their relatives. The participants were instructed to avoid analgesic or antiinflammatory drugs for the duration of the treatment and to abstain from the execution of painful activities of daily living involving the affected shoulder. The participants kept a daily log of analgesic or antiinflammatory drug intake during the study period. A total of 85 consecutive patients (50 women and 35 men) were screened for study eligibility. At the end of the evaluation, 70 patients who were affected by SAIS (Neer stage I or II, 45 right shoulders and 25 left shoulders), had subacute or chronic pain, fulfilled the selection criteria, agreed to participate, and signed informed consent statements were enrolled in the study (42 women and 28 men; mean age⫽54.1 years, SD⫽9.0, range⫽35– 69; mean time since onset of pain⫽8.4 months, SD⫽9.8). These participants were randomly assigned to 2 groups: a group of 35 participants received HILT (20 women and 15 men), and a group of 35 participants received US therapy (22 women and 13 men). Reasons

for exclusion are shown in the Figure, which is a flow diagram of participant recruitment and retention. No participant reported taking analgesic or anti-inflammatory drugs during the study. All 70 participants completed the trial and were included in the analysis. Outcome Measures All of the participants in the present study were evaluated with a visual analog scale (VAS),39 the ConstantMurley Scale (CMS),40 and the Simple Shoulder Test (SST).41 The VAS is used to measure pain on a 10-cm horizontal axis between a left endpoint of “no shoulder pain” and a right endpoint of “worst pain ever.” The distance is measured, and pain is recorded on a 10-point scale.39 In the acute pain setting, the VAS has been shown to have very good test-retest reliability (intraclass correlation coefficient [ICC]⫽.99)42; this scale generally is accepted as a valid measure of acute pain, with good construct validity.43,44 At a recent consensus meeting of the Initiative on Methods, Measurement, and Pain Assessment in Clinical Trials (IMMPACT), the results of several studies on this issue were considered. It was suggested that raw score changes of approximately one point or percentage changes of approximately 15% to 20% represent the minimal clinically important difference (MCID) for the VAS and other, similar numerical rating scales (0 –10) for pain intensity.45 The CMS is a 100-point scoring system in which 35 points are derived from a patient’s report of pain and function.40 The remaining 65 points are allocated to a quantitative assessment of ROM and strength (forcegenerating capacity). The self-report assessment includes a single item for pain (15 points) and 4 items for activities of daily living (work, 4 points; recreation, 4 points; sleep, 2 points; and ability to work at various levels, 10 points). The quantitative assess-

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Figure. Flow diagram of recruitment and retention of participants with subacromial impingement syndrome for ultrasound therapy and high-intensity laser therapy.

ment includes ROM (forward elevation, 10 points; lateral elevation, 10 points; external rotation, 10 points; and internal rotation, 10 points) and power (scoring is based on the number of pounds of pull a patient can resist in abduction to a maximum of 25 points).40 This tool has good psychometric properties; the 646

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CMS score reflects shoulder function with accuracy, test-retest reliability (ICC⫽.80),46 and reproducibility.47 Unfortunately, to date, there are no studies providing data on the MCID for the CMS, despite the fact that for this tool, error estimates (95% confidence interval [CI] of the standard error of measurement [SEM]⫽

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⫾17.7)46 and responsiveness (standardized response mean⫽0.59),48 that is, the ability of a measure to detect change over time, have been reported. The SST is a series of 12 questions with dichotomous “yes” or “no” response options. One group of quesJuly 2009

High-Intensity Laser Therapy Versus Ultrasound Therapy for Subacromial Impingement Syndrome tions pertains to pain, and a second group of questions relates to function. Strength and ROM are not directly evaluated. A theoretical “normal” shoulder would result in a “yes” answer to all 12 questions. The goal of the SST is to compare pain and function before and after treatments.41 Content, criterion, and construct validity have been measured for the SST.49 Test-retest reliability (ICC⫽.99),50 internal consistency (Cronbach alpha⫽.85),51 error estimates (95% CI of the SEM⫽⫾22.8, calculated from a converted score range of 0 –100),51 and responsiveness (standardized response mean⫽0.82 and effect size⫽.83) have been reported for the SST. Unfortunately, at present, there are no data on the MCID for the SST. Randomization After the baseline examination, participants were randomly assigned to receive HILT or US therapy. Concealed allocation was performed with random numbers generated from the Web site http://www. random.org/ before the beginning of the study. The procedure Random Integer Generator allowed us to generate random integers. A priori it generated 100 random integers and, before the beginning of the study, the randomization number was already present. Individual, sequentially numbered index cards with the random assignments were prepared. The index cards were folded and placed in sealed opaque envelopes. A physician who was unaware of the baseline examination findings opened the envelopes to attribute the interventions according to the group assignments. Interventions The protocol involved the application of 2 different forms of physical therapy modalities for a total of 10 treatment sessions over a period of 2 consecutive weeks (5 days per week). A physiatrist (A.S.) with 6 July 2009

years of experience provided HILT, and a physical therapist with 7 years of experience provided US therapy. Participants in the HILT group received HILT with a neodymiumyttrium aluminum garnet laser that has a pulsating waveform produced by an HIRO 1.0 device (ASA srl*). The treatment consisted of a high peak power (1 kW), a wavelength of 1,064 nm, a maximum energy for a single impulse of 150 mJ, an average power of 6 W, a fluency of 760 mJ⶿cm2, and a duration for the single impulse of less than 150 milliseconds. A pulsating waveform (5,000 W/cm2) can transfer 1,000 times more light intensity to the soft tissues than a continuous waveform (5 W/cm2) with the same average power (1 W) and bright spot (0.2 cm2). These ultrashort impulses established a deep action in biological tissue (3– 4 cm), with a homogeneous distribution of the light source in the irradiated soft tissue but without excessive thermal enhancements. A standard handpiece endowed with fixed spacers was used to ensure the same distance to the skin and verticality of 90 degrees to the zone to be treated with a brightspot diameter of 5 mm. Three phases of treatment were performed for every session. An initial phase involved fast manual scanning (100 cm2/30 s) of the zones of muscular contracture, particularly for the upper trapezius and deltoid muscles and anteriorly for the pectoralis minor muscle. Scanning was performed in both transverse and longitudinal directions with the arm positioned in internal rotation and extension to expose the rotator cuff. In this phase, a total energy dose of 1,000 J was administered. An intermediate phase involved applying the handpiece with fixed * Arcugnano, Via Volta, 9 Vicenza, Italy.

spacers vertically to 90 degrees on the trigger points until a pain reduction of 70% to 80% was achieved. In this phase, the mean energy dose was 50 J. A final phase involved slow manual scanning (100 cm2/60 s) of the same areas treated in the initial phase until a total energy dose of 1,000 J was achieved. Three steps were predicted in the starting/initial and final phases of the treatment; the fluencies used were 510, 610, and 710 mJ/cm2, respectively. Therefore, the total dose of energy administered was approximately 2,050 J. The time to apply all 3 stages of HILT was approximately 10 minutes. Participants in the US therapy group received continuous US for 10 minutes with a SONOPLUS 492,† a device that was operated at a frequency of 1 MHz, an intensity of 2 W/cm2, and a duty cycle of 100%. The transducer head had an area of 5.8 cm2 and an effective radiating area of 4.6 cm2. The treating physical therapist, using the technique of slow circular movements, applied the transducer head over the superior and anterior periarticular regions of the participant’s glenohumeral joint and on the shoulder trigger points, covering an area of approximately 20 cm2 (4 times the effective radiating area). Participants were assessed by a physical medicine physician at the baseline (before the first treatment session) and at the end of physical therapy (after the last treatment session). Moreover, the pretreatment and posttreatment clinical evaluations (VAS, CMS, and SST) were done by the same tester. It is important to remember that the physicians who performed the clinical evaluations of the participants were unaware of the group assignments. All participants in the 2 treatment groups received † Enraf-Nonius BV, Vareseweg 127, Rotterdam, the Netherlands.

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High-Intensity Laser Therapy Versus Ultrasound Therapy for Subacromial Impingement Syndrome Table 1. Baseline Demographic and Clinical Characteristics of Participants With Subacromial Impingement Syndrome (SAIS) in High-Intensity Laser Therapy (HILT) and Ultrasound (US) Therapy Groups HILT Group (nⴝ35)

US Therapy Group (nⴝ35)

P

X (SD)

54.2 (8.2)

54.0 (9.8)

.93a

Range

38–69

35–69

X (SD)

8.7 (8.8)

8.1 (10.8)

Range

1–36

1–42

20/15

22/13

.63c

SAIS Neer stage I

13

14

.81c

SAIS Neer stage II

22

21

Characteristic

Results

Age, y

Time since onset of pain, mo

Sex (female/male)

.82b

Diagnosis (n)

a b c

As determined by an independent 2-sample t test. As determined by the Mann-Whitney U test. As determined by the Pearson chi-square test.

10 treatment sessions in the 2-week period. Sample Size Determination The sample size and power calculations were performed with nQuery Advisor statistical software (version 6.0).‡ Sample sizes of 35 for the HILT group and 35 for the US therapy group achieved a power of 80% to detect a difference of 50% in the VAS (score⫽1.0 point) in a design with 2 repeated measurements when the standard deviation was 1.5, the correlation between observations for the same participant was .7, and the alpha level was .05. Data Analysis All analyses were performed with SAS statistical software (version 9.1).§ Frequency distributions as well as means and standard deviations were used for descriptive purposes. At the baseline, differences in age and time since the onset of pain between treatment groups were ‡

Statistical Solutions Ltd, 7B Airport East Business Park, Farmer’s Cross, Cork, Ireland (www.statsol.ie). § SAS Institute Inc, PO Box 8000, Cary, NC 27511.

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Council-CNR-Targeted Project on Aging grants 9400419PF40 and 95973PF40). The funding agencies had no role in the design, conduct, or reporting of the study.

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analyzed with an independent 2-sample t test and a Mann-Whitney U test, respectively. Differences in sex and SAIS Neer stage frequency distributions were evaluated with a Pearson chi-square test. Differences between treatment groups in change scores at the baseline and after 10 treatment sessions over a period of 2 consecutive weeks were analyzed with an independent 2-sample t test. Repeated measurements obtained before and after treatments within groups were analyzed with a pairedmatched t test. A 2-way repeatedmeasures analysis of variance (ANOVA) was performed to estimate differences between (group effect) and within (time and time ⫻ group effects) treatment groups for each studied outcome. The statistical inferences were adjusted according to Bonferroni inequality (P values corresponding to .05/6⫽.008 and .01/ 6⫽.002). The alpha level for significance was set at .05. Role of the Funding Source This work was supported by the Italian Longitudinal Study on Aging (ILSA) (Italian National Research

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Table 1 summarizes the baseline clinical and demographic characteristics of the subjects enrolled in the study. Table 2 summarizes test performance at the baseline and at the completion of the study (after 10 treatment sessions over a period of 2 consecutive weeks) for each treatment group. A significant change in test performance was observed in both groups after the initiation of treatments (VAS: ANOVA F statistic for a time effect⫽435.73; df⫽1,68; P⬍.001; CMS: ANOVA F statistic for a time effect⫽800.98; df⫽1,68; P⬍.001; SST: ANOVA F statistic for a time effect⫽366.38; df⫽1,68; P⬍.001). Moreover, we found a significant difference in VAS scores when we compared US therapy with HILT (ANOVA F statistic for groups⫽10.863, P⫽.002), but we found no significant differences in CMS and SST scores between treatments. Finally, statistically significant differences in changes from the baseline after 10 treatment sessions by treatment group were observed (VAS: ANOVA F statistic for a time ⫻ group effect: 34.07; df⫽1,68; P⬍.001; CMS: ANOVA F statistic for a time ⫻ group effect⫽22.72; df⫽1,68; P⬍.001; SST: ANOVA F statistic for a time ⫻ group effect⫽7.88; df⫽1,68; P⫽.007). Multiple comparisons analyzing differences within groups were performed for the HILT group and the US therapy group, and the results are shown in Table 2. Multiple comparisons analyzing differences between groups also are shown in Table 3. Finally, we analyzed differences in change scores between groups after 10 treatment sessions over a period of 2 consecutive weeks; we found July 2009

High-Intensity Laser Therapy Versus Ultrasound Therapy for Subacromial Impingement Syndrome Table 2. Test Performance at Baseline and After Intervention for Participants With Subacromial Impingement Syndrome in High-Intensity Laser Therapy (HILT) and Ultrasound (US) Therapy Groups: Evaluation Within Groups and Between Groupsa

Test

HILT Group (nⴝ35)

US Therapy Group (nⴝ35)

Mean Difference in Change Scores (95% CI)

Actual P Value

BonferroniCorrected P Valueb

6.28 (1.8)

6.6 (1.53)

0.29 (⫺1.10 to 0.52)

.48

NS

⫺1.97 (⫺2.64 to ⫺1.30)

⬍.001

⬍.01

VAS score Baseline After intervention

2.42 (1.42)

4.44 (1.37)

Mean difference in change scores (95% CI)

3.86 (3.33 to 4.39)

2.17 (1.92 to 2.43)

Actual P value

⬍.001

⬍.001

Bonferroni-corrected P valueb

⬍.01

⬍.01

CMS score Baseline

63.22 (8.68)

63.08 (7.05)

0.14 (⫺3.63 to 3.92)

.94

NS

After intervention

75.91 (7.02)

72.11 (6.95)

0.14 (⫺3.63 to 3.92)

.03

NS

Mean difference in change scores (95% CI)

⫺12.69 (⫺13.94 to ⫺11.43)

⫺9.03 (⫺9.96 to ⫺8.10)

Actual P value

⬍.001

⬍.001

Bonferroni-corrected P valueb

⬍.01

⬍.01

Baseline

7.22 (2.28)

6.91 (2.24)

0.31 (⫺0.77 to 1.39)

.56

NS

After intervention

9.68 (1.99)

8.74 (2.04)

0.94 (⫺0.02 to 1.91)

.06

NS

Mean difference in change scores (95% CI)

⫺2.46 (⫺2.86 to ⫺2.06)

SST score

⫺1.83 (⫺2.04 to ⫺1.62)

Actual P value

⬍.001

⬍.001

Bonferroni-corrected P valueb

⬍.01

⬍.01

a Values are means (SDs) unless otherwise indicated. CI⫽confidence interval, VAS⫽visual analog scale, NS⫽not significant, CMS⫽Constant-Murley Scale, SST⫽Simple Shoulder Test. b The statistical inferences were adjusted according to Bonferroni inequality within groups.

statistically significant differences for VAS, CMS, and SST scores (Tab. 3).

Discussion In the present study, we compared the results obtained after 10 treatment sessions over a period of 2 consecutive weeks with 2 different physical therapy modalities in subjects diagnosed with Neer stage I or II SAIS. The subjects treated with HILT showed a greater reduction in pain and more improvement in articular movement, functionality, and muscle strength of the affected shoulder than the subjects treated July 2009

with US therapy (as measured with the VAS, CMS, and SST). Significant differences in changes after 10 treatment sessions over a period of 2 consecutive weeks from the baseline by treatment group were observed. In particular, the difference in the change in the VAS scores between the groups (1.65 points) surpassed the accepted MCID for this tool.47 Contrasting findings have been reported for US therapy and laser therapy in the treatment of SAIS and other shoulder disorders.11–21 There is little evidence that active thera-

peutic US is more effective than placebo US for treating people with soft-tissue disorders of the shoulder, including SAIS.17,20,21 Several authors20,52,53 have reported no differences between true US and sham US for subjects with soft-tissue disorders of the shoulder. Conversely, studies by other researchers have supported the efficacy of US therapy in reducing pain, improving activities of daily living, and improving quality of life.26,27 In particular, Ebenbichler and colleagues27 reported that 24 daily applications of US therapy at 2.5 W/cm2 (5 times per week for 3

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High-Intensity Laser Therapy Versus Ultrasound Therapy for Subacromial Impingement Syndrome Table 3. Change in Test Performance Over Time From Baseline for Participants With Subacromial Impingement Syndrome in HighIntensity Laser Therapy (HILT) and Ultrasound (US) Therapy Groups: Evaluation Between Groupsa

Variable

Both Groups (Nⴝ70)

HILT Group (nⴝ35)

US Therapy Group (nⴝ35)

Difference in Means (95% CI)

Actual P Value

Bonferroni-Corrected P Valueb

⫺3.01 (1.46)

⫺3.86 (1.53)

⫺2.17 (0.75)

⫺1.69 (⫺2.27 to ⫺1.12)

⬍.001

⬍.01

⫺48.89

⫺61.36

⫺33.04

10.86 (3.68)

12.69 (3.64)

9.03 (2.70)

3.66 (2.13 to 5.19)

⬍.001

⬍.01

17.19

20.06

14.31

2.14 (0.98)

2.46 (1.17)

1.83 (0.61)

0.63 (0.18 to 1.08)

.006

⬍.05

30.30

33.99

26.45

VAS score X (SD) % CMS score X (SD) % SST score X (SD) % a

CI⫽confidence interval, VAS⫽visual analog scale, CMS⫽Constant-Murley Scale, SST⫽Simple Shoulder Test. b The statistical inferences were adjusted according to Bonferroni inequality (0.05/6⫽0.008 and 0.01/6⫽0.002).

weeks and then 3 times per week for 3 weeks) reduced the painful symptoms in patients with calcific tendinitis of the supraspinatus tendon; in addition, the calcium deposits resolved in 19% of patients in the US therapy group and decreased by at least 50% in 28% of the patients. The variability of shoulder disorders and variations in the treatment intensity, duration, frequency, and location of US applications in previous studies could explain, in part, these contrasting findings.20,26,27,52,53 Some authors20,31,32,34 have suggested that LILT used without other physical therapy modalities could be helpful in the management of SAIS. For a small group of patients with tendinitis of the supraspinatus tendon, the data revealed that the patients treated with LILT had less pain, less secondary weakness, and less tenderness after the treatment than before.32 However, in another study of patients with shoulder tendonitis, LILT had only a short-term benefit for pain, self-reported function, active ROM, stiffness, and restriction after 2 weeks of treatment when compared with a placebo laser.34 Furthermore, conflicting results were demonstrated by Vecchio 650

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and colleagues35 in a comparison of patients who had SAIS and were treated with LILT and ROM exercises and patients who were treated with a placebo laser and ROM exercises; at 4- and 8-week follow-up sessions, there was no difference between groups with regard to pain, ROM, function, or strength. A recent metaanalysis suggested analgesic and tissue repair actions of LILT,33 whereas another study reported that 10 applications of LILT for 2 weeks did not induce significant pain relief and improvements in articular function relative to the findings for a group control given a placebo.54 Therefore, although the current evidence is conflicting, it appears that LILT was more beneficial than a placebo when applied as a single intervention for participants with SAIS. Our findings with HILT may lead to promising new therapeutic options. In the present study, the results obtained after 10 treatment sessions with the experimental protocol suggested greater effectiveness of HILT than of US therapy in the treatment of SAIS. The participants treated with HILT showed a greater reduction in pain and more improvement in articular movement, functionality,

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and muscle strength of the affected shoulder than the participants treated with US therapy. No studies have yet been conducted to compare the effectiveness of these different physical therapies, but no therapeutic differences among US therapy, LILT, and combined treatments were noted for tendon healing in rats.55 High-intensity laser therapy quickly reduces inflammation and painful symptoms.56 It utilizes a particular waveform with regular peaks of elevated values of amplitude and distances (in time) between them to decrease thermal accumulation phenomena, and it is able to rapidly induce in the deep tissue photochemical and photothermic effects that increase blood flow, vascular permeability, and cell metabolism.57 The HILT had an analgesic effect on nerve endings, but there was no evidence of a diminution of inflammation.58,59 Limitations of the present study include the lack of a control group receiving no treatment; this limitation constrains our ability to claim cause and effect. Participants in both groups may have improved simply because of the passage of time and July 2009

High-Intensity Laser Therapy Versus Ultrasound Therapy for Subacromial Impingement Syndrome the avoidance of strenuous activity for the treatment period. We have compared a new treatment option (HILT) with an accepted physical therapy modality, US therapy. As discussed above, some studies have shown US therapy to be effective in improving symptoms26,27 and have proposed this treatment as an acceptable physical therapy modality for SAIS.16 Additionally, the fact that the participants in one group were treated by a physical therapist and the participants in another group were treated by a physiatrist is a limitation of the present study because the participants were randomly assigned to physiatrist-HILT or physical therapist-US therapy groups. Another limitation is the lack of follow-up data, which reduces the clinical application of our findings on the short-term effects of HILT and US therapy in SAIS. Furthermore, our protocol of 10 treatment sessions over a period of 2 weeks could be challenging to apply in clinical practice. Finally, notwithstanding the good psychometric properties of the 3 measurement tools used in the present study, we only have MCID data on the VAS, limiting our ability to attribute a clinical significance to the differences between groups observed with the CMS and the SST. However, the difference in the change in the VAS scores between the groups (1.65 points) surpassed the MCID for this tool.45 On the other hand, the 95% CI of the SEM for the CMS was ⫾17.7 points,46 and the between-group difference did not surpass the SEM (3.8 points). Moreover, although the reliability of the SST has been reported to be good,60 a recent psychometric evaluation of the CMS suggested that its use is acceptable when pretreatment and posttreatment scores are determined by the same tester,54 as in the present study.

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Conclusion Although further studies are needed to confirm the effectiveness of physical therapy interventions for SAIS, HILT was shown to have greater benefit for SAIS than US therapy in reducing pain and improving the articular movement, functionality, and muscle strength of the affected shoulder. The results of the present study are encouraging, but other studies with larger samples, longerterm findings, and possible comparisons with other conservative interventions or placebo control groups are needed. Dr Santamato provided concept/idea/research design. Dr Santamato and Dr Panza provided writing. Dr Solfrizzi provided data collection. Dr Solfrizzi and Dr Panza provided data analysis. Dr Tondi and Dr Frisardi provided participants. Dr Leggin and Dr Fiore provided institutional liaisons. Dr Leggin and Dr Ranieri provided consultation (including review of manuscript before submission). The authors thank Dr Sheila Abrusci for her help in editing the manuscript. The study protocol received approval from the Institutional Review Board of the University of Bari. This work was supported by the Italian Longitudinal Study on Aging (ILSA) (Italian National Research Council-CNR-Targeted Project on Aging grants 9400419PF40 and 95973PF40). The funding agencies had no role in the design, conduct, or reporting of the study. This article was received May 10, 2008, and was accepted Aapril 6, 2009. DOI: 10.2522/ptj.20080139

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50 Beaton DE, Richards RR. Assessing the reliability and responsiveness of 5 shoulder questionnaires. J Shoulder Elbow Surg. 1998;7:565–572. 51 Roddey TS, Olson SL, Cook KF, et al. Comparison of the University of California-Los Angeles Shoulder Scale and the Simple Shoulder Test with the shoulder pain and disability index: single-administration reliability and validity. Phys Ther. 2000;80: 759 –768. 52 Nykanen M. Pulsed ultrasound treatment of the painful shoulder: a randomized, double-blind, placebo-controlled study. Scand J Rehabil Med. 1995;27:105–108. 53 Kurtais¸ Gu ¨ rsel Y, Ulus Y, Bilgiç A, et al. Adding ultrasound in the management of soft-tissue disorders of the shoulder: a randomized placebo-controlled trial. Phys Ther. 2004;84:336 –343. 54 Bingol U, Altan L, Yurtkuran M. Lowpower laser treatment for shoulder pain. Photomed Laser Surg. 2005;23:459 – 464. 55 Demir H, Menku P, Kirnap M, et al. Comparison of the effects of laser, ultrasound, and combined laser ⫹ ultrasound treatments in experimental tendon healing. Lasers Surg Med. 2004;35:84 – 89. 56 Zati A, Degli Esposti S, Bilotta TW. Il laser CO2: effetti analgesici e psicologici in uno studio controllato. Laser & Technology. 1997;7:723–730. 57 Kujawa J, Zavodnik L, Zavodnik I, et al. Effect of low-intensity (3.75–25 J/cm2) near-infrared (810 nm) laser radiation on red blood cell ATPase activities and membrane structure. J Clin Laser Med Surg. 2004;22:111–117. 58 Tsukya K, Kawatani M, Takeshige C, et al. Laser irradiation abates neuronal responses to nociceptive stimulation of ratpaw skin. Brain Res Bull. 1994;34: 369 –374. 59 Nicolau RA, Martinez MS, Rigau J, Toma`s J. Neurotransmitter release changes induced by low power 830 nm diode laser irradiation on the neuromuscular junctions of the mouse. Lasers Surg Med. 2004;35:236 –241. 60 Rocourt MH, Radlinger L, Kalberer F, et al. Evaluation of intratester and intertester reliability of the Constant-Murley shoulder assessment. J Shoulder Elbow Surg. 2008; 17:364 –369.

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Research Report

Measurement of Paretic–LowerExtremity Loading and Weight Transfer After Stroke Vicki Stemmons Mercer, Janet Kues Freburger, Shuo-Hsiu Chang, Jama L. Purser

Background. Weight bearing through, or “loading” of, the paretic lower extremity and transfer of weight from one lower extremity to the other are important impairment-level goals of stroke rehabilitation. Improvements in these limb-loading and weight-transfer abilities have been shown to relate to improved performance of many functional activities. Unfortunately, valid and practical clinical measures of paretic–lower-extremity loading and weight transfer have not been identified. Objective. The purpose of this study was to assess convergent validity of the Step Test (ST) and the knee extension component of the Upright Motor Control Test (UMCe) as measures of paretic-limb loading and of the Repetitive Reach Test (RR) as a measure of weight transfer in the first 6 months after stroke.

Design. This was a prospective cohort study of 33 adults with lower-extremity motor impairment following unilateral, noncerebellar stroke. Participants were tested one time per month from 1 to 6 months poststroke.

Results. Scores on the ST (performed with the nonparetic leg as the stepping leg) and UMCe were positively correlated with peak vertical ground reaction forces (GRFs) beneath the paretic limb during functional tasks (R2⫽.35–.76 for the ST, pseudo R2⫽.21–.34 for the UMCe). Scores on the RR were positively correlated with change in vertical GRF beneath the paretic limb during the diagonal reach task (R2⫽.45) and with weight-transfer time during stepping with the nonparetic limb (R2⫽.15).

Conclusions. The ST, performed with the nonparetic leg as the stepping leg, is a valid measure of paretic-limb loading during stroke recovery. Of the clinical measures tested, the ST correlated most strongly with the force platform measures.

V.S. Mercer, PT, PhD, is Associate Professor, Division of Physical Therapy, Department of Allied Health Sciences, University of North Carolina at Chapel Hill, CB 7135, Bondurant Hall, Ste 3022, Chapel Hill, NC 27599-7135 (USA). Address all correspondence to Dr Mercer at: vmercer@med. unc.edu. J.K. Freburger, PT, PhD, is Research Associate and Fellow, Cecil G. Sheps Center for Health Services Research, and Research Scientist, Institute on Aging, University of North Carolina at Chapel Hill. S-H. Chang, PT, PhD, is Postdoctoral Research Scholar, Graduate Program in Physical Therapy and Rehabilitation Science, The University of Iowa, Iowa City, Iowa. J.L. Purser, PT, PhD, is Assistant Professor, Division of Geriatrics, Department of Medicine, and Division of Physical Therapy, Department of Community and Family Medicine, and Senior Fellow, Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, North Carolina. [Mercer VS, Freburger JK, Chang S-H, Purser JL. Measurement of paretic–lower-extremity loading and weight transfer after stroke. Phys Ther. 2009;89:653– 664.] © 2009 American Physical Therapy Association

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke troke is a leading cause of longterm disability in the United States. The estimated number of people who have survived a stroke stands at 5,500,0001 and is expected to continue to grow.2 Approximately 50% of people who survive a stroke have chronic motor deficits,3 the most common of which is hemiparesis. Individuals with hemiparesis following a stroke often have difficulty bearing weight on or “loading” the paretic lower extremity and transferring weight from one leg to the other.4 – 6 As a result, these individuals commonly exhibit asymmetry during sitting and standing activities and during walking, with a greater proportion of body weight distributed on the nonparetic lower extremity than on the paretic lower extremity.4 – 8

S

symmetry during the sit-to-stand (STS) task is associated with faster STS performance under both selfpaced and fast-paced conditions.10 Lee et al20 reported that the maximum weight-bearing difference between the 2 lower extremities during the STS task was highest for the subjects with stroke who had the lowest scores on the Functional Independence Measure.21 Kim and Eng19 found that the greater the asymmetry of various temporaldistance and force platform measures of gait, the lower the gait speed in subjects with chronic stroke. The relationship was strongest for asymmetry of vertical ground reaction forces (GRFs), indicating that reduced dynamic loading of the paretic leg significantly affects gait performance.

A few researchers have focused specifically on the ability to transfer weight from one leg to the other after stroke.4,8,14,15,23 The functional importance of this ability, however, is not as well-established as that of paretic–lower-extremity loading. Both spatial and temporal features of weight transfer have been examined using force platform and kinematic data. Weight-transfer ability, as indicated by movement of the center of pressure or center of mass during voluntary weight shifts in a standing position, has been reported to relate to various measures of standing balance14 and gait performance.4 Pai and colleagues,15 however, found only a weak correlation (rho⫽.40) between successful weight transfer during a single-leg flexion task in a standing position and gait speed.

Several researchers have provided evidence that impaired lowerextremity loading9 –13 and, to a lesser extent, weight-transfer8,14,15 abilities after stroke are associated with functional deficits. In most of these studies, the ability to load the paretic leg or to load both legs symmetrically was measured using force platforms or digital scales to record forces under the feet. Loading on the paretic lower extremity has been shown to relate to performance of functional tasks such as reaching in sitting,9,16 rising from a chair,10,11 standing,17,18 walking,12,19 and climbing curbs and stairs.11,13 Greater weight-bearing

Research also suggests that interventions designed to improve paretic– lower-extremity loading improve functional performance in individuals with stroke. Dean and Shepherd9 demonstrated that practice of seated reaching tasks over a 2-week period increased paretic–lower-extremity loading and improved task performance in subjects with stroke. After training, subjects in the experimental group showed increased paretic– lower-extremity loading when reaching forward and toward the paretic side and were able to reach faster and farther than subjects in the control group. Experimental group subjects, but not control group subjects, also exhibited a significant increase after intervention in paretic–lowerextremity loading during the STS task. In a study by Cheng et al,22 patients with stroke who received symmetrical standing training and repetitive STS training in addition to usual care showed more-symmetrical body-weight distribution during STS training and fewer falls over the 6-month follow-up period than patients who received only usual care.

Paretic–lower-extremity loading and weight-transfer abilities are a major focus of rehabilitation training for patients with hemiparesis.24 –27 Unfortunately, most previous studies of these abilities have relied heavily on laboratory measurements, such as GRFs and medial-lateral impulses calculated from force platform data. Force platforms are expensive and require extra time and a high level of technical support for data collection and reduction.28 Valid and practical clinical measures of paretic– lower-extremity loading and weight transfer have not been identified. In many settings, the only practical way to measure weight bearing is with digital scales.7,13 Because these scales cannot record dynamic load changes, they are useful only for measuring weight-bearing performance during certain tasks, such as static standing and prolonged voluntary weight shifting. Even with selection of relatively static tasks, important components of performance may be missed with use of such systems. The lack of clinically accessible measures makes it difficult for clinicians to make sound decisions

Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on May 21, 2009, at www.ptjournal.org.

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke about interventions directed toward improving symmetry and weight transfer and, ultimately, increasing function. The Step Test (ST)29 and the knee extension component of the Upright Motor Control Test (UMCe)30,31 are clinical tests that require single-limb stance on the paretic lower extremity and, therefore, have face validity as measures of paretic-limb loading. The Repetitive Reach Test (RR)28 is a clinical test that requires stability in bipedal stance during rapid, repetitive nonparetic– upper-extremity reaching movements across midline and forward beyond arm’s length. Because the individual must control movement of the body’s center of mass toward both the nonparetic and paretic sides during these dynamic reaches, we viewed the RR as a potential measure of weight-transfer abilities. The aims of this study were: (1) to determine whether the ST and the UMCe are valid measures of paretic– lower-extremity loading and (2) to determine whether the RR is a valid measure of weight transfer during the first 6 months of stroke recovery. The type of validity assessed in this study was convergent validity, which is a subtype of construct validity. Convergent validity reflects the ability of an instrument to measure an abstract concept, or construct.32 The basis for convergent validity is that 2 measures thought to reflect the same underlying construct (eg, a clinical measure and a laboratory measure of paretic–lowerextremity loading) should correlate highly.

were recruited from University of North Carolina Hospitals in Chapel Hill, North Carolina, and WakeMed Rehab, a rehabilitation hospital in Raleigh, North Carolina. Inclusion criteria were: (1) a primary diagnosis of unilateral noncerebellar stroke; (2) medically stable and free of major cardiovascular conditions (eg, recent myocardial infarction, unstable angina, ventricular tachycardia) and musculoskeletal problems (eg, fracture, sprain, strain); (3) able to follow 3-step commands; (4) able to reach in all directions to touch a target with the nonparetic hand while sitting without support; (5) lower-extremity motor impairment, as indicated by a score of ⱕ28 on the lower-extremity motor scale of the Fugl-Meyer Assessment33; (6) adequate vision and hearing for completing the study protocol, as indicated by the ability to see targets for reaches and to follow oral instructions during screening; and (7) residence within an 80-km (50-mile) radius, with willingness to return to our laboratory for testing at monthly intervals from 1 to 6 months poststroke.

Method

Potential participants were excluded from the study if they: (1) had a history of previous strokes or other neurologic diseases or disorders, such as Parkinson disease or Alzheimer disease; (2) were unable to live or ambulate independently in the community prior to the stroke; (3) had a terminal illness; or (4) had pain, limited motion, or weakness in the nonparetic lower extremity that affected performance of daily activities (by self-report). Informed consent was obtained from all participants prior to testing.

Participants Adults (over the age of 21 years) with stroke were recruited as part of a broader longitudinal study of paretic–lower-extremity loading during stroke recovery. Participants

Procedure Participants were recruited and baseline testing was completed during the time period from hospital admission to 1 month poststroke. At

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baseline, we examined paretic-limb motor function using the lowerextremity motor scale of the FuglMeyer Assessment33 and collected quantitative data on visuospatial neglect. Tests for neglect, including the letter and star cancellation subtests of the Behavioral Inattention Test (BIT),34,35 were included in the study primarily because of the strong association between spatial neglect and postural disorders such as asymmetrical weight bearing in standing.36 Testing at the Center for Human Movement Science at the University of North Carolina at Chapel Hill began at 1 month poststroke and continued at monthly intervals through 6 months poststroke. Participants were weighed at the beginning of each test session. Measurements of height and right foot length were recorded at the first (1-month) test session only and were used to determine standardized positions for force platform testing. The clinical and force platform tests described below were administered by the same examiner at each session. Clinical tests. The ST, UMCe, and RR were selected because of their face validity and because they: (1) simulate functional movements that challenge dynamic stability in standing, (2) were developed for and tested with people with stroke, (3) have evidence of reliability, and (4) can be easily administered in a variety of clinical settings. The ST assesses an individual’s ability to place one foot onto a 7.5-cm-high step and then back down to the floor repeatedly as fast as possible for 15 seconds.29 The step is placed 5 cm in front of the individual’s feet. The test is scored by recording the number of steps completed in the 15-second period for each leg. Participants wore any customary orthoses but were not permitted to use an assistive device during testing. They performed the

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke test first with the nonparetic foot and then with the paretic foot placed on and off the step. Because we were interested in loading of the paretic leg, only ST scores for stepping with the nonparetic leg were analyzed. The ST has high test-retest reliability in people poststroke (intraclass correlation coefficient [3,1]⫽ .94 for performance with the nonparetic leg as the stepping leg)29 and is responsive to change during stroke rehabilitation, with standardized response means (SRMs)37,38 of 0.92 and 0.95 for the nonparetic and paretic legs, respectively.37,39 In a sample of older adults who were healthy and individuals undergoing inpatient rehabilitation after stroke, ST scores for stepping with the nonparetic leg were significantly correlated with scores on the Functional Reach Test,40 gait speed, and stride length, with Pearson correlation coefficients (r) of .73, .83, and .83, respectively.29 The UMCe assesses strength (forcegenerating capacity) and control of the knee extensor muscles during single-limb stance on the paretic side.31 In standing, the participants flexed both knees to approximately 30 degrees and then lifted the nonparetic foot off the ground. They then attempted to extend the knee on the paretic side while still holding the nonparetic foot off the ground. Knee extension was graded on a 3-point scale: 1⫽unable to bear full weight on a flexed knee, 2⫽able to support full weight on the flexed knee but unable to extend further, and 3⫽able to complete full range of knee extension. This test has evidence for intertester reliability and predictive validity.31 Knee extension and flexion scores on the UMCe have been shown to predict home versus community walking ability prior to hospital discharge, with a score of 3 on either component predicting community ambulation.31

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Repetitive reach assesses how rapidly an individual is able to reach back and forth between 2 targets with the nonparetic arm while maintaining bipedal stance.28 The number of reaches performed during a 30-second period is recorded.39 Participants reached with the nonparetic upper extremity from a target placed on the nonparetic side opposite the greater trochanter to a target placed 15 cm beyond arm’s length in front of their paretic hip (at the same height as the side target). Participants maintained their feet in a step stance position with the paretic foot forward while reaching. Intrasession and intersession reliability coefficients (Pearson product moment correlation coefficients) for RR ranged from .90 to .99 in patients tested at a mean time interval of 2 months after stroke.28 Intersession reliability was slightly higher for testing in step stance (r⫽.94) compared with parallel stance (r⫽.90) positions. Like the ST, the RR has been shown to be responsive to changes occurring during stroke rehabilitation (SRMs of 0.75 and 0.86 when performed in parallel stance and step stance, respectively).39 Force platform tests. Two Bertec (N60501, Type 4060A, 40- ⫻ 60-cm) force platforms* mounted side-byside in the floor were used to measure GRFs during performance of 4 functional tasks: diagonal reach in standing, STS transfer, stepping up onto a step with the nonparetic leg leading, and stepping up onto a step with the paretic leg leading. Foot tracings were used to facilitate consistency of foot position during testing for each participant. The participant’s feet were positioned so that one foot was on each force platform and the distance between the midpoints of the heels was equal to right foot length.23 This positioning * Bertec Corp, 6717 Huntley Rd, Columbus, OH 43229.

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served to standardize the length and width of the base of support with respect to each participant’s foot length. Participants performed 2 practice trials and 4 test trials of each task, as described below. Peak Motus software† on a personal computer was used to acquire force platform data online at a sampling rate of 500 Hz. For diagonal reach in standing, participants used their nonparetic upper extremity to pick up an unopened 355-mL (12-fl oz) soft drink can from a starting point on the nonparetic side (15 cm directly lateral to the greater trochanter) and set it down on a target located 1.4 armlengths away on the paretic side at a 45-degree angle from midline.9 They were instructed to move as fast as they could without feeling unsafe or dropping or knocking over the can. Pressure switches at the start location and at the target were used to detect the beginning and end of the reach, respectively. The switch at the start location was “on” at the beginning of the trial and was released when a participant lifted the can. The switch at the end location was overlaid by a 12- ⫻ 12-cm sheet of hard plastic that served as the target. This switch closed when the can contacted the plastic sheet, signaling the end of the reaching movement. For the STS transfer, participants started in a sitting position in a standard wooden chair without armrests (seat height⫽44.4 cm) with feet positioned in the tracings and the chair just behind the force platforms. Participants were instructed to come to a standing position as fast as they could without feeling unsafe. They were not allowed to use an assistive device and were asked to try not to use either upper extremity to push up from the chair. Because the legs † Peak Performance Technologies, 7388 S Revere Pkwy, Ste 603, Englewood, CO 80112.

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke of the chair were not in contact with the force platforms, a participant’s use of upper-extremity support on the chair resulted in a proportional decrease in the forces recorded beneath the feet. For the stepping tasks, participants started in a standing position with their feet in the tracings and stepped up onto an 8-cm-high step with both feet. The step, which did not contact the force platform, was positioned with the front edge 1.5 foot-lengths from the back of each participant’s heels. Participants were instructed to step as fast as they could without feeling unsafe. The stepping task was performed first with the nonparetic lower extremity leading (4 test trials) and then with the paretic lower extremity leading (4 test trials). Data Reduction Force platform data were exported from Motus to customized software programs (MotionSoft 3D version 6.5 and MotionSoft Discrete Data Reader version 6.0)‡ for processing and reduction. The GRF signals were calibrated and converted to newtons. The force platform measures used in the analyses are described below. For each force platform measure, the mean of the 4 test trials was used. All GRF measurements were normalized by the participant’s body weight recorded at each test session. The peak vertical GRF through the paretic lower extremity was determined for each of the following tasks: diagonal reach, STS transfer, and stepping up onto a step with the nonparetic limb leading. These were the 3 biomechanical measures of paretic-limb loading. The biomechanical measures of weight transfer were: (1) change in vertical GRF, (2) weight-transfer ‡ Bing Yu, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7135.

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Figure 1. Force platform data for a representative trial of the diagonal reach task. The vertical ground reaction force (GRF) beneath the paretic limb decreased as the participant picked up a can from the nonparetic side at the start of the reach, then increased as the participant reached across midline to place the can on the target.

time, and (3) medial-lateral impulse. Change in vertical GRF was determined for the diagonal reach task only and was measured as the difference between the maximum and minimum values of the vertical GRF beneath the paretic limb during the reach (Fig. 1). The time period of the reach was indicated by the pressure switch signals. Weight-transfer time41 was determined for stepping up with the nonparetic limb leading (Fig. 2) and for stepping up with the paretic limb leading. This measure of weight transfer was defined as the duration from the first change in vertical GRF data (change for either limb of more than 2% of body weight from the mean baseline measurement during quiet standing) to when the force beneath the leading limb reached zero, indicating that the limb had lost contact with the force platform. Medial-lateral impulse42 also was determined for the 2 stepping tasks (stepping up with the nonparetic limb leading and stepping up with the paretic limb leading) and was calculated as the inte-

gral of the medial-lateral GRF beneath the paretic limb during the weight-transfer time. Clinical test scores and force platform data on participants who were not able to perform a task safely without physical assistance from another person were retained and assigned a value of 0. Data were treated as missing if the participant was too fatigued to perform a given task. Data Analysis All analyses were conducted using Stata version 9.2.§ Descriptive statistics were generated for the baseline characteristics of the sample and for the clinical and biomechanical measurements of paretic-limb loading and weight transfer collected at each session. The clinical and biomechanical data for each session and for the sessions combined also were plotted to examine visually the relationships between the measures. Bi§

StataCorp LP, 4905 Lakeway Dr, College Station, TX 77845.

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke dent variable in an ordinal logistic regression analysis, however, is categorical and ordered (eg, UMCe score) rather than continuous.

Figure 2. Force platform data for a representative trial of the stepping task performed with the nonparetic leg leading. The participant stepped from the force platform up onto the step with both feet. The medial-lateral (M-L) impulse generated by the paretic limb is indicated by the cross-hatched area. Note that the M-L forces are exerted in the same direction (from the flexing toward the stance limb) under both legs during the weighttransfer time. Peak vertical ground reaction force (GRF) beneath the paretic limb, which was one of our measures of paretic-limb loading, also is indicated.

variate linear regression analyses were conducted to determine the relationship between the ST scores (nonparetic limb) and each of the paretic–limb-loading measures (ie, peak vertical GRF through the paretic lower extremity for the diagonal reach and STS tasks and stepping with the nonparetic lower extremity leading) and between the RR scores and each of the weight-transfer measures (ie, change in vertical GRF, weight-transfer times during the stepping tasks, and medial-lateral impulse produced by the paretic limb during the stepping tasks). Because lower scores on weight-transfer times indicated less impairment, weight-transfer times of 0 (indicating individuals who could not attempt the test without assistance) were eliminated from the regression analyses. A bivariate linear regression analysis describes the nature (eg, as ST scores increase, limb-loading measurements increase) and strength (eg, the degree of correlation between ST scores and limb-loading 658

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measurements) of a linear relationship between a continuous dependent variable and a continuous or discrete independent variable. Linear regression analysis is one analytic approach for establishing convergent validity. The R2 value generated from a linear regression analysis specifically describes the strength of the relationship between the dependent and independent variable. For example, an R2 value of .30 indicates that 30% of the variation in the dependent variable is explained by variation in the independent variable. Ordinal logistic regression analyses were conducted to examine the relationship between UMCe and peak vertical GRF through the paretic lower extremity for the diagonal reach and STS tasks and stepping with the nonparetic lower extremity leading. An ordinal logistic regression analysis is like a linear regression analysis in that it assesses the nature and strength of the relationship between variables. The depen-

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Based on preliminary regression analyses conducted on data from each session, we determined that the strength of the relationships between the clinical and laboratory measurements (ie, R2 values) did not follow any consistent patterns (eg, increasing, decreasing) over time. Consequently, we combined the data from all sessions to increase the size of the data set and to account for the non-independence of measures in our analyses.43 Data on the same individuals over time are not independent of one another. If this non-independence is unaccounted for in regression analyses, the standard errors of the parameter estimates (eg, the measure of slope in linear regression) may be underestimated, thereby increasing the likelihood of statistically significant findings. To address this issue, we estimated the standard errors using the Huber/White/sandwich estimator of variance.44 This estimator gives accurate assessments of the sample-to-sample variability of the parameter estimates even when the statistical model is not correctly specified. For the linear regression analyses, statistical tests45 were conducted to verify that a linear model was appropriate (eg, that the relationship between the variables was linear and not exponential). Based on these tests and plots of the data, the independent variables for the linear regression analyses were transformed, if necessary. Transformation of the independent variable is one approach to take when conducting a linear regression analysis if the relationship between the dependent and independent variables is not linear. For example, one way to linearize a curvilinear relationship between a July 2009

Paretic–Lower-Extremity Loading and Weight Transfer After Stroke dependent variable and an independent variable is to square the independent variable.

Table 1. Baseline Participant Characteristics (N⫽33) Mean (SD) [range] or N (%)

Variable

For the ordinal logistic regression analyses, statistical tests were conducted to verify that the analysis was appropriate for the data and to assess the strength of the relationship between the dependent variable (UMCe) and the independent variable (force platform measure).43,46 Although the ordinal logistic regression analysis does not have an exact analog to the R2 generated in a linear regression analysis, various tests and pseudo R2 values are recommended to describe the strength of the relationship between the dependent and independent variables. We used the McFadden’s pseudo R2 and the Bayesian Information Criterion (BIC) to assess model fit.46 We interpret these statistics in the “Results” section.

Age (y)

58.73 (17.27) [24–97]

Sex Female

15 (45)

Male

18 (55)

Race/ethnicity White

18 (55)

African-American

14 (42)

Hispanic

1 (3)

Paretic side Right

10 (30)

Left

23 (70)

Baseline Fugl-Meyer test score

17.82 (6.22) [7–28]

Behavioral Inattention Test

a

● Star Cancellation Scorea (maximum score⫽54, cutoff⫽51), number of participants scoring below cutoff⫽13

47.78 (9.73) [10–54]

● Letter Cancellation Scorea (maximum score⫽40, cutoff⫽32), number of participants scoring below cutoff⫽9

32.56 (8.85) [6–40]

Scores below cutoff indicate the presence of unilateral visuospatial neglect.

Results Baseline characteristics of the 33 individuals who enrolled in the study are presented in Table 1. Twenty-five participants completed all 6 testing sessions. Three participants dropped out after the third testing session, 4 participants missed 1 testing session, and 1 participant missed 2 testing sessions. Completers (n⫽25) were similar to non-completers in regard to all baseline characteristics (P⬍ .05) except sex, with a greater proportion of female participants not completing all 6 sessions. Completers and non-completers also were similar in regard to initial measurements of impairment, function, and disability. Descriptive data on the clinical and biomechanical measures of limb loading and weight transfer are presented in Tables 2 and 3. Nine participants received the lowest possible score on the ST (score of 0) and the UMCe (score of 1) at all time points. Six participants received the July 2009

lowest possible score on the RR (score of 0) at all time points. Some of these same individuals also were unable to perform one or more of the 4 functional tasks from which the biomechanical measurements were determined. The numbers of participants with scores of 0 for the biomechanical measures through the 6-month time point were 2 for the diagonal reach and STS tasks and 8 for each of the 2 stepping tasks. Tables 2 and 3 indicate that individuals generally improved over time on the clinical and biomechanical measures and that the 2 types of measures tended to trend in a similar manner. The results of the linear regression of nonparetic-limb ST scores on paretic– limb-loading measures are presented in Table 4. The peak vertical GRF variables for 2 of the tasks were transformed because of nonlinear relationships with ST scores (peak vertical GRF during the diagonal reach task was squared and peak vertical

GRF during stepping with the nonparetic limb leading was cubed). The beta coefficients were all positive and significantly larger than 0, as indicated by their values and by the fact that the 95% confidence intervals were far from 0. These findings indicate that as ST score increased, so did paretic–limb-loading measurements. Although ST scores were significantly related to paretic-limb loading during all 3 tasks, the relationship with peak vertical GRF during stepping with the nonparetic limb leading was strongest (R2⫽.76). That is, 76% of the variation in ST scores was explained by variation in peak vertical GRF scores. Less than 50% of the variation in ST scores was explained by peak vertical GRF during the diagonal reach and STS tasks. The results of the ordinal logistic regression analyses of UMCe scores on paretic–limb-loading measures are presented in Table 5. The coefficients were all positive and signifi-

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke Table 2. Descriptive Statistics (Mean⫾SD or Frequency) for Clinical and Biomechanical Tests of Paretic-Limb Loadinga Session Variable

1

2

3

4

5

6

3.5⫾4.0 (N⫽33)

5.8⫾4.6 (n⫽31)

5.8⫾4.8 (n⫽31)

6.3⫾5.1 (n⫽30)

6.9⫾5.4 (n⫽29)

7.5⫾5.0 (n⫽29)

Grade 1

24 (73%)

16 (52%)

14 (45%)

11 (37%)

10 (33%)

9 (31%)

Grade 2

4 (12%)

9 (29%)

8 (26%)

9 (30%)

7 (24%)

4 (14%)

Grade 3

4 (12%) (n⫽32)

6 (19%) (n⫽31)

9 (29%) (n⫽31)

10 (33%) (n⫽30)

12 (41%) (n⫽29)

16 (55%) (n⫽29)

Peak vertical GRF during diagonal reach task (%BW)

53.41⫾38.29 (n⫽31)

61.6⫾35.5 (n⫽31)

66.79⫾31.10 (n⫽31)

72.98⫾26.07 (n⫽30)

74.17⫾22.80 (n⫽29)

74.06⫾23.64 (n⫽28)

Peak vertical GRF during sit-to-stand task (%BW)

35.75⫾22.42 (n⫽31)

40.46⫾21.56 (n⫽31)

41.47⫾20.51 (n⫽31)

42.85⫾21.05 (n⫽30)

49.76⫾13.73 (n⫽29)

47.71⫾15.91 (n⫽28)

Peak vertical GRF during stepping with nonparetic limb leading (%BW)

47.37⫾53.12 (n⫽31)

68.20⫾51.60 (n⫽31)

72.67⫾51.38 (n⫽31)

74.49⫾49.98 (n⫽30)

77.13⫾48.71 (n⫽29)

81.11⫾46.81 (n⫽29)

Step Test, nonparetic limb (no. of steps) Upright Motor Control Test extension componentb

a Number of participants (n) included in the analysis at each session is indicated for each variable. GRF⫽ground reaction force, %BW⫽percentage of body weight. b Data for this variable are the number (%) of participants achieving each grade (1–3) for the knee extension component of the Upright Motor Control Test.

cantly greater than 0, indicating that as scores on the UMCe increased, measurements of paretic-limb loading increased. The confidence intervals around the coefficients, however, were wide, and the pseudo R2 values generally were low. Although these pseudo R2 values cannot be interpreted in a manner similar to the R2 in linear regression, higher scores generally mean a stronger re-

lationship. The BIC is another way of interpreting model fit and is most useful when comparing one model with another model. The lower the BIC, the better the fit. In bivariate models (such as those in this study), differences of 10 or more between 2 models provide strong evidence that the model with the lower BIC is the best-fitting model.47 Based on the pseudo R2 values and the BIC values,

scores on UMCe were most strongly related to peak vertical GRF during the task of stepping with the nonparetic limb. The wide confidence interval around the coefficient and the low pseudo R2 value, however, suggest that the relationship was not strong. With regard to relationships between RR scores and data for weight-

Table 3. Descriptive Statistics (Mean⫾SD or Frequency) for Clinical and Biomechanical Tests of Weight Transfera Session Variable

1

2

3

4

5

6

Repetitive Reach Test

11.00⫾9.71 (n⫽28)

14.19⫾9.66 (n⫽31)

16.03⫾10.81 (n⫽30)

17.45⫾10.07 (n⫽29)

18.79⫾11.63 (n⫽28)

18.57⫾9.85 (n⫽28)

Change in vertical GRF during diagonal reach task (%BW)

30.80⫾23.93 (n⫽31)

36.33⫾22.81 (n⫽31)

41.51⫾21.62 (n⫽31)

42.92⫾17.37 (n⫽30)

43.28⫾15.54 (n⫽29)

40.74⫾14.94 (n⫽28)

ML impulse of the paretic limb during stepping with paretic limb leading (%BW-s)

1.10⫾1.37 (N⫽33)

1.51⫾1.45 (n⫽31)

2.01⫾2.99 (n⫽31)

2.22⫾2.64 (n⫽30)

2.19⫾2.43 (n⫽29)

2.27⫾2.23 (n⫽29)

ML impulse of the paretic limb during stepping with nonparetic limb leading (%BW-s)

0.77⫾1.08 (N⫽33)

1.05⫾1.12 (n⫽31)

1.42⫾2.47 (n⫽31)

1.69⫾2.60 (n⫽30)

1.66⫾2.27 (n⫽29)

1.66⫾1.84 (n⫽29)

Weight-transfer time during stepping with paretic limb leading (s)

0.31 (0.37) (n⫽31)

0.44 (0.38) (n⫽31)

0.95 (2.66) (n⫽31)

0.78 (1.89) (n⫽30)

0.59 (0.91) (n⫽29)

0.66 (0.94) (n⫽29)

Weight-transfer time during stepping with the nonparetic limb (s)

0.32 (0.38) (n⫽31)

0.46 (0.40) (n⫽31)

0.75 (1.55) (n⫽31)

0.72 (1.31) (n⫽30)

0.69 (0.98) (n⫽29)

0.72 (1.12) (n⫽29)

a Number of participants (n) included in the analysis at each session is indicated for each variable. GRF⫽ground reaction force, %BW⫽percentage of body weight, %BW-s⫽percentage of body weight-seconds, ML⫽medial-lateral.

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke Table 4. Relationships Between Step Test Scoresa and Force Platform Measures of Paretic-Limb Loading Force Platform Measure

n

␤ Coefficient

95% Confidence Interval

R2

Peak vertical GRF during diagonal reach taskb

180

11.51

9.32–13.70

.42

Peak vertical GRF during sit-to-stand task

180

14.76

11.31–18.22

.35

Peak vertical GRF during stepping with the nonparetic limbc

181

7.11

6.20–8.01

.76

a

Step Test performed with the nonparetic leg as the stepping leg. b Transformed to peak vertical ground reaction force (GRF) squared. c Transformed to peak vertical GRF cubed.

transfer variables, no relationships were found for the medial-lateral impulses developed by the paretic limb during the stepping tasks. Weak negative associations were obtained for the weight-transfer variables (R2⫽ .09 and .15 for stepping with the paretic and nonparetic limbs, respectively), indicating that as weighttransfer times increased, RR scores decreased. The RR score had the strongest relationship with change in vertical GRF during the diagonal reach task (R2⫽.45). As weight shift onto the paretic limb increased during the diagonal reach task, RR scores also increased.

Discussion The main finding of this study was that the ST, performed with the nonparetic limb as the stepping limb, demonstrates convergent validity as a measure of paretic–lowerextremity loading in individuals recovering from stroke. Unlike laboratory measures of loading, this test can be performed easily and quickly in the clinical setting. The ST, therefore, provides clinicians with information not only about a patient’s bal-

ance abilities, as reported previously in the literature,29,39 but also about the patient’s ability to bear weight through the paretic leg. Peak vertical GRF beneath the paretic limb during various functional tasks accounted for 35% to 76% of the variance in ST scores, with peak vertical GRF during stepping (with the nonparetic limb leading) having the strongest relationship. This finding is not surprising, considering the similarities between the 2 tasks. The diagonal reach and STS tasks, however, do not require full weight bearing through the paretic limb. Relationships with peak vertical GRF during these tasks, although present, were not as strong. The ability to perform the ST appears to be reflective of the ability to load the paretic limb during tasks such as stepping up onto a single step or a curb, which have important functional implications in individuals recovering from stroke. Mean ST scores in our sample improved steadily from 1 to 6 months poststroke, with no evidence of reaching a plateau after 3 months poststroke. The ST may offer suffi-

cient challenge to make it a useful measure for monitoring progress beyond 6 months poststroke. However, 9 (27%) of our participants received the lowest possible score on this test at all time points. If meaningful change was actually occurring in these patients, then floor effects on the ST may have been present. Because the ST is performed in standing without upper-extremity support, some patients, especially those in the earliest stages of recovery, may have balance problems or other impairments that result in a score of 0 on this test. The other measure of paretic-limb loading investigated in this study (ie, UMCe) also was associated with peak vertical GRF beneath the paretic limb during functional tasks. The strongest association (pseudo R2⫽.34) was for the task of stepping up onto a step with the nonparetic limb leading, again supporting the idea that similar tasks may require similar abilities (eg, the ability to load the paretic limb). The correlations were much lower than for the ST, however, possibly because the

Table 5. Parameter Estimates, 95% Confidence Intervals, and Model Fit Statistics From Linear Regression of Upright Motor Control Testa on Force Platform Measures of Paretic-Limb Loading n

Coefficient

95% CI

Pseudo R2

BICb

179

9.75

4.56–14.94

.22

⫺78.64

Peak vertical GRF during sit-to-stand task

180

11.05

7.04–15.07

.21

⫺78.81

Peak vertical GRF during stepping with the nonparetic limb

181

5.90

2.78–9.02

.34

⫺128.98

Force Platform Measure Peak vertical GRF during diagonal reach task

a b

Knee extension component only. CI⫽confidence interval, BIC⫽Bayesian Information Criterion, GRF⫽ground reaction force. A lower, or more negative, BIC indicates better fit.

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke UMCe was less similar to the biomechanical test. Another explanation for the weaker correlations is that the UMCe is a less-sensitive measure than the ST. The UMCe uses a 3-level scoring system, whereas the ST is a continuous measure, with scores that ranged from 0 to 20 in our study. As with ST scores, UMCe scores generally improved from 1 to 6 months poststroke. Both floor and ceiling effects, however, were observed for UMCe. Nine participants (27%) received the lowest-possible score on the test for all 6 sessions, and 12 participants (36%) received the highest possible score on the test before the sixth session. Our expectation that RR scores would be correlated with force platform measures of weight transfer generally was not supported. An important consideration in interpreting this result is the lack of consensus in the literature about appropriate biomechanical measures of weight transfer. Unlike paretic-limb loading, for which peak or mean vertical GRF is widely accepted for biomechanical measurement, weight transfer has been measured in a number of different ways. We chose force platform measurements of the magnitude and temporal characteristics of the transfer of weight from one leg to the other leg. Evidence of the relationship between these characteristics and performance of functional activities is limited. The strongest relationship in our study between RR scores and force platform measures was the relationship with the change in vertical GRF beneath the paretic limb during the diagonal reach task. Although diagonal reach was the functional task that bore the strongest resemblance to the RR task, even this association was not strong. This may be attributable at least partially to differences in stance position and target location. 662

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For the RR task, each participant stood in a step stance, and the target was placed 15 cm beyond arm’s length in front of the participant’s paretic hip. For the biomechanical test (diagonal reach task), participants stood with their feet side by side, and the target was placed 1.4 arm-lengths away on the paretic side at a 45-degree angle from midline. The difference in foot position means that the participants may have been able to achieve high RR scores by reliance on the nonparetic leg for support in the step stance position. Other researchers48,49 have reported that the step stance position may encourage individuals to bear more weight on the posterior (in this case, nonparetic) leg. The difference in target location in our study means that the participants did not have to reach as far across midline to perform the RR task and, consequently, may have been able to compensate to some degree for their weighttransfer difficulties during this task. The possibility that participants could perform well on the RR task despite minimal weight transfer also may account for the weak or nonexistent relationships between RR scores and the weight-transfer measurements obtained for the stepping tasks. The RR task and the biomechanical measurements of weight transfer obtained during the stepping tasks (weight-transfer time and paretic-limb medial-lateral impulse) were similar in terms of emphasizing temporal components of limb movements in standing. The stepping tasks, however, required complete transition from bipedal to unipedal stance. In order to successfully lift one foot from the floor, the center of mass must move laterally at least as far as the medial border of the supporting foot.15 Although additional research would be needed to determine the extent of displacement of the center of mass during the RR task, the large, stationary base of sup-

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port limits the amount of displacement that is necessary for successful task performance. These results suggest that the RR may be more clinically important as a measure of dynamic postural control, as originally intended, than as an indicator of weight transfer, as we hypothesized here. The results of our study confirm previous reports in the literature of difficulties maintaining single-limb stance on the paretic side after stroke.15,50 As evidenced by their UMCe scores (Tab. 2), 24 (73%) of our subjects were unable to bear full weight on the paretic side with the knee flexed at 1 month poststroke, and 9 (31%) remained unable to do so at 6 months poststroke. The mean score (SD) on the ST (nonparetic limb) was 5.8⫾4.6 at 2 months poststroke, very similar to the score of 6.5⫾5.1 reported by Bernhardt and colleagues39 for subjects at the same time point during stroke recovery, but far below the normative value of 17.7⫾3.2 reported by Hill et al.29 Changes over time in the force platform measures of limb loading (Tab. 2) and weight transfer (Tab. 3) are more difficult to interpret. These data reflect inclusion of scores of 0 for participants who were unable to complete the various functional tasks. As a result, the values in the tables may underestimate the true means for each force platform measure. This issue is particularly salient for measures such as weight-transfer time, for which smaller values would indicate shorter durations (ie, better performance). The mean values for the force platform measures presented in Tables 2 and 3, therefore, should be interpreted with these caveats in mind. Limitations of the study included a relatively small sample size and a preponderance of participants with left-sided hemiparesis. With regard July 2009

Paretic–Lower-Extremity Loading and Weight Transfer After Stroke to the latter issue, we have found that speech and language impairments may complicate the process of obtaining informed consent and thereby limit recruitment of subjects with right-sided hemiparesis. The sample included individuals with varying degrees of lower-extremity motor impairment, ranging from mild to severe, as well as those who showed evidence of unilateral visual neglect at baseline. Forty-five percent of the sample was nonwhite. Consequently, our results should be generalizable to the population of people poststroke with respect to these characteristics.

Conclusion Step Test scores were correlated with GRFs and other force platform measures during reaching, STS, and stepping tasks from 1 to 6 months poststroke. These correlations support the use of the ST as a measure of paretic–lower-limb loading in individuals recovering from stroke and provide clinicians, as well as researchers, with an accessible and easily administered alternative to laboratory measures of loading. We are currently investigating relationships between ST scores and measures of activity and participation after stroke in order to understand how impairments measured by the ST may affect these other domains. Additional research is needed to identify reliable, valid, and clinically accessible measures of weight transfer in this population. Dr Mercer, Dr Freburger, and Dr Purser provided concept/idea/research design and writing. Dr Mercer and Dr Chang provided data collection and project management. Dr Mercer and Dr Freburger provided data analysis and fund procurement. Dr Mercer provided participants, facilities/equipment, and institutional liaisons. Dr Freburger, Dr Chang, and Dr Purser provided consultation (including review of manuscript before submission).

versity of North Carolina at Chapel Hill and by the WakeMed Institutional Review Board. This study was supported by the National Institutes of Health/National Institute of Child Health and Human Development (grant R03 HD43907). Dr Purser’s work on this study was supported, in part, by a Mentored Research Career Development Award from the National Institutes of Health/National Center for Medical Rehabilitation Research/National Institute of Child Health and Human Development (1K01HD049593– 01A1). This article was received July 29, 2008, and was accepted March 18, 2009. DOI: 10.2522/ptj.20080230

References 1 Thom T, Haase N, Rosamond W, et al. Heart disease and stroke statistics—2006 update: a report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2006;113:e85– e151. 2 Gordon NF, Gulanick M, Costa F, et al. Physical activity and exercise recommendations for stroke survivors: an American Heart Association scientific statement from the Council on Clinical Cardiology, Subcommittee on Exercise, Cardiac Rehabilitation, and Prevention; the Council on Cardiovascular Nursing; the Council on Nutrition, Physical Activity, and Metabolism; and the Stroke Council. Circulation. 2004;109:2031–2041. 3 Bonita R, Solomon N, Broad JB. Prevalence of stroke and stroke-related disability. estimates from the Auckland stroke studies. Stroke. 1997;28:1898 –1902. 4 Dettmann MA, Linder MT, Sepic SB. Relationships among walking performance, postural stability, and functional assessments of the hemiplegic patient. Am J Phys Med. 1987;66:77–90. 5 Kusoffsky A, Apel I, Hirschfeld H. Reaching-lifting-placing task during standing after stroke: coordination among ground forces, ankle muscle activity, and hand movement. Arch Phys Med Rehabil. 2001;82:650 – 660. 6 Wall JC, Turnbull GI. Gait asymmetries in residual hemiplegia. Arch Phys Med Rehabil. 1986;67:550 –553. 7 Bohannon RW, Larkin PA. Lower extremity weight bearing under various standing conditions in independently ambulatory patients with hemiparesis. Phys Ther. 1985;65:1323–1325. 8 Turnbull GI, Charteris J, Wall JC. Deficiencies in standing weight shifts by ambulant hemiplegic subjects. Arch Phys Med Rehabil. 1996;77:356 –362. 9 Dean CM, Shepherd RB. Task-related training improves performance of seated reaching tasks after stroke: a randomized controlled trial. Stroke. 1997;28:722–728.

10 Lomaglio MJ, Eng JJ. Muscle strength and weight-bearing symmetry relate to sit-tostand performance in individuals with stroke. Gait Posture. 2005;22:126 –131. 11 Cameron DM, Bohannon RW, Garrett GE, et al. Physical impairments related to kinetic energy during sit-to-stand and curbclimbing following stroke. Clin Biomech (Bristol, Avon). 2003;18:332–340. 12 Brunt D, Vander Linden DW, Behrman AL. The relation between limb loading and control parameters of gait initiation in persons with stroke. Arch Phys Med Rehabil. 1995;76:627– 634. 13 Laufer Y, Dickstein R, Resnik S, Marcovitz E. Weight-bearing shifts of hemiparetic and healthy adults upon stepping on stairs of various heights. Clin Rehabil. 2000; 14:125–129. 14 de Haart M, Geurts AC, Dault MC, et al. Restoration of weight-shifting capacity in patients with postacute stroke: a rehabilitation cohort study. Arch Phys Med Rehabil. 2005;86:755–762. 15 Pai YC, Rogers MW, Hedman LD, Hanke TA. Alterations in weight-transfer capabilities in adults with hemiparesis. Phys Ther. 1994;74:647– 657; discussion 657– 659. 16 Messier S, Bourbonnais D, Desrosiers J, Roy Y. Weight-bearing on the lower limbs in a sitting position during bilateral movement of the upper limbs in post-stroke hemiparetic subjects. J Rehabil Med. 2005;37:242–246. 17 de Haart M, Geurts AC, Huidekoper SC, et al. Recovery of standing balance in postacute stroke patients: a rehabilitation cohort study. Arch Phys Med Rehabil. 2004;85:886 – 895. 18 Marigold DS, Eng JJ. The relationship of asymmetric weight-bearing with postural sway and visual reliance in stroke. Gait Posture. 2006;23:249 –255. 19 Kim CM, Eng JJ. Symmetry in vertical ground reaction force is accompanied by symmetry in temporal but not distance variables of gait in persons with stroke. Gait Posture. 2003;18:23–28. 20 Lee MY, Wong MK, Tang FT, et al. Comparison of balance responses and motor patterns during sit-to-stand task with functional mobility in stroke patients. Am J Phys Med Rehabil. 1997;76:401– 410. 21 Center for Functional Assessment Research and the Uniform Data System for Medical Rehabilitation. Guide for Use of the Uniform Data Set for Medical Rehabilitation, Including the Functional Independence Measure (FIM), Version 3.1. Buffalo, NY: State University of New York; 1990. 22 Cheng PT, Wu SH, Liaw MY, et al. Symmetrical body-weight distribution training in stroke patients and its effect on fall prevention. Arch Phys Med Rehabil. 2001;82:1650 –1654. 23 Rogers MW, Hedman LD, Pai YC. Kinetic analysis of dynamic transitions in stance support accompanying voluntary leg flexion movements in hemiparetic adults. Arch Phys Med Rehabil. 1993;74:19 –25.

The study was approved by the Biomedical Institutional Review Board (IRB) at the Uni-

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Paretic–Lower-Extremity Loading and Weight Transfer After Stroke 24 Winstein CJ, Gardner ER, McNeal DR, et al. Standing balance training: effect on balance and locomotion in hemiparetic adults. Arch Phys Med Rehabil. 1989;70:755–762. 25 Walker C, Brouwer BJ, Culham EG. Use of visual feedback in retraining balance following acute stroke. Phys Ther. 2000; 80:886 – 895. 26 Shumway-Cook A, Anson D, Haller S. Postural sway biofeedback: Its effect on reestablishing stance stability in hemiplegic patients. Arch Phys Med Rehabil. 1988; 69:395– 400. 27 Davies PM. Steps to Follow: The Comprehensive Treatment of Patients With Hemiplegia. Berlin, Germany: SpringerVerlag; 2000. 28 Goldie PA, Matyas TA, Spencer KI, McGinley RB. Postural control in standing following stroke: test-retest reliability of some quantitative clinical tests. Phys Ther. 1990;70:234 –243. 29 Hill KD, Bernhardt J, McGann AM, et al. A new test of dynamic standing balance for stroke patients: reliability, validity and comparison with healthy elderly. Physiother Can. 1996;48:257–262. 30 Keenan MA, Perry J, Jordan C. Factors affecting balance and ambulation following stroke. Clin Orthop Relat Res. 1984;(182): 165–171. 31 Perry J, Garrett M, Gronley JK, Mulroy SJ. Classification of walking handicap in the stroke population. Stroke. 1995;26:982– 989. 32 Portney LG, Watkins MP, eds. Foundations of Clinical Research: Applications to Practice. 2nd ed. Upper Saddle River, NJ: Prentice-Hall Inc; 2000.

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33 Fugl-Meyer AR, Jaasko L, Leyman I, et al. The post-stroke hemiplegic patient, 1: a method for evaluation of physical performance. Scand J Rehabil Med. 1975; 7:13–31. 34 Halligan P, Wilson B, Cockburn J. A short screening test for visual neglect in stroke patients. Int Disabil Stud. 1990;12:95–99. 35 Hartman-Maeir A, Katz N. Validity of the Behavioral Inattention Test (BIT): relationships with functional tasks. Am J Occup Ther. 1995;49:507–516. 36 Perennou D. Postural disorders and spatial neglect in stroke patients: a strong association. Restor Neurol Neurosci. 2006; 24:319 –334. 37 Katz JN, Larson MG, Phillips CB, et al. Comparative measurement sensitivity of short and longer health status instruments. Med Care. 1992;30:917–925. 38 Liang MH, Fossel AH, Larson MG. Comparisons of five health status instruments for orthopedic evaluation. Med Care. 1990; 28:632– 642. 39 Bernhardt J, Ellis P, Denisenko S, Hill K. Changes in balance and locomotion measures during rehabilitation following stroke. Physiother Res Int. 1998;3:109 –122. 40 Duncan PW, Weiner DK, Chandler J, Studenski S. Functional reach: a new clinical measure of balance. J Gerontol. 1990;45: M192–M197. 41 Patla AE, Frank JS, Winter DA, et al. Agerelated changes in balance control system: initiation of stepping. Clin Biomech (Bristol, Avon). 1993;8:179 –184.

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42 Buckley JG, Heasley K, Scally A, Elliott DB. The effects of blurring vision on mediolateral balance during stepping up or down to a new level in the elderly. Gait Posture. 2005;22:146 –153. 43 StataCorp. Stata Base Reference Manual. Vol 3, R-Z, Release 9. College Station, TX: Stata Press; 2005. 44 Estimation and post-estimation commands. In: Stata 9 User’s Guide. College Station, TX: Stata Press; 2005: chap 20. 45 Berry WD. Understanding Regression Assumptions. Thousand Oaks, CA: Sage Publications; 1993. 46 Long JS, Freese J. Regression Models for Categorical Dependent Variables Using Stata. College Station, TX: Stata Press; 2003. 47 Raftery A. Bayesian model selection in social research. In: Marsden PV, ed. Sociological Methodology. Vol 25. Oxford, United Kingdom: Blackwell Publishers; 1995:111–163. 48 Fishman MN, Colby LA, Sachs LA, Nichols DS. Comparison of upper-extremity balance tasks and force platform testing in persons with hemiparesis. Phys Ther. 1997;77:1052–1062. 49 Kirby RL, Price NA, MacLeod DA. The influence of foot position on standing balance. J Biomech. 1987;20:423– 427. 50 Eng JJ, Chu KS. Reliability and comparison of weight-bearing ability during standing tasks for individuals with chronic stroke. Arch Phys Med Rehabil. 2002;83:1138 – 1144.

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Research Report Elastic, Viscous, and Mass Load Effects on Poststroke Muscle Recruitment and Co-contraction During Reaching: A Pilot Study Tina M. Stoeckmann, Katherine J. Sullivan, Robert A. Scheidt

Background. Resistive exercise after stroke can improve strength (forcegenerating capacity) without increasing spasticity (velocity-dependent hypertonicity). However, the effect of resistive load type on muscle activation and cocontraction after stroke is not clear. Objective. The purpose of this study was to determine the effect of load type (elastic, viscous, or mass) on muscle activation and co-contraction during resisted forward reaching in the paretic and nonparetic arms after stroke.

Design. This investigation was a single-session, mixed repeated-measures pilot study.

Methods. Twenty participants (10 with hemiplegia and 10 without neurologic involvement) reached forward with each arm against equivalent elastic, viscous, and mass loads. Normalized shoulder and elbow electromyography impulses were analyzed to determine agonist muscle recruitment and agonist-antagonist muscle co-contraction.

Results. Muscle activation and co-contraction levels were significantly higher on virtually all outcome measures for the paretic and nonparetic arms of the participants with stroke than for the matched control participants. Only the nonparetic shoulder responded to load type with similar activation levels but variable co-contraction responses relative to those of the control shoulder. Elastic and viscous loads were associated with strong activation; mass and viscous loads were associated with minimal co-contraction.

Limitations. A reasonable, but limited, range of loads was available. Conclusions. Motor control deficits were evident in both the paretic and the nonparetic arms after stroke when forward reaching was resisted with viscous, elastic, or mass loads. The paretic arm responded with higher muscle activation and co-contraction levels across all load conditions than the matched control arm. Smaller increases in muscle activation and co-contraction levels that varied with load type were observed in the nonparetic arm. On the basis of the response of the nonparetic arm, this study provides preliminary evidence suggesting that viscous loads elicited strong muscle activation with minimal co-contraction. Further intervention studies are needed to determine whether viscous loads are preferable for poststroke resistive exercise programs.

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T.M. Stoeckmann, PT, DSc, is Clinical Assistant Professor and Neurologic Residency Program Coordinator, Department of Physical Therapy, Marquette University, Schroeder Health Complex, PO Box 1881, Milwaukee, WI 532011881 (USA). At the time of the study, she was a student in the Graduate Program in Neurology, Rocky Mountain University of Health Professions, Provo, Utah. Address all correspondence to Dr Stoeckmann at: tina.stoeckmann @ mu.edu. K.J. Sullivan, PT, PhD, is Associate Professor, Department of Biokinesiology and Physical Therapy, and Director, Professional Doctorate in Physical Therapy Program, University of Southern California, Los Angeles, California. R.A. Scheidt, PhD, is Associate Professor, Department of Biomedical Engineering, Marquette University, Milwaukee, Wisconsin, and Department of Physical Medicine and Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, Illinois. [Stoeckmann TM, Sullivan KJ, Scheidt RA. Elastic, viscous, and mass load effects on poststroke muscle recruitment and co-contraction during reaching: a pilot study. Phys Ther. 2009;89: 665– 678.] © 2009 American Physical Therapy Association

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Poststroke Muscle Recruitment and Co-contraction During Reaching

S

troke is the leading cause of serious, long-term disability in the United States because of sensorimotor impairments that affect functional ability.1 Physical therapists are faced with the clinical challenge of designing rehabilitation programs that address the activity limitations and resultant impairments associated with stroke. Of the cluster of upper motor neuron impairments that affect movement production after stroke, weakness is most strongly correlated with activity limitations.2,3 For the upper extremity, activities that include reaching are commonly affected.4,5 Upper motor neuron weakness is primarily associated with poor agonist muscle recruitment.6,7 However, impaired timing of agonist and antagonist muscle activation can result in cocontraction because of overlapping and opposing muscle activation; this co-contraction also can contribute to weakness during dynamic tasks. The effect of impaired coordination associated with co-contraction after stroke remains controversial, in part because of the variety of tasks and analytical approaches used as well as the operational definitions of cocontraction. For example, abnormal co-contraction in hemiparetic muscles has been described as “markedly altered timing”8 and as a “delay in initiation and termination.”9 Inappropriate co-contraction has been reported during dynamic reaching af-

Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on May 14, 2009, at www.ptjournal.org.

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ter stroke9,10 or in association with certain stages of recovery.11,12 In contrast, others have reported normal co-contraction levels during isometric contractions13 and appropriate sequential activation during reaching after stroke.14 Clinical studies have demonstrated that resistive exercise programs after stroke can increase strength (forcegenerating capacity)15–19 and improve the performance of functional tasks20 –22 with no increase in spasticity (velocity-dependent hypertonicity).17,23 In addition, improvements in strength have been associated with increased accuracy and timing (ie, coordination) in dynamic upper-extremity tasks.20,24 Our research hypotheses were formulated, in part, on the basis of the potential of resistive exercise to improve the strength and coordination of agonist and antagonist muscle groups impaired after stroke. Although physical therapists commonly use weights, elastic bands, pneumatic or hydraulic exercise machines, or pools for resistive exercise, no systematic studies have been conducted in people after stroke to investigate the effects of various resistive load types during strength training. The kinetic properties of resistive loads place unique demands on muscles during movement: the force required to elongate an elastic load increases with the distance the material is stretched; the force required to move against a viscous load (such as water) increases with movement speed; and for weights (mass loads), balanced and appropriately timed acceleration and deceleration forces are required to move and stop the load. Studies comparing these types of resistance have investigated adaptations to load type,25 muscle responses to unexpected loading,26 and variations in load magnitude27— but only in people who were neurologically intact. These subjects did

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not demonstrate co-contraction with any resistive load.8,27 It is not clear how these load types would affect muscle activation during resistive exercise in people after stroke. A growing body of literature has consistently demonstrated that force production and coordination (ie, speed and accuracy) are impaired in both the paretic and the nonparetic arms after stroke.28 –31 The purpose of this pilot study was to investigate the effects of commonly used resistive load types (mass, elastic, and viscous) on muscle activation and timing in both arms after stroke. The significance of this study is that it contributes important clinical insights related to the effects and, potentially, the effectiveness of specific physical rehabilitation interventions for people after stroke. Thus far, there has been insufficient evidence to guide therapists in selecting the resistive load type that can result in both an increase in strength and an improvement in muscle coordination. We hypothesized that the level of muscle activation during reaching would be higher against the viscous load because the peak force requirements of viscous loads coincide with the peak velocity profile of the movement, arguably the “weakest” part of the reach, on the basis of the forcevelocity relationship of muscle contraction. In contrast, we hypothesized that muscle timing for the mass load would be associated with the largest amount of abnormal co-contraction in both the nonparetic and the paretic arms after stroke because the mass load requires appropriately synchronized agonist and antagonist muscles to successfully move (accelerate) and stop (decelerate) the load.

Method Participants A convenience sample of 10 righthanded adults with hemiparesis attributable to stroke and 10 ageJuly 2009

Poststroke Muscle Recruitment and Co-contraction During Reaching Table 1. Participants’ Demographic Dataa

Group Stroke

Participant

Age, y

Maximum Isometric Push (N)

Grip (kg)

Sex

Month After Stroke

Paretic Arm

MAS Score

UE-FM Score

Hand Openingb

Paretic Arm

Nonparetic Arm

Nonparetic Arm

1

77

F

118

L

2

46

Yes

14

16

87

181

2

62

M

11

L

3

39

Yes

8

45

212

351

3

59

F

42

L

2

61

Yes

20

23

183

227

4

56

F

11

R

2

55

Yes

10

32

106

295

5

54

M

60

L

0

60

Yes

10

23

132

249

6

53

M

18

R

3

31

No

21

NT

146

338

7

52

M

316

L

2

24

No

13

43

318

407

8

51

F

37

L

2

24

No

9

43

73

236

9

48

M

39

L

3

21

No

17

NT

102

353

10

31

M

276

L

3

21

Yes

2

41

97

435

X (SD)

54 (11)

93 (112)

38 (16)

12 (6)

33 (11)

Group

Participant

Age, y

Sex

Control

1

80

F

2

60

F

3

60

4

Left Arm

145 (75)

307 (83)

Maximum Isometric Push (N)

Grip (kg)

X (SD)

Paretic Arm

Right Arm

Left Arm

Right Arm

26

29

214

216

32

29

240

195

M

46

46

517

550c

58

F

25

23

211

191

5

58

F

34

33

249

228

6

55

M

48

52

550c

459

7

56

M

63

61

550c

501

8

54

F

43

48

373

354

9

46

M

57

50

550

550c

10

27

M

68

71

529

394

55 (13)

44 (15)

44 (15)

c

398 (155)

364 (148)

a

F⫽female, M⫽male, L⫽left, R⫽right, MAS⫽Modified Ashworth Scale, NT⫽not tested, UE-FM⫽upper-extremity portion of the Fugl-Meyer Motor Assessment (maximum score⫽66). b Hand opening⫽active opening of the fingers to grasp an object. c Upper limit of force transducer.

matched right-handed control participants took part in this study. Participants were recruited from local rehabilitation centers and by use of posted flyers. Participants with hemiplegia had had a stroke at least 6 months before testing and had residual unilateral upper-extremity hemiparesis but retained the ability to push a handle at waist level away from their bodies while seated. Exclusion criteria included non–strokerelated neurologic deficits, tremor, July 2009

and inability to follow instructions. Control participants had no history of neurologic disease or injury or upper-limb injury and were age matched to the participants with stroke (⫾5 years) (Tab. 1). Written informed consent was obtained for each participant, in compliance with policies established by the institutional review boards of Marquette University and Rocky Mountain University of Health Professions.

Instruments The experimental task involved pushing the ball handle of a light cart-and-rail apparatus 15 cm away from the body in the horizontal plane at waist level against 3 different types of resistance: mass, viscous, and elastic (Fig. 1A). The mass load consisted of disk weights mounted on the cart, the viscous load comprised a pneumatic plunger with nozzle orifices of various sizes, and the elastic load was provided by

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Poststroke Muscle Recruitment and Co-contraction During Reaching Thera-Band* materials. Each cart was fitted with infrared markers and a force transducer (model BG 100†) mounted in series with its respective load. An OPTOTRAK 3020 motion analysis system‡ recorded force, kinematic, and electromyography (EMG) data for this study at a rate of 1,000 samples per second (sample data from one trial are shown in Fig. 2A). Experimental Procedure Each participant took part in a single experimental session. After providing informed consent, participants with stroke were evaluated for motor impairment and the severity of the impairment by a licensed physical therapist. Baseline assessments for participants with stroke included the Modified Ashworth Scale (MAS) and the upper-extremity portion of the Fugl-Meyer Motor Assessment. The grip strength of both arms was assessed for all participants.

Figure 1.

Participants were required to perform 10 successful reaches for all 3 loads with each arm. They were instructed to wait for the “go” signal and then push the cart forward until the cart marker touched the target post and remained at the target briefly before returning to the start position. A successful reach involved moving the cart forward to the spatial target (criterion: 16⫾1 cm) in about 0.5 second (criterion: 700⫾100 milliseconds). Data collection for each trial lasted 4 seconds from the time of the auditory “go” signal. Participants were informed of the criteria for a successful reach, and feedback about reach time and distance was provided after each trial. Participants were allowed to practice until they were successful

Experimental loads. (A) Cart-and-rail apparatus used for the experimental task. Participants reached 15 cm by pushing forward against the elastic load (far), the viscous load (center), and the mass load (near). Each cart was fitted with infrared markers and a force transducer. (B) Representative data for force profiles collected from a single control participant (x-axis shows time in milliseconds; y-axis shows force in newtons) during forward reaching against elastic, viscous, and mass loads. Shaded areas under the acceleration components of the curves were used to determine equivalent loads.

* The Hygenic Corp, 1245 Home Ave, Akron, OH 44310. † Mark-10 Corp, 11 Dixon Ave, Copiague, NY 11726. ‡ Northern Digital Inc, 5555 Business Park, Ste 100, Bakersfield, CA 93309.

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Poststroke Muscle Recruitment and Co-contraction During Reaching

Figure 2. Electromyography (EMG) data processing. (A) Representative data collected in one trial from a single control participant reaching against a viscous load. From top to bottom: channels of raw surface EMG data collected from the anterior deltoid muscle, posterior deltoid muscle, long head of the biceps muscle, short head of the biceps muscle, lateral head of the triceps muscle, and long head of the triceps muscle and force, velocity, and position data collected during forward reaching against a viscous load. Red cursors indicate the onset and offset of movement. (B) Representative data collected from a single control participant for the 6 muscles of interest plotted as the average of 10 trials of normalized, full-wave-rectified EMG data (⫾95% confidence interval) at 30% maximum voluntary isometric contractions (MVIC) for elastic, viscous, and mass loads. The dependent measure of agonist muscle activation (EMG impulse) was calculated as the area under the curve. Trials were aligned at movement onset (vertical dashed line). Scale bars (solid black lines) represent 500 ms for time on the x-axis and 20% MVIC on the y-axis. For traces indicated by asterisks, the vertical scale bar corresponds to 50% MVIC. (C) Representative example of normalized full-wave-rectified EMG data for anterior deltoid (blue trace) and posterior deltoid (green trace) muscle activation from a control arm (left panel) and a paretic arm (right panel) during reaching against a mass load. The red trace indicates the lowest EMG signal between the 2 muscles at each time point; the area under the red curve represents the measure of co-contraction. The left panel represents little co-contraction; the right panel represents significant co-contraction. The vertical dashed line indicates the onset of movement, when the forward reach velocity exceeded 0.02 m/s. Scale bars (solid black lines) represent 500 ms for time on the x-axis and 10% MVIC on the y-axis.

but generally needed only a few trials. Each participant reached against one type of resistance until 10 successful trials were achieved. This process was repeated for each of the remaining load types, resulting in 30 trials of data. Load order was randomized across subjects. Participants were allowed to rest as often as needed, although no subject requested a rest. Participants with July 2009

stroke started with the nonparetic limb so that they could learn the task before performing it with the lesscoordinated arm32; control participants started with the dominant (right) arm. Before and after the reaching trials, maximum-effort force data were collected from 3 isometric pushes against a cart locked in the midreach

position. The pretrial pushes were used to determine how much resistance to use for the subsequent experimental reaches. Pre- and postexperimental maximum-effort pushes also were compared to assess for fatigue; all participants exceeded their initial efforts by a small amount (⬍7%) in postexperimental testing, suggesting a modest learning effect and no fatigue.

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Poststroke Muscle Recruitment and Co-contraction During Reaching Data Collection and Analysis Load equivalency. Because the different load types placed substantially different kinetic demands on the subjects during reaching, we developed a method to determine resistive loads that would require approximately equivalent efforts across the 3 load types. On the basis of previous protocols of resistive movement after stroke,12,23 our goal was for each participant to reach against loads requiring approximately 30% of the preexperimental maximum isometric push. Resistive loads for each arm were matched to create “triplets” of equivalent force impulses, so that Imass ⫽ Iviscous ⫽ Ielastic with I being calculated as follows:

冕

t ⫽ tf

I ⫽

F共t兲 dt

t⫽0

In this equation, F is the measured force, t is time, and t⫽0 and t⫽tf represent the start time and the finish time for the movement, respectively. Thus, each participant was assigned a mass load whose peak acceleratory force requirement was closest to (but not more than) 30% of the subject’s preexperimental maximum isometric push, and the elastic and viscous loads with impulse values equivalent to that of the mass load completed the triplet. EMG data collection and analysis. Surface EMG data were collected from the anterior and posterior deltoid muscles, both heads of the biceps muscle, and the lateral and long heads of the triceps muscle (Fig. 2A). The prime movers for our task were identified as the anterior deltoid and triceps muscles in a pilot study of adults who were healthy; the antagonists were identified as the posterior deltoid and biceps muscles.

to frequencies between 10 and 500 Hz before sampling with a Noraxon MyoSystem 1200.§ Postprocessing within MATLAB 㛳 included calculating root-mean-square amplitudes of the full-wave-rectified EMG signals with a 25-millisecond slidingwindow root-mean-square filter and a 50-millisecond sliding-window low-pass filter. To capture the onset of contraction that precedes movement, we analyzed the EMG data beginning 300 milliseconds before the onset of movement. Movement onset was identified as the point at which the cart velocity exceeded 0.02 m/s, and onset ended when the velocity returned to less than 0.02 m/s (Fig. 2A, red cursors). The EMG data were recorded during preexperimental maximum voluntary isometric contractions (MVICs) for shoulder and elbow flexion and extension and quiet resting baseline trials.28,33 The lowest average EMG value for 3 resting baseline trials was subsequently subtracted from all experimental EMG values (including MVIC EMG values). The highest of the 3 resulting MVIC EMG values for each muscle group was used for normalization during postprocessing data analysis.34,35 All dependent outcome variables were calculated from the average EMG impulse data (V䡠ms)— expressed as a percentage of the MVIC—and included the average impulse for each agonist muscle and the co-contraction impulse between agonist and antagonist muscles. For each resistance type, the EMG signals from its 10 trials were averaged for each muscle, and the area under the curves was calculated (Fig. 2B). Our co-contraction measure estimated the amount of EMG overlap

for agonist and antagonist pairs, calculated as the area under the curve created by the lower of the 2 EMG values at each moment in time (Fig. 2C, red trace).36 This cocontraction impulse value reflected how much the least-active muscle was firing throughout the movement. In this way, agonist and antagonist pairs could be active at different times without any cocontraction, a distinction that was critical for the acceleration and deceleration of mass loads (Fig. 2B, right column). Statistical Testing The EMG recordings from one participant with hemiplegia were corrupted by a faulty ground electrode. The EMG data for this participant and the corresponding matched control participant were excluded from further analysis. Given the multiple comparisons of this study, a multivariate analysis of variance (MANOVA) was used to assess for an effect of arm type or load type on task performance. Separate analyses were completed for the paretic and nonparetic arms, each paired with the respective right or left arm of the age-matched control participant. To determine the effect of specific load types (mass, viscous, and elastic) on our dependent measures of agonist muscle activation and co-contraction, we used separate post hoc 2 (arm type) ⫻ 3 (load type) mixed-design, repeatedmeasures analyses of variance (ANOVAs). In all cases, effects were considered statistically significant at P⫽.05, as determined with Tukey t tests, when appropriate. Statistical tests were performed with the Minitab# statistics package.

§

The EMG signals were preamplified with a gain of 1,000 and band limited 670

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Noraxon USA Inc, 13430 N Scottsdale Rd, Ste 104, Scottsdale, AZ 85254. 㛳 The MathWorks Inc, 3 Apple Hill Dr, Natick, MA 01760-2098.

Number 7

# Minitab Inc, Quality Plaza, 1829 Pine Hall Rd, State College, PA 16801-3008.

July 2009

Poststroke Muscle Recruitment and Co-contraction During Reaching Table 2. Participants’ Strength Values and Analysisa

P2

Paretic Arm

Nonparetic Arm

P3

Paretic vs Control Arms, P4

Control Participants

Parameter X (SE) grip strength, kg X (SE) maximum isometric push, kg

Participants With Stroke

Right

Left

P1

(Paretic) Control Arm

(Nonparetic) Control Arm

Nonparetic vs Control Arms, P5

44.2 (3.9)

44.2 (3.9)

1.0

44.4 (3.9)

44.0 (43.9)

.95

12.4 (2.4)

33.3 (3.4)

⬍.001

⬍.001

.11

363.8 (12.2)

398.3 (12.4)

.62

367.2 (12.4)

374.9 (12.4)

.91

145.6 (8.6)

307.0 (9.1)

⬍.001

.001

.24

a P1⫽one-way analysis of variance (ANOVA) for comparison of right and left arms of control participants, P2⫽one-way ANOVA for comparison of (paretic) control and (nonparetic) control arms, P3⫽one-way ANOVA for comparison of paretic and nonparetic arms, P4⫽one-way ANOVA for comparison of paretic and control arms, P5⫽one-way ANOVA for comparison of nonparetic and control arms.

Results Baseline Participant Characteristics Participants with stroke and participants who were neurologically intact (control participants) were well matched with respect to age and sex (Tab. 1). As expected, values for both grip and isometric strength assessments for the paretic arm were significantly lower than those for both the nonparetic and the control arms (Pⱕ.001 for each). There were no significant strength differences between the right and the left arms of the control participants (P values for grip and push were 1.0 and .62, respectively) (Tab. 2). Although the lower mean values of both strength measures for the nonparetic arm than for the control arm were not significantly different (P values for grip and push were .11 and .24, respectively), these differences reflected medium to large effect sizes37 (.79 and .55 for grip and push, respectively), consistent with previous reports indicating mild impairment of the nonparetic arm.28,30,31,38 Paretic Arm The MANOVA provided evidence for a difference in arm type (P⬍.001) but not in load type (P⫽.74) across our paretic arm performance measures. A post hoc repeated-measures ANOVA indicated that the level of July 2009

normalized muscle activation was significantly higher in the paretic arm than in the control arm for the agonist muscles (anterior deltoid and triceps muscles) as well as for coactivity at the shoulder and elbow (P⬍.001 for all comparisons), reflecting a marked effect of stroke on muscle recruitment and selection (Tab. 3, Fig. 3). Although the MANOVA did not provide compelling evidence of an effect of load type, visual inspection of the data in a comparison of the paretic and control arms in Figure 4 (histogram pairs in top row, right) suggested that the anterior deltoid muscle recruitment of the control arm was affected by load type. A separate post hoc one-way ANOVA revealed that the level of anterior deltoid muscle recruitment for the elastic and viscous loads was significantly higher than that for the mass load in the control arm (P⫽.004), whereas there were no differences between the load types in the paretic arm (P⫽.92). We suspect that this interaction between load type and arm type did not reach statistical significance because of the similar trending of the data for both the paretic and the control arms in combination with the large variability of the data for the paretic arm.

Nonparetic Arm A second MANOVA provided compelling evidence for significant effects of arm type (P⫽.007) and load type (P⫽.002) in a comparison of the nonparetic and control arms. A post hoc analysis revealed that normalized muscle activation was significantly higher in the nonparetic arm than in the matched control arm for all outcome measures (P⬍.05) except anterior deltoid muscle recruitment (Tab. 3, Fig. 3). Both agonist muscle recruitment and co-contraction were affected by load type at the shoulder but not at the elbow (Tab. 3, Fig. 4). Elastic and viscous loads resulted in significantly higher levels of muscle recruitment than the mass load for the anterior deltoid muscle in both the nonparetic and the control arms (Tab. 3 [Tukey post hoc analysis], Fig. 4). Although the elastic load elicited higher levels of shoulder cocontraction than the mass load in the nonparetic arm, the viscous load did not (Tab. 3 [Tukey post hoc analysis], Fig. 4). A marginal interaction between arm type and load type for anterior deltoid muscle recruitment was also demonstrated (P⫽.06). Despite the different magnitudes of the responses, both arm types demonstrated a sensitivity to load type at the shoulder, reflecting a blend of

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Poststroke Muscle Recruitment and Co-contraction During Reaching Table 3. Muscle Impulse Data From Repeated-Measures Analysis of Variance for Nonparetic and Paretic Armsa V䡠ms for: Nonparetic Arm (nⴝ9) Parameter

Load

X

SE

Load (2 df)

Arm (1 df)

Control Arm (nⴝ9) X

SE

Anterior deltoid muscle activation

V䡠ms for: Paretic Arm (nⴝ9)

F 12.93

P

F

<.001

b

1.92

P

X

SE

Load (2 df)

Control Arm (nⴝ9) X

SE

.17

Mass

28.6

9.3

24.4

4.0

130.3

36.4

34.8

8.9

Elastic

88.4

14.8

67.2

13.6

150.9

45.2

81.6

15.2

Viscous

80.7

14.1

67.8

7.5

149.9

33.5

84.0

20.7

Triceps muscle activation

0.93

.40

4.48

.04

Mass

235.2

31.6

169.4

30.8

322.9

72.5

201.1

22.9

Elastic

169.2

37.8

123.0

19.2

259.1

43.7

141.2

26.8

Viscous

233.8

79.4

129.4

19.9

282.3

46.7

163.1

36.8

Shoulder coactivity

3.49 Mass

6.9

3.9

Elastic

24.2

Viscous

15.6

.04

c

4.83

.03

8.8

2.3

39.7

11.1

8.9

2.0

6.1

9.4

1.7

44.2

13.2

8.9

2.0

2.2

10.3

1.9

35.8

10.8

9.0

2.2

Elbow coactivity

0.47

.63

11.47

Arm (1 df)

.001

Mass

28.8

6.5

15.1

3.8

74.2

16.5

14.3

4.1

Elastic

23.2

5.9

11.3

2.6

56.7

8.8

11.2

3.1

Viscous

27.1

6.1

12.2

2.6

65.6

14.0

11.5

3.3

F

P

F

P

0.84

.44

15.54

<.001

0.88

.42

17.69

<.001

0.10

.91

19.4

<.001

0.59

.56

43.46

<.001

a

Bold type indicates comparisons that achieved statistical significance (P⬍.05). b P values determined with Tukey post hoc analysis for comparisons of mass with elastic, mass with viscous, and elastic with viscous were .0001, .0003, and .95, respectively. c P values determined with Tukey post hoc analysis for comparisons of mass with elastic, mass with viscous, and elastic with viscous were .03, .31, and .49, respectively.

both normal and impaired responses in the nonparetic arm.

mass load, with little co-contraction for any load type.

Discussion

In contrast, reaching with a hemiparetic (paretic) arm resulted in a high percentage of muscle activation and a higher level of co-contraction across all load types relative to those in people without neurologic involvement.

On the basis of the kinetic properties of common resistive load types used for strengthening, reaching against elastic or viscous loads requires only agonist muscle activation, whereas reaching against mass loads requires appropriately timed agonist and antagonist muscle activation to move and stop the load (Fig. 2B).39 As expected, people without neurologic involvement had higher levels of agonist muscle (ie, anterior deltoid and triceps muscles) activation during forward reaching against the elastic and viscous loads than against the 672

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We also found evidence of impairment during reaching in the nonparetic arm. With the exception of shoulder agonist muscle activation, nonparetic arms also demonstrated higher percentages of muscle activation and co-contraction, which differed in response to load type. Spe-

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cifically, elastic and viscous loads were associated with a higher level of agonist muscle activation (anterior deltoid muscle), and elastic loads were associated with the most co-contraction at the shoulder. In light of our findings of differences in muscle activation patterns in the paretic and nonparetic arms of people after stroke and people who were neurologically intact (control participants), future research and clinical applications should include consideration of the types of loads being used to improve strength, and a load type should be chosen on the basis of its effect on muscle activation. July 2009

Poststroke Muscle Recruitment and Co-contraction During Reaching

Figure 3. Effect of arm type on normalized electromyography (EMG) impulses. Bar graphs show mean and standard error (SE) of the normalized EMG impulses for the agonist anterior deltoid and triceps muscles (top row) and coactivity for the shoulder and elbow (bottom row) by group collapsed across load types. Shaded bars represent the paretic arm (PAR [dark blue]) and the nonparetic arm (N-PAR [light blue]) of participants with stroke; white bars represent matched control (CON) participants. Significant differences are indicated by asterisks: *P⬍.05, **P⬍.001.

Agonist Muscle Recruitment Because the peak force requirement of a viscous load coincides with the peak of the velocity profile (theoretically the weakest part of the reach, on the basis of the force-velocity relationship of the muscles), we hypothesized that the viscous load would induce a higher level of agonist muscle recruitment. This hypothesis was only partially supported by our data. The elastic and viscous loads were equally effective in eliciting significantly higher levels of agonist muscle activation than the mass load—and only at the shoulder for the control and nonparetic arms. As expected for the control group, July 2009

the elastic and viscous loads elicited only agonist muscle activation, whereas the mass load elicited a brief agonist burst and then a brief antagonist burst, which coincided with the acceleration and deceleration profiles for the load, respectively. This biphasic muscle activation profile is consistent with those in other single-joint studies of subjects who were healthy and who responded to changes in these load types.19,27,39 Gottlieb et al27 reported synchronization of biphasic muscle torque and EMG values at both the elbow and the shoulder in response to resisted reaching, whereas our participants demonstrated this pat-

tern only at the shoulder. This difference likely was attributable to the arm configuration for the reaching task. In the study by Gottlieb et al,27 the reach occurred with 90 degrees of shoulder abduction, whereas the reach occurred with 0 degrees of abduction in the present study. Such posture-dependent and task-specific effects also have been described by other authors.40 – 43 In contrast, the paretic arm consistently used a higher percentage of maximum voluntary effort and cocontraction across all load types. This finding is consistent with those of other stroke studies reporting that

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Figure 4. Effect of load type by arm on normalized electromyography (EMG) impulses. Bar graphs show mean and standard error (SE) of the normalized full-wave-rectified EMG impulses for the agonist anterior deltoid (first row) and triceps (second row) muscles, shoulder coactivity (third row), and elbow coactivity (fourth row) by group and load type. Bars are ordered by load type (M⫽mass, E⫽elastic, and V⫽viscous) for the paretic (PAR [dark blue]), nonparetic (N-PAR [light blue]), and respective matched control (CON [white]) groups. Significant differences are indicated by asterisks: *P⬍.05. Note differences in the scaling of the y-axis.

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Poststroke Muscle Recruitment and Co-contraction During Reaching participants with more motor impairment after stroke lacked the ability to individually coordinate joints within a limb and were unable to adapt their motor responses to various upper-extremity tasks.5,44 – 46 Lum et al associated the presence of these abnormal synergies with strength imbalances,47 suggesting an association between strength and coordination in this population. Importantly, both paretic and nonparetic muscles used a higher percentage of their voluntary capacity to reach against various types of resistance, as evidenced by increased agonist muscle recruitment and cocontraction in most conditions. Thus, although our results are consistent with the earlier findings that paretic muscles are much less efficient in producing force, requiring more EMG activity to effectively move a load,4,6,7,47 our results also implicate excessive co-contraction of the antagonist muscle10 –12,48 as potentially contributing to the clinical presentation of weakness during our dynamic task. Coactivity Some investigators have suggested that abnormal co-contraction patterns represent a reduction in the number of muscle combinations or possible synergies available in a paretic limb after stroke,18 reflecting impairments in both agonist muscle recruitment and antagonist muscle inhibition.49 Our second hypothesis proposed that the levels of agonistantagonist muscle co-contraction would be elevated in the paretic and nonparetic arms in response to the mass load, the only load that inherently required appropriately timed agonist and antagonist muscle activation.39 Our dynamic task, combined with the different kinetic demands for the loads tested, required a measurement of co-contraction that was sensitive to the timing of agonist and antagonist muscle activation. Simply July 2009

measuring antagonist muscle activation levels may contribute to erroneous conclusions about the presence or absence of co-contraction; it is not just whether antagonist muscles are on but when they are on that is critical. Thus, a unique contribution of this pilot study is the introduction of a temporally sensitive method of quantifying co-contraction. On the basis of this analysis, we were able to demonstrate and support our hypothesis that both the paretic and the nonparetic arms would exhibit a significant amount of co-contraction not observed in the control arms. Specifically, we found that the nonparetic shoulder showed a significantly higher level of co-contraction with the elastic load than with the mass load but not the viscous load. A post hoc analysis (t tests) confirmed that the level of co-contraction of the nonparetic shoulder was significantly higher than that of the control shoulders for the elastic load (P⫽.05), but the levels of cocontraction for the viscous and mass loads were lower and comparable to those of the control shoulders (P⫽.09 and P⫽.68, respectively). Therefore, the nonparetic arm showed more flexible motor strategies than the paretic arm but this variable level of co-contraction is not consistent with the consistently minimal co-contraction seen in the control arms. We believe that the higher level of co-contraction for the elastic load may reflect the need for large stabilization forces at the end of reach for the elastic load.13,50 The “Unimpaired” (Nonparetic) Arm Also Is Affected Consistent with the growing body of evidence that the “unimpaired” limb also shows subtle motor impairments after stroke,30,31 we also found significant differences between the nonparetic and control arms in all EMG outcome measures except anterior deltoid muscle recruitment

(Fig. 3). Lower baseline strength is consistent with deficits in isometric torque production reported by other authors.28,29 More sensitive kinematic and kinetic studies have consistently demonstrated motor control deficits in the “less paretic” limb after stroke, such as the impaired muscle timing represented in the present study by high levels of cocontraction.51 Such deficits call into question the use of the nonparetic arm as a matched control for research or clinical practice. Clinical Applications and Future Studies Because both muscle weakness and co-contraction correlate significantly with motor impairment and disability,52 the results of the present study may have important implications. There is very little literature suggesting effective treatment strategies for temporal coordination deficits after stroke. With mounting evidence supporting the use of resistive strength training to reduce impairments after stroke,15,16 the logical extension of the present study is to determine whether training with a particular type of resistance can preferentially benefit both muscle recruitment and coordination. In our study, muscle activation patterns (our indicator of coordination) were specific to our task and the kinetic demands imposed on the limb by different resistive loads for both the nonparetic and the control arms. Viscous loads, in particular, appeared to place demands on the muscle that resulted in higher levels of muscle activation with less cocontraction than did elastic or mass loads. However, the paretic arm responded with high levels of muscle activation and co-contraction across all load types. Future intervention studies could investigate whether strengthening exercises with viscous loads are more effective than those with other loads for developing

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Poststroke Muscle Recruitment and Co-contraction During Reaching strength without co-contraction after stroke. Some investigators have suggested that weakness in the paretic elbow musculature reveals a strong task dependence that is attributed to abnormal synergy between the elbow and the shoulder muscles43 and that can be modified with training.46 On the basis of the specificity of the training literature,40,41,53 one could extrapolate that practice accelerating and decelerating mass loads might facilitate the generation of more appropriately timed agonist and antagonist muscle activation, elastic loads might foster stability, and viscous loads might preferentially facilitate agonist muscle recruitment with minimal co-contraction. Lum et al54 found that participants with stroke showed improvements in agonist muscle EMG amplitude and work output and reductions in force direction errors after guided reaching against robotically simulated viscous loads. However, the support provided during the guided reaching task reduced the need to accommodate the mass of the limb, altering the dynamic requirements of the reaching task. Cirstea et al reported that a single session spent practicing arm pointing movements led to improved elbow and shoulder muscle timing in subjects who had had a stroke and had mild to moderate levels of functioning.42 Given that the arm itself acts predominantly as a mass load during reaching tasks, such findings may provide mechanistic support for randomized controlled trials that have demonstrated the effectiveness of task-specific training in people after stroke.55 Further investigation is needed to determine which type of resistive training might best help subjects acquire more appropriate motor responses after stroke. Although the optimal treatment has yet to be identified, there is a grow676

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ing awareness of the need to address both strength and coordination in rehabilitation paradigms.43 For example, Sullivan et al21 used a combination of task-specific training and isotonic strengthening of the legs to improve ambulation; that strategy positively affected both impairment and function, with improvements continuing even 6 months later. Using a different exercise sequence, Patten and colleagues22 evaluated an upper-extremity hybrid intervention comprising both resistance training and functional task practice and reported strength gains with increased EMG activation and marked improvement in all clinical and functional measures. Although further research along these lines is needed, our pilot study is a preliminary step in developing a method for directly comparing different types of resistive loads and evaluating their effects on motor control.

Conclusion

Study Limitations The present study had a few minor limitations. The side on which the lesion was located was not homogeneous across participants (8 of 10 had right-side cerebrovascular accidents). Despite the fact that our participants’ Fugl-Meyer Motor Assessment scores fell within the moderate impairment category,12 our participants had with a fairly wide range of impairment levels within that category. Given that muscle activation patterns may be related to the level of residual arm function,11,12,56,57 these variables should be more tightly controlled in future work. Finally, although the clinically based loads were specifically chosen for their validity, matching these load triplets to each participant’s strength was limited to the weight increments available. Robotic techniques have already shown potential in stroke rehabilitation for the arm19,58 and would provide a means for more precisely matching resistive loads to individual abilities.

The significance of this pilot study is that it revealed anticipated differences in muscle activation and cocontraction by load type that were not distinguishable in the hemiparetic arm. However, the nonparetic arm provided a model of mildly impaired motor response that might be more sensitive to investigations of intervention efficacy. Future studies should be conducted to determine intervention effectiveness before the initiation of an intervention trial.

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The present study provides preliminary information on the effects of reaching against equivalent mass, viscous, and elastic loads on the muscle activation patterns of the paretic and nonparetic arms of people who have had a stroke. Of the 3 load types, only the viscous load resulted in increased activation with minimal cocontraction in the nonparetic shoulder. Because of the motor control deficits (including upper motor neuron weakness and co-contraction) in the paretic arm, muscle activation in that arm was less efficient and did not differ across the load types. In contrast, muscle activation patterns did differ by load type in the control and nonparetic arms. Consistent with previous reports, the nonparetic arms showed impairments in muscle activation that might not be readily detected with clinical motor control assessments.

Dr Stoeckmann and Dr Scheidt provided concept/idea/research design, project management, and fund procurement. All authors provided writing and data analysis. Dr Stoeckmann provided data collection and participants. Dr Scheidt provided facilities/ equipment. Dr Sullivan and Dr Scheidt provided consultation (including review of manuscript before submission). The authors are grateful to Guy Simoneau, PhD, for his insightful comments on the analysis of this project and Supriya Asnani, MS, for her assistance in software programming as well as data collection and analysis. They also are deeply indebted to Priyanka

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Poststroke Muscle Recruitment and Co-contraction During Reaching Kanade, MS, for building and validating the cart-on-rail system. This research was done in partial fulfillment of the requirements for Dr Stoeckmann’s Doctor of Science degree at Rocky Mountain University of Health Professions, Provo, Utah. This study was approved by the institutional review boards of Marquette University and Rocky Mountain University of Health Professions. This work was supported by a Marquette University College of Health Science Faculty Development Award to Dr Stoeckmann, by the National Science Foundation (grant BES 0238442) awarded to Dr Scheidt, and by the National Institute of Child Health and Human Development, National Institutes of Health (grants NIH R24 HD39627 and NIH R01 HD53727) awarded to Dr Scheidt. This article was received April 30, 2008, and was accepted March 18, 2009. DOI: 10.2522/ptj.20080128

References 1 American Heart Association. Heart disease and stroke statistics: 2007 update. Circulation. 2007;115:e69 – e171. 2 Harris J, Eng JJ. Paretic upper-limb strength best explains arm activity in people with stroke. Phys Ther. 2007;87: 88 –97. 3 LeBrasseur NK, Sayers SP, Ouellette MM, Fielding RA. Muscle impairments and behavioral factors mediate functional limitations and disability following stroke. Phys Ther. 2006;86:1342–1350. 4 Wagner JM, Lang CE, Sahrmann SA, et al. Relationships between sensorimotor impairments and reaching deficits in acute hemiparesis. Neurorehabil Neural Repair. 2006;20:406 – 416. 5 Zackowski KM, Dromerick AW, Sahrmann SA, et al. How do strength, sensation, spasticity, and joint individuation relate to reaching deficits of people with chronic hemiparesis? Brain. 2004;127:1035–1046. 6 Gowland C, deBruin H, Basmajian JV, et al. Agonist and antagonist activity during voluntary upper-limb movement in patients with stroke. Phys Ther. 1992;72:624 – 633. 7 Sahrmann SA, Norton BJ. The relationship of voluntary movement to spasticity in the upper motor neuron syndrome. Ann Neurol. 1977;2:460 – 465. 8 Hoffman DS, Strick PL. Effects of a primary motor cortex lesion on step-tracking movements of the wrist. J Neurophysiol. 1995; 73:891– 895. 9 Chae J, Yang G, Park BK, Labatia I. Delay in initiation and termination of muscle contraction, motor impairment, and physical disability in upper limb hemiparesis. Muscle Nerve. 2002;25:568 –575.

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10 Levin MF, Selles RW, Verheul MHG, Meijer OG. Deficits in the coordination of agonist and antagonist muscles in stroke patients: implications for normal motor control. Brain Res. 2000;853:352–369. 11 el-Abd MA, Ibrahim IK, Dietz V. Impaired activation pattern in antagonistic elbow muscles of patients with spastic hemiparesis: contribution to movement disorder. Electromyogr Clin Neurophysiol. 1993; 33:247–255. 12 Dancause N, Ptito A, Levin MF. Error correction strategies for motor behavior after unilateral brain damage: short-term motor learning processes. Neuropsychologia. 2002;40:1313–1323. 13 Fellows SJ, Kaus CK, Thilmann AF. Agonist and antagonist EMG activation during isometric torque development at the elbow in spastic hemiparesis. Electroencephalogr Clin Neurophysiol. 1994;93: 106 –112. 14 Wagner JM, Dromerick AW, Sahrmann SA, Lang CE. Upper extremity muscle activation during recovery of reaching in subjects with post-stroke hemiparesis. Clin Neurophysiol. 2007;118:164 –176. 15 Eng JJ. Strength training in individuals with stroke. Physiother Can. 2004;56: 189 –201. 16 Morris SL, Dodd KJ, Morris ME. Outcomes of progressive resistance strength training following stroke: a systematic review. Clin Rehabil. 2004;18:27–39. 17 Teixeira-Salmela LF, Olney SJ, Nadeau S, Brouwer B. Muscle strength and physical conditioning to reduce impairment and disability in chronic stroke survivors. Arch Phys Med Rehabil. 1999;80:1211–1218. 18 Dewald JPA, Pope PS, Given JD, et al. Abnormal muscle coactivation patterns during isometric torque generation at the elbow and shoulder in hemiparetic subjects. Brain. 1995;118:495–510. 19 Lum PS, Burgar CG, Shor PC, et al. Robotassisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Arch Phys Med Rehabil. 2002;83:952–959. 20 Canning CG, Ada L, Adams R, O’Dwyer NJ. Loss of strength contributes more to physical disability after stroke than loss of dexterity. Clin Rehabil. 2004;18:300 –308. 21 Sullivan KJ, Klassen T, Mulroy S. Combined task-specific training and strengthening effects on locomotor recovery poststroke: a case study. J Neurol Phys Ther. 2006;30:130 –141. 22 Patten C, Dozono J, Schmidt S, et al. Combined functional task practice and dynamic high intensity resistance training promotes recovery of upper-extremity motor function in post-stroke hemiparesis: a case study. J Neurol Phys Ther. 2006; 30:99 –115. 23 Badics E, Wittmann A, Rupp M, et al. Systematic muscle building exercises in the rehabilitation of stroke patients. NeuroRehabilitation. 2002;17:211–214.

24 Carroll TJ, Barry B, Riek S, Carson RG. Resistance training enhances the stability of sensorimotor coordination. Proc R Soc London Ser B: Biol Sci. 2001;268: 221–227. 25 Fukushi T, Ashe J. Adaptation of arm trajectory during continuous drawing movements in different dynamic environments. Exp Brain Res. 2003;148:95–104. 26 Simmons RW, Richardson C. Peripheral control of the antagonist muscle during unexpectedly loaded arm movements. Brain Res. 1992;585:260 –266. 27 Gottlieb GL, Song Q, Hong DA, Corcos D. Coordinating two degrees of freedom during human arm movement: load and speed invariance of relative joint torques. J Neurophysiol. 1996;76:3196 –3206. 28 Bohannon RW. Measurement and nature of muscle strength in patients with stroke. J Neurol Rehabil. 1997;11:115–125. 29 McCrea PH, Eng JJ, Hodgson AJ. Time and magnitude of torque generation is impaired in both arms following stroke. Muscle Nerve. 2003;28:46 –53. 30 Sainburg RL, Duff SV. Does motor lateralization have implications for stroke rehabilitation? J Rehabil Res Dev. 2006; 43:311–322. 31 Desrosiers J, Bourbonnais D, Bravo G, et al. Performance of the “unaffected” upper extremity of elderly stroke patients. Stroke. 1996;27:1564 –1570. 32 Criscimagna-Hemminger S, Donchin O, Gazzaniga M, Shadmer R. Learned dynamics of reaching movements generalize from dominant to nondominant arm. J Neurophysiol. 2003;89:168 –176. 33 Mercier C, Bertrand AM, Bourbonnais D. Comparison of strength measurements under single-joint and multijoint conditions in hemiparetic individuals. Clin Rehabil. 2005;19:523–530. 34 Harris GF, Smith PA. Human Motion Analysis: Current Applications and Future Directions. New York, NY: IEEE Press; 1996. 35 Kasman GS, Cram JR, Wolf SL, Barton L. Clinical Applications in Surface Electromyography. Gaithersburg, MD: Aspen Publishers; 1998. 36 Suminski AJ, Rao SM, Mosier KM, Scheidt RA. Neural and electromyographic correlates of wrist posture. J Neurophysiol. 2007;97:1527–1545. 37 Thomas JR, Salazar W, Landers DM. What is missing in p less than .05? Effect size. Res Q Exerc Sport. 1991;62:344 –348. 38 Andrews AW, Bohannon RW. Short-term recovery of limb muscle strength after acute stroke. Arch Phys Med Rehabil. 2003;84:125–130. 39 Gottlieb GL. On the voluntary movement of compliant (inertial-viscoelastic) loads by parcellated control mechanisms. J Neurophysiol. 1996;76:3207–3229. 40 Lindh M. Increase of muscle strength from isometric quadriceps exercises at different knee angles. Scand J Rehabil Med. 1979; 11:33–36.

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Poststroke Muscle Recruitment and Co-contraction During Reaching 41 Kurtzer I, DiZio P, Lackner J. Taskdependent motor learning. Exp Brain Res. 2003;153:128 –132. 42 Cirstea MS, Mitnitski AB, Feldman AG, Levin MF. Interjoint coordination dynamics during reaching in stroke. Exp Brain Res. 2003;151:289 –300. 43 Beer RF, Given JD, Dewald JPA. Taskdependent weakness at the elbow in patients with hemiparesis. Arch Phys Med Rehabil. 1999;80:766 –772. 44 Reisman DS, Scholz JP. Aspects of joint coordination are preserved during pointing in persons with post-stroke hemiparesis. Brain. 2003;126:2510 –2527. 45 Levin MF. Interjoint coordination during pointing movements is disrupted in spastic hemiparesis. Brain. 1996;119: 281–293. 46 Ellis MD, Holubar BG, Acosta AM, et al. Modifiability of abnormal isometric elbow and shoulder joint torque coupling after stroke. Muscle Nerve. 2005;32:170 –178. 47 Lum PS, Burgar CG, Shor PC. Evidence for strength imbalances as a significant contributor to abnormal synergies in hemiparetic subjects. Muscle Nerve. 2003;27: 211–221.

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48 Kamper DG, Rymer WZ. Impairment of voluntary control of finger motion following stroke: role of inappropriate muscle coactivation. Muscle Nerve. 2001;24: 673– 681. 49 Hammond MC, Fitts SS, Kraft GH, et al. Co-contraction in the hemiparetic forearm: quantitative EMG evaluation. Arch Phys Med Rehabil. 1988;69:348 –351. 50 Gribble PL, Ostry DJ. Independent coactivation of shoulder and elbow muscles. Exp Brain Res. 1998;123:355–360. 51 Kim SH, Pohl PS, Luchies CW, et al. Ipsilateral deficits of targeted movements after stroke. Arch Phys Med Rehabil. 2003;84: 719 –724. 52 Chae J, Yang G, Park BK, Labatia I. Muscle weakness and co-contraction in upper limb hemiparesis: relationship to motor impairment and physical disability. Neurorehabil Neural Repair. 2002;16:241–248. 53 Page SJ. Intensity versus task-specificity after stroke: how important is intensity? Am J Phys Med Rehabil. 2003;82: 730 –732. 54 Lum PS, Burgar CG, Shor PC. Evidence for improved muscle activation patterns after retraining of reaching movements with the MIME robotic system in subjects with post-stroke hemiparesis. IEEE Trans Neural Syst Rehabil Eng. 2004;12:186 –194.

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55 Kwakkel G, Wagenaar RC, Twisk JWR, et al. Intensity of leg and arm training after primary middle-cerebral-artery stroke: a randomised trial. Lancet. 1999;354: 191–196. 56 Kamper DG, McKenna-Cole AN, Kahn LE, Reinkensmeyer DJ. Alterations in reaching after stroke and their relation to movement direction and impairment severity. Arch Phys Med Rehabil. 2002;83: 702–707. 57 Cirstea MC, Ptito A, Levin MF. Arm reaching improvements with short-term practice depend on the severity of the motor deficit in stroke. Exp Brain Res. 2003;152:476 – 488. 58 Fasoli S, Krebs HL, Stein J, et al. Effects of robotic therapy in motor impairment and recovery in chronic stroke. Arch Phys Med Rehabil. 2003;84:477– 482.

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Research Report Treadmill Testing of Children Who Have Spina Bifida and Are Ambulatory: Does Peak Oxygen Uptake Reflect Maximum Oxygen Uptake? Janke Frederike de Groot, Tim Takken, Sanna de Graaff, Rob H.J.M. Gooskens, Paul J.M. Helders, Luc Vanhees

Background. Earlier studies have demonstrated low peak oxygen uptake ˙ O2peak) in children with spina bifida. Low peak heart rate and low peak respiratory (V exchange ratio in these studies raised questions regarding the true maximal character ˙ O2peak values obtained with treadmill testing. of V Objective. The aim of this study was to determine whether the V˙ O2peak measured during an incremental treadmill test is a true reflection of the maximum oxygen ˙ o2max) in children who have spina bifida and are ambulatory. uptake (V Design. A cross-sectional design was used for this study. Methods. Twenty children who had spina bifida and were ambulatory partici˙ O2peak was measured during a graded treadmill exercise test. The pated. The V ˙ O2peak measurements was evaluated by use of previously described validity of V guidelines for maximum exercise testing in children who are healthy, as well as ˙ O2peak and V ˙ O2 during a supramaximal protocol (V ˙ O2supradifferences between V maximal).

Results. The average values for V˙ O2peak and normalized V˙ O2peak were, respectively, 1.23 L/min (SD⫽0.6) and 34.1 mL/kg/min (SD⫽8.3). Fifteen children met at least 2 of the 3 previously described criteria; one child failed to meet any criteria. ˙ O2peak and V ˙ O2supraAlthough there were no significant differences between V maximal, 5 children did show improvement during supramaximal testing.

Limitations. These results apply to children who have spina bifida and are at least community ambulatory.

Conclusions. The V˙ O2peak measured during an incremental treadmill test seems ˙ O2max in children who have spina bifida and are ambulatory, to reflect the true V validating the use of a treadmill test for these children. When confirmation of maximal effort is needed, the addition of supramaximal testing of children with disability is an easy and well-tolerated method.

J.F. de Groot, PT, MSc, is Researcher, Research Group Lifestyle and Health, University of Applied Sciences, Utrecht, the Netherlands, and Department of Pediatric Physical Therapy and Exercise Physiology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Room kb.02.056.0, PO Box 85090, 3508 AB Utrecht, the Netherlands. Address all correspondence to Mrs de Groot at: [email protected]. T. Takken, PhD, is Medical Physiologist, Department of Pediatric Physical Therapy and Exercise Physiology, Wilhelmina Children’s Hospital, University Medical Center Utrecht. S. de Graaff, MSc, was a medical student, Faculty of Medicine, University Medical Center Utrecht, at the time of the study. R.H.J.M. Gooskens, is Professor and Child Neurologist, Department of Pediatric Neurology, Wilhelmina Children’s Hospital, University Medical Center Utrecht. P.J.M. Helders, PT, PhD, PCS, is Professor, Department of Pediatric Physical Therapy and Exercise Physiology, Wilhelmina Children’s Hospital, University Medical Center Utrecht. L. Vanhees is Professor, Research Group Lifestyle and Health, University of Applied Sciences, Utrecht, the Netherlands, and Department of Rehabilitation Sciences, Catholic University, Leuven, Belgium. [de Groot JF, Takken T, de Graaff S, et al. Treadmill testing of children who have spina bifida and are ambulatory: does peak oxygen uptake reflect maximum oxygen uptake? Phys Ther. 2009;89; 679 – 687.] © 2009 American Physical Therapy Association Post a Rapid Response or find The Bottom Line: www.ptjournal.org

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Exercise Testing of Children With Spina Bifida

B

ecause of advances in medical science, many children with chronic diseases now have longer and healthier lives. This change requires a different approach in the medical management of these patients from childhood through adolescence and into adulthood. An approach that focuses not only on the pathological aspects but also on the (preventable) medical, functional, and social consequences of the disease and lifestyle issues is needed. As a result of this shift, exercise testing and training in children with chronic diseases, such as spina bifida, have emerged as areas of interest in the field of pediatric exercise physiology.1

Spina bifida is the most frequent congenital deformity of the neural tube, with an incidence of 0.4 to 1.0 per 1,000 births.2– 4 Depending on both the type and the level of the spina bifida lesion, patients can experience a variety of deficits in cognition, motor function, sensory function, and bowel and bladder function.5 Besides medical classification according to type, lesion level, and presence of hydrocephalus, children are functionally classified as having “normal ambulation” or “community ambulation” by use of the adapted Hoffer classification.6,7 Appendix 1 provides descriptions of ambulation levels. About 20% of lesions occur at the sacral level, enabling most children

Available With This Article at www.ptjournal.org • The Bottom Line clinical summary • The Bottom Line Podcast • Audio Abstracts Podcast This article was published ahead of print on May 29, 2009, at www.ptjournal.org.

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so affected to have community or normal ambulation. Despite high levels of functioning, these patients still experience difficulties in performing both dynamic motor skills and activities of daily living.8 This situation could be an important factor in inducing a cycle of less ability resulting in less activity, further reducing physical fitness and ambulation. Studies have indeed shown children and young adults with spina bifida to be less active and to have lower levels of physical fitness than their peers who are healthy.9 –12 In exercise testing, maximum oxy˙ O2max [Appendix 2]) gen uptake (V is considered to be the single best indicator of aerobic exercise capacity, which often is referred to as “aerobic fitness.”13 Gas exchange analysis during an incremental ergometry test to the point of volitional termination because of exhaustion is considered the gold standard for measur˙ O2max.14 There has been much ing V debate about peak oxygen uptake ˙ O2peak) [Appendix 2]) versus (V ˙ O2˙max. Whereas V ˙ O2peak is the V ˙ ˙ O2 highest level of oxygen˙ uptake (V [Appendix 2]) attained during a sin-˙ ˙ O2max is considered to be gle test, V ˙ the maximum possible attainable level of oxygen utilization by both the cardiorespiratory and the neuro˙ O2 muscular systems, resulting in a V plateau at the end of testing despite˙ an increase in workload.15,16 A common method of exercise testing in children is incremental cycle or treadmill testing.1 In patients with spinal cord disease or dysfunction (including spinal cord injury and spina bifida)17 and in patients with spina bifida,18 arm ergometry has been used. An advantage of using arm ergometry with this population could be that the muscles tested are less involved in the disease process. In this way, the outcomes of the test might more closely reflect cardiorespiratory limitations in ex-

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ercise testing. On the other hand, upper-extremity ergometry has been ˙ O2peak known to result in lower V ˙ values because of the smaller muscle 19 mass involved in testing. At the same time, for this group of children, ambulation is the main mode of transportation. In this case, it is recommended that a treadmill be used for maximum exercise testing because of its specificity.20 –22 To evaluate whether an exercise test in children yields “true” maximum values, Bar-Or and Rowland1 described guidelines regarding heart rate (HR [Appendix 2]), respiratory exchange ratio (RER [Appendix 2]), ˙ O2 plateau in and the presence of a V ˙ Because the final minutes of testing. the presence of a plateau in both adult and pediatric exercise testing has been disputed,13 supramaximal protocols, such as the one-session protocol described by Rossiter et al,16 have been used to evaluate whether the added step can yield ˙ O2 values. When the suprahigher V maximal step does not result in in˙ O2, V ˙ O2peak is considered creased V ˙ ˙ O2max. to be a valid indicator of V ˙ In an earlier study,23 we reported a ˙ O2peak values when a reduction in V ˙ test was used for treadmill exercise children who had spina bifida and were ambulatory. The lower ˙ O2peak values in that study seemed V ˙ attributable to reduced muscle to be mass, deconditioning, and possible ventilatory limitations. In addition, both low peak HR (HRpeak) and low peak RER (RERpeak) in both our study and the literature11,23,24 raised questions regarding the true maxi˙ O2peak values obmal character of V ˙ of testing. tained with this mode Although earlier studies of treadmill exercise testing of children who were healthy showed that it is possi˙ O2peak in chilble to validly test V ˙ 25–29 no redren who are healthy, search has been done on the validity July 2009

Exercise Testing of Children With Spina Bifida ˙ O2peak testing in children who of V ˙ have spina bifida and are ambulatory. The purpose of this study, therefore, ˙ O2peak was to determine whether V ˙ measured during a graded treadmill ˙ O2max in chilexercise test reflects V ˙ dren who have spina bifida and are ambulatory.

Table 1. Level of Lesion and Functional Ambulation Level in Groups of Children No. (%) of Children With Community Ambulation (nⴝ10)

L3–L4

2 (10)

0 (0)

2 (20)

L4–L5

7 (35)

1 (10)

6 (60)

L5–S1

6 (30)

4 (40)

2 (20)

S2 and below

1 (5)

1 (10)

0 (0)

No motor loss

4 (20)

4 (40)

0 (0)

13 (65)

9 (90)

3 (30)

418 (95)

473 (45.5)

357 (100)b

Parameter Level of lesion

Method Participants This study was part of a larger study regarding exercise and functional capacity testing of children who were diagnosed with spina bifida (the Utrecht Spina Bifida And Graded Exercise [USAGE] study) and were ambulatory. Study procedures took place at the Department of Pediatric Physical Therapy and Exercise Physiology, Wilhelmina Children’s Hospital, University Medical Center Utrecht, Utrecht, the Netherlands, in 2007 and 2008.

All (nⴝ20)

With Normal Ambulation (nⴝ10)

a

6MWT Walking ⬎400 m Distance walked, m, X (SD) Anthropometric measurements, X (SD) Age

10.3 (4.9)

9.9 (3.2)

11.1 (4.1)

Height, m

1.36 (0.21)

1.38 (0.19)

1.32 (0.24)

Weight, kg

37.1 (18.7)

35.9 (15.0)

38.2 (21.5)

BMI, kg/m2

18.9 (3.9)

17.8 (2.8)

20.1 (4.7)

a

6MWT⫽Six-Minute Walk Test, BMI⫽body mass index. P⬍.05 for difference between children with normal ambulation and children with community ambulation. b

Children were included when they had at least community ambulation, were able to follow instructions regarding testing, and were between 6 and 18 years of age. Parents and children signed informed consent statements before testing. Exclusion criteria were medical events that might interfere with the outcomes of the testing or medical status that did not allow maximum exercise testing. The power calculation was performed with the assumption of an alpha value of .05 and a power of 80%. On the basis of population mean and standard deviation values of 33.14 and 7.6, respectively, for ˙ O2peak/kg/min23 and with the asV ˙ sumption of a correlation of .9, a sample size of 18 children was determined to be sufficient to detect differences during the supramaximal step of testing at 110% of the maximum achieved speed.30 The study population consisted of 20 children who had spina bifida and were ambulatory (9 boys and 11 girls). The level of the lesion (classiJuly 2009

fied according to the guidelines of the American Spinal Injury Association31), the ambulation level, SixMinute Walk Test (6MWT) results, age, and anthropometric measurements are shown in Table 1. Demographics Data concerning medical history were obtained from medical records. These data included the type of spina bifida, the level of the lesion, the ambulation level, age, and sex. Body Mass Index The body mass index was calculated as weight (kilograms) divided by height squared (meters squared). This index has proven to be a reliable and valid tool for estimating children’s nutritional status (such as whether they are overweight or underweight).32,33 Weight was measured with an electronic scale. Height was measured with a wallmounted centimeter scale.

Peak Oxygen Uptake and Supramaximal Oxygen Uptake In previous studies, treadmill proto˙ O2peak in cols were used to test V ˙ children with disability,11,34,35 including children with spina bifida.11,23 In the present study, ˙ O2peak was measured with a V ˙ graded treadmill (EnMill*) test because all children should have been able to perform this test and because reference values are available for both young children and adolescents. To accommodate children with different ambulatory abilities, we used 2 progressive exercise test protocols. Children ambulating less than 400 m during the 6MWT were tested with a starting speed of 2 km/h, which was gradually increased by 0.25 km/h every minute, with a set grade of 2%. Children ambulating farther than 400 m during * Enraf, Delft Techpark 39, 2628 XJ Delft, the Netherlands.

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Exercise Testing of Children With Spina Bifida Table 2. Rowland Criteria Used to Evaluate Peak Oxygen Uptake in Children Who Are Healthy Criteria Subjective

Description a

Unsteady walking, running, or biking Sweating Facial flushing Clear unwillingness to continue despite encouragement

Objective

Heart rate of ⬎95% (210 ⫺ age) Respiratory exchange ratio of ⬎1.00 Oxygen uptake plateau in last minute

a

Signs of intense effort.

the 6MWT were tested with a starting speed of 3 km/h, which was increased by 0.50 km/h every minute, with a set grade of 2%. The cutoff point of 400 m was chosen on the basis of earlier testing in our laboratory.21,22 The children were allowed to use handrails to maintain balance. The protocols were continued until the children stopped because of exhaustion, despite verbal encouragement from the test leader. After a resting period of 4 minutes, the children were tested for a maximum of 3 minutes at 110% of their maximum achieved speed. This type of supramaximal testing for adults who were healthy was described by Rossiter et al.16 During the incremental exercise testing, physiologic responses, including breath-by-breath gas analysis, were measured with an HR monitor (Polar Accurex†) and a calibrated mobile gas analysis system (Cortex Metamax B3‡). The Cortex Metamax is a valid and reliable system for measuring gas exchange parameters during exercise.36,37 Ambulatory Ability Ambulatory ability was measured during the 6MWT. The test was per†

Polar-Nederland BV, Antennestraat 46, 1322 AS Almere, the Netherlands. ‡ Cortex Medical GmbH, Nonnenstrasse 39, Leipzig, Germany.

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formed on a 20-m track in a straight corridor. The children were instructed to cover the greatest possible distance in 6 minutes at a selfselected walking speed. The test and encouragements during the test were in accordance with the guidelines of the American Thoracic Society.38 The walking distance in the 6MWT was recorded in meters. This test was performed before the treadmill test and was followed by a 15minute recovery period. Data Analysis V˙ O2peak. Both peak and supra˙ maximal exercise parameters were calculated as average values during the last 30 seconds of the exercise ˙ O2 was calculated as test. Normalized V ˙ O2peak/kg or V ˙ O˙2supramaximal/kg V ˙ and was expressed˙as milliliters per kilogram per minute. Two-tailed t tests were used to test differences between children with community ambulation and children with normal ambulation after testing for normal distribution and equality of means. The significance level was set at a P value of less than .05. To evaluate the validity of maximum exercise testing in children with spina bifida, we analyzed the data with the following methods. Rowland criteria. Rowland established criteria for maximum exercise testing in children who are healthy.39 These criteria are subdi-

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vided into subjective (ie, qualitative) and objective (ie, quantitative) criteria; a child has to meet the subjective criteria and at least 2 of the objective criteria for the test to be considered of maximal effort and character ˙ O2 plateau was deter(Tab. 2). The V mined from the ˙difference between ˙ O2peak and V ˙ O2 in the normalized V last 30 seconds˙of the minute˙ before the last minute. When the difference was 2.1 mL/kg/min or less, the child was considered to have reached a plateau.40 Supramaximal protocol. Twotailed paired t tests were used to test differences between normalized ˙ O2peak and V ˙ O2supramaximal after V ˙ ˙ distribution and testing for normal equality of means. The significance level was set at a P value of less than .05. Statistical analyses were performed with SPSS for Windows (version 15.0).§ Clinically relevant differ˙ O2peak ences between normalized V ˙ ˙ O2supramaximal were defined and V ˙ as those for a plateau at greater than 2.1 mL/kg/min, as stated above.

Results Exercise Testing Twenty children completed the graded treadmill exercise test followed by a 3-minute supramaximal test. The supramaximal protocol was well tolerated. Only one child (subject 17) was not able to complete the full 3 minutes of supramaximal testing and had to stop after 2 minutes. ˙ O2peak, HRpeak, peak ventilaThe V ˙ carbon dioxide exhaled, tion, peak and RERpeak are shown in Table 3 ˙ O2peak (see also Appendix 2). The V ˙ ˙ O2peak/kg values averaged and V ˙ 1.23 L/min (SD⫽0.6) and 34.1 mL/ kg/min (SD⫽8.3), respectively. Rowland Criteria All children showed signs of the subjective criteria. Sixty-five percent of §

SPSS Inc, 233 S Wacker Dr, Chicago, IL 60606.

July 2009

Exercise Testing of Children With Spina Bifida ˙ O2 plateau the children reached a V during the last minute of ˙exercise testing. The criteria for HRpeak were met by 65% of the children, whereas 80% reached an RERpeak of greater than 1.00. Seven children met all 3 criteria, 8 children met 2 criteria, and 4 children met one criterion; one child failed to meet any criteria (Tabs. 4 and 5). Seventy-five percent of the children met at least 2 of the 3 criteria. Supramaximal Protocol No significant differences were seen between the regular test and the su˙ O2peak verpramaximal protocol (V ˙ versus ˙ O2supramaximal: 34.1 sus V ˙ 34.8 mL/kg/min; P⫽.274). Individual differences are shown in Table 5. ˙ O2peak and V ˙ O2supraAn example of V ˙ the maximal testing ˙is shown in Figure. As indicated by the individual values, 5 children showed clinically relevant differences between normalized ˙ O2peak and V ˙ O2supramaximal. The V ˙ O˙2 increased by˙ more than 2.1 mL/ V ˙ kg/min during supramaximal testing ˙ O2 did not in these children. The V ˙ increase during supramaximal testing in the other children; 10 children were not even able to reach previous peak values despite an increase in speed. Of the 5 children who did not meet at least 2 of the 3 objective criteria described by Rowland,39 2 continued to improve during supramaximal testing. The child who failed to meet any criteria (subject 1) did not show ˙ O2 during the an improvement in V ˙ added step. Of the children who ˙ O2 during showed an increase in V ˙ supramaximal testing, one child had met all 3 criteria (subject 8), 3 children had met 2 of the 3 criteria (subjects 4, 7, and 16), and one child (subject 3) had met only one of the criteria for maximum exercise testing. Three children did not meet the HRpeak criteria (subjects 3, 7, and July 2009

Table 3. Exercise Testing of 20 Children With Spina Bifida X (SD) for Children All

With Normal Ambulation

With Community Ambulation

V˙ O2peak (L/min)

1.23 (0.6)

1.43 (0.6)

1.02 (0.5)

V˙ O2peak/kg (mL/kg/min)

34.1 (8.3)

39.4 (5.7)

28.7 (7.0)b

183.8 (19.9)

184.7 (20.4)

182.3 (20.3)

Parametera

HRpeak (bpm) RERpeak (V˙ CO2/V˙ O2)

1.07 (0.1)

1.09 (0.1)

1.05 (0.1)

Peak ventilation (L/min)

45.1 (22.2)

51.4 (20.9)

38.9 (22.6)

˙ 2 (L/min) Peak Vco

1.34 (0.71)

1.57 (0.7)

1.11 (0.7)

9.0 (4.0)

10.4 (2.9)

9.3 (5.0)

Duration of testing (min)

V˙ O2peak⫽peak oxygen uptake, HRpeak⫽peak heart rate, RERpeak⫽peak respiratory exchange ratio, V˙ CO2⫽carbon dioxide exhaled. P⬍.05 for difference between children with normal ambulation and children with community ambulation. a

b

16), one child reached an RERpeak of less than 1.00 (subject 4), and one ˙ O2 plateau in child did not reach a V ˙ testing. the last minute of exercise Of the children who reached a low HRpeak, 42% showed a higher ˙ O2supramaximal value. Of the chilV ˙ who had a low RERpeak, only dren 25% still improved during supramaximal testing. Despite the fact that fewer children with community ambulation reached an RERpeak of ˙ O2 plateau, greater than 1.00 or a V ˙ in sigthis difference did not result ˙ nificant differences in VO2peak and ˙ O2supramaximal values ˙ between V the˙ groups. Of the 7 children who ˙ O2 plateau, only one did not reach a V ˙ the added step. still improved during Furthermore, 3 children who still improved had community ambulation, and 2 had normal ambulation. Dur-

ing the last minute of supramaximal ˙ O2 testing, 4 of 5 children reached a V ˙ plateau.

Discussion The purpose of the present study ˙ O2peak was to determine whether V ˙ measured during a graded treadmill ˙ exercise test reflects VO2max in chil˙ dren who have spina bifida and are ambulatory. Rowland Criteria In the present study, the percentage of children meeting one of the Rowland criteria39 was much higher than that in our earlier data. Seventy-five percent of the children in the present study met at least 2 of the 3 criteria, and only one child failed to meet any criteria. These findings are much more in line with the findings

Table 4. Rowland Criteria During Exercise Testing No. (%) of Children All

With Normal Ambulation

With Community Ambulation

Signs of subjective criteria

20 (100)

10 (100)

10 (100)

HRpeak of ⬎95% (210 ⫺ age)

13 (65)

7 (70)

6 (60)

Parametera

a

RERpeak of ⬎1.00

16 (80)

9 (90)

7 (70)

V˙ O2 plateau

13 (65)

7 (70)

6 (60)

˙ 2⫽oxygen uptake. HRpeak⫽peak heart rate (bpm), RERpeak⫽peak respiratory exchange ratio, Vo

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Exercise Testing of Children With Spina Bifida Table 5. Individual Differences in Normalized Peak Oxygen Uptake (V˙ O2peak) and Supramaximal Oxygen Uptake (V˙ O2supramaximal) and Rowland Criteriaa

Ambulation Status

˙ O2supramaximal/kg) (V ˙ O2peak/kg) ⴚ (V (mL/kg/min)

1

CA

⫺0.49

143

2

NA

⫺2.92

3

NA

4

CA

Subject No.

HRpeak (bpm) b

RERpeak

˙ O2 ˙ O2peak–V V in Last Minute (mL/kg/min)

No. of Rowland Criteria Met (of 3)

0.97b

3.11b

0

201

1.18

1.02

3

8.21c

159d

1.17

5.62d

1

3.09c

189

0.92d

1.98

2

5

NA

1.79

177

6

NA

0.04

192 c

140 200

7

NA

2.27

8

CA

3.65c

d

d

1.04

1.55

2

1.03

0.61

3

1.02

1.82

1

1.06

1.61

3

9

NA

⫺0.18

202

1.05

0.38

3

10

CA

⫺0.18

188d

1.19

1.1

2

11

NA

⫺1.86

195

1.14

2.29d

2

12

CA

0.85

210

1.29

13

CA

⫺3.28

192

1.00

2.28

14

CA

⫺1.46

191

1.27

1.54

15

CA

1.32

159d

1.00

3.68d

1

16

CA

4.88c

165d

1.02

0.55

2

17

CA

⫺1.06

185

0.84d

4.99d

1

18

NA

1.79

198

1.30

2.35d

2

19

NA

⫺1.30

195

0.92

20

NA

⫺1.11

188

1.06

⫺0.32

d

d

3 2 3

1.32

2

0.27

3

a

HRpeak⫽peak heart rate, RERpeak⫽peak respiratory exchange ratio, CA⫽community ambulation, NA⫽normal ambulation. Did not reach HRpeak of ⬎95% (210 ⫺ age), RERpeak of ⬎1.00, and V˙ O2plateau. Increased by more than 2.1 mL/kg/min in the supramaximal test. d Did not reach HRpeak of ⬎95% (210 ⫺ age), RERpeak of ⬎1.00, or V˙ O2plateau. b c

of earlier research with children who were healthy, which showed ˙ O2peak in children is a valid that V ˙ of V ˙ O2max.26 Gulmans et indicator al26 tested 158 ˙children who were healthy and 12 to 18 years of age; 100% met the criteria for maximum exercise testing. The criteria used in that study were different from those used in the present study and included invasive testing but were still based on the guidelines described by Rowland.1

Figure. Example of peak oxygen uptake (V˙ O2peak) and supramaximal oxygen uptake (V˙ O2supramaximal) testing.

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In a Danish study with a large sample of subjects,28 84% of the subjects met at least 2 of the 3 objective criteria described by Rowland,39 a finding similar to that in the present

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Exercise Testing of Children With Spina Bifida study. The presence of a plateau in pediatric exercise testing has been disputed in the literature. Even though reaching a plateau often is considered to be the true criterion for maximum exercise testing, a literature review revealed that 21% to 95% of children, with an average of 55% of children who were healthy, reached a plateau during exercise testing.13 In the present study, 70% of children reached a plateau; interestingly, however, reaching a plateau was not predictive of improvement during supramaximal testing. Four of 5 children reaching a higher ˙ O2supramaximal value met the criV ˙ O2 plateau during initial teria for a V ˙ 1 of 7 children who testing, but only ˙ O2 plateau imdid not reach a V ˙ step. proved during the added Supramaximal Protocol Besides the Rowland criteria,39 we used a protocol described by Rossiter et al16 to determine whether ˙ O2max had been reached the true V ˙ during the graded treadmill exercise test. We did this by adding an extra step of testing at 110% of the maximum achieved speed. We found no significant differences between ˙ O2peak and V ˙ O2supramaximal in V ˙ ˙ children with either normal ambulation or community ambulation. These results are in line with those of other studies in which supramaximal protocols were used. Rowland15 was ˙ O2 unable to elicit an increase in V during supramaximal testing in 9˙ children who were healthy. Rossiter et al16 concluded that when subjects seem to give their maximal effort (Rowland subjective criteria), ˙ O2peak most likely reflects V ˙ O2max. V ˙ 5 At ˙the individual level, though, children still continued to improve during supramaximal testing in the present study. Eighty percent of children reached a plateau during supramaximal testing, implying a maximal ˙ O2 during the measurement of V ˙ added step. Besides meeting fewer than 2 of the 3 criteria, a low July 2009

HRpeak, in particular, seems to be an indication that an individual may not ˙ O2max. have reached the true V ˙ The present study differed from our earlier studies in 2 ways.23,24 First, the population tested in the present study included more subjects with community ambulation and children with a lesion at a higher level (and therefore more muscular deficits). Despite these differences, the HRpeak and RERpeak reached in the present study were higher than those achieved in our previous studies— but without reaching a higher ˙ O2peak value. A secondary analysis V ˙ revealed no correlation between HRpeak and the level of the lesion, in contrast to the results of a study by Agre et al.11 This difference could be explained partly by the fact that children with a lesion at a higher level performed the treadmill test in a wheelchair; this mode of exercise was less strenuous than walking. In addition, a discontinuous and lessprogressive testing protocol was used. Still, compared with the results of studies involving children who were healthy, HRpeak was much lower in our population (183.8 versus 196 –19928 or 199 –20041). This finding likely was attributable to the ˙ O2peak in children who fact that V ˙ is determined not by are ambulatory cardiac limitations but rather by deconditioning, muscular deficiencies, or both, and possible ventilatory limitations.23 Second, we defined “ambulatory ability” in a different way in the present study; the decision about which treadmill protocol to use was based on actual performance during the 6MWT instead of functional classification. This change in protocol improved peak outcomes for our population. Limitations of the Study In the context of the USAGE study, only children with spina bifida and

community or normal ambulation were included. In future studies, it would be interesting to develop exercise testing for children who are considered to have “household ambulation” (Appendix 1) as well. Questions could be raised about a possible practice effect and familiarization with the test procedures for both the treadmill test and the 6MWT. At present, we are examining the reproducibility of exercise testing in children who have spina bifida and are ambulatory. A question could be raised about the frequent use of medications in children with spina bifida. It is unclear how such medications might interfere ˙ O2, utilization and transport with V ˙ the body, and central and systems in peripheral fatigue. In the present study, we monitored medication use during exercise testing.

Conclusion A graded treadmill exercise test is an appropriate method for measuring ˙ O2peak in children with spina bifida V and˙ normal or community ambulation. For the selection of a treadmill protocol, it is important to use actual performance and not functional classification as a decisive factor. Levels of HRpeak (not RERpeak) that are lower than predicted may be an indication of submaximal effort. When the true character of maximum exercise testing of children who have spina bifida and are ambulatory is in doubt, a supramaximal step of testing at 110% of the maximum achieved speed is an easy and welltolerated method for the confirmation and further interpretation of maximum exercise testing. Mrs de Groot, Dr Takken, Dr Helders, and Dr Vanhees provided concept/idea/research design, writing, and fund procurement. Mrs de Groot, Dr Takken, and Ms de Graaff provided data collection. Mrs de Groot, Dr Takken, Ms de Graaff, and Dr Vanhees provided data analysis and project management. Dr Gooskens provided institutional liaisons. Mrs de Groot and Dr Gooskens

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Exercise Testing of Children With Spina Bifida provided participants. Dr Takken and Dr Helders provided facilities/equipment. Dr Takken, Ms de Graaff, Dr Gooskens, Dr Helders, and Dr Vanhees provided consultation (including review of manuscript before submission). The authors thank the children and the parents for their participation in the research. They also thank the students who participated as research assistants. All study procedures were approved by the Utrecht University Medical Ethics Committee. The USAGE study is funded by the Dutch Royal Society for Physiotherapy, the Wilhelmina Children’s Hospital Research Fund, and Stichting BIO-Kinderrevalidatie. This article was received October 17, 2008, and was accepted March 25, 2009. DOI: 10.2522/ptj.20080328

References 1 Bar-Or O, Rowland TW. Pediatric Exercise Medicine: From Physiologic Principles to Healthcare Application. Champaign, IL: Human Kinetics; 2004. 2 RIVM. http://www.rivm.nl/vtv/object_ document/o1762n18478.html. 2006. 3 Shaer CM, Chescheir N, Schulkin J. Myelomeningocele: a review of the epidemiology, genetics, risk factors for conception, prenatal diagnosis, and prognosis for affected individuals. Obstet Gynecol Surv. 2007;62: 471– 479. 4 De Wals P, Tairou F, Van Allen MI, et al. Spina bifida before and after folic acid fortification in Canada. Birth Defects Res A Clin Mol Teratol. 2008;82:622– 626. 5 Ryan DK, Ploski C, Emans JB. Myelodysplasia: the musculoskeletal problem— habilitation from infancy to adulthood. Phys Ther. 1991;71:67–78. 6 Hoffer M, Feiwell E, Perry J, Bonnet C. Functional ambulation in patients with myelomeningocele. J Bone Joint Surg Am. 1973;55:137–148. 7 Schoenmakers MA, Uiterwaal CS, Gulmans VA, et al. Determinants of functional independence and quality of life in children with spina bifida. Clin Rehabil. 2005;19: 677– 685. 8 Schoenmakers MA, Gulmans VA, Gooskens RH, Helders PJ. Spina bifida at the sacral level: more than minor gait disturbances. Clin Rehabil. 2004;18:178 –185. 9 Steele CA, Kalnins IV, Jutai JW, et al. Lifestyle health behaviours of 11–16 year old youth with physical disabilities. Health Education Research. 1996;11:173–186. 10 van den Berg-Emons HJ, Bussmann JB, Meyerink HJ, et al. Body fat, fitness and level of everyday physical activity in adolescents and young adults with meningomyelocele. J Rehabil Med. 2003;35: 271–275.

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11 Agre JC, Findley TW, McNally MC, et al. Physical activity capacity in children with myelomeningocele. Arch Phys Med Rehabil. 1987;68:372–377. 12 Buffart LM, Roebroeck ME, Rol M, et al. Triad of physical activity, aerobic fitness and obesity in adolescents and young adults with myelomeningocele. J Rehabil Med. 2008;40:672– 677. 13 Vanhees L, Lefevre J, Phillipaers R, et al. How to assess physical activity? How to assess physical fitness? Eur J Cardiovasc Prev Rehabil. 2005;12:102–114. 14 Shephard RJ, Allen C, Benade AJ, et al. The maximum oxygen uptake: an international reference standard of cardiorespiratory fitness. Bull WHO. 1968;38:757–764. ˙ O2 reflect 15 Rowland TW. Does peak V ˙ supra˙ O2max in children? Evidence from V maximal testing. Med Sci Sports Exerc. 1993;25:689 – 693. 16 Rossiter HB, Kowalchuk JM, Whipp BJ. A test to establish maximum O2 uptake despite no plateau in the O2 uptake response to ramp incremental exercise. J Appl Physiol. 2006;100:764 –770. 17 Widman LM, Abresch RT, Styne DM, McDonald CM. Aerobic fitness and upper extremity strength in patients aged 11 to 21 years with spinal cord dysfunction as compared to ideal weight and overweight controls. J Spinal Cord Med. 2007;30(suppl 1):S88 –S96. 18 Bruinings AL, van den Berg-Emons HJ, Buffart LM, et al. Energy cost and physical strain of daily activities in adolescents and young adults with myelomeningocele. Dev Med Child Neurol. 2007;49:672– 677. 19 Franklin BA. Exercise testing, training and arm ergometry. Sports Med. 1985;2: 100 –119. 20 Stromme SB, Ingler F, Meen HD. Assessment of maximal aerobic power in specifically trained athletes. J Appl Physiol. 1977;42:833– 837. 21 Åstrand P-O, Rodahl K, Dahl HA, Stromme SB. Textbook of Work Physiology. New York, NY: McGraw-Hill; 2003. 22 Bar-Or O, Zwiren LD. Maximal oxygen consumption test during arm exercise: reliability and validity. J Appl Physiol. 1975; 38:424 – 426. 23 de Groot JF, Takken T, Schoenmakers MA, et al. Interpretation of maximal exercise testing and the relationship with ambulation parameters in ambulation children with spina bifida. Eur J Appl Physiol. 2008;104:657– 665. 24 Schoenmakers MA, de Groot JF, Gorter JW, et al. Muscle strength, aerobic capacity and physical activity in independent ambulating children with lumbosacral spina bifida. Disabil Rehabil. 2009;31: 259 –266. 25 Sherman MS, Kaplan JM, Effgen S, et al. Pulmonary dysfunction and reduced exercise capacity in patients with myelomeningocele. J Pediatr. 1997;131:413– 418. 26 Gulmans VA, de Meer K, Binkhorst RA, et al. Reference values for maximum work capacity in relation to body composition in healthy Dutch children. Eur Respir J. 1997;10:94 –97.

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27 Reybrouck T, Deroost F, Van der Hauwaert LG. Evaluation of breath-by-breath measurement of respiratory gas exchange in pediatric exercise testing. Chest. 1992;102:147–152. 28 Eiberg S, Hasselstrom H, Gronfeldt V, et al. Maximum oxygen uptake and objectively measured physical activity in Danish children 6 –7 years of age: the Copenhagen school child intervention study. Br J Sports Med. 2005;39:725–730. 29 Armstrong N, Welsman J, Winsley R. Is ˙ O2 a maximal index of children’s peakV aerobic ˙fitness? Int J Sports Med. 1996; 17:356 –359. 30 Portney LG, Watkins MP. Foundations of Clinical Research: Applications to Practice. 3rd ed. Upper Saddle River, NJ: Pearson Prentice Hall; 2008. 31 Maynard FM, Bracken MB, Creasey G, et al. International standards for neurological and functional classification of spinal cord injury. American Spinal Injury Association. Spinal Cord. 1997;35:266 –274. 32 Mei Z, Grummer-Strawn LM, Pietrobelli A, et al. Validity of body mass index compared with other body-composition screening indexes for the assessment of body fatness in children and adolescents. Am J Clin Nutr. 2002;75:978 –985. 33 Dietz WH, Robinson TN. Use of the body mass index (BMI) as a measure of overweight in children and adolescents. J Pediatr. 1998;132:191–193. 34 Hoofwijk M, Unnithan VB, Bar-Or O. Maximal treadmill performance of children with cerebral palsy. Pediatr Exerc Sci. 1995;7:305–313. 35 Verschuren O, Takken T, Ketelaar M, et al. Reliability and validity of data for 2 newly developed shuttle run tests in children with cerebral palsy. Phys Ther. 2006;86: 1107–1117. 36 Brehm MA, Harlaar J, Groepenhof H. Validation of the portable VmaxST system for oxygen-uptake measurement. Gait Posture. 2004;20:67–73. 37 Medbo JI, Mamen A, Welde B, von Heimburg E, Stokke R. Examination of the Metamax I and II oxygen analysers during exercise studies in the laboratory. Scan J Clin Lab Invest. 2002;62:585–598. 38 ATS Committee on Proficiency Standards for Clinical Pulmonary Function Laboratories. ATS statement: guidelines for the sixminute walk test. Am J Respir Crit Care Med. 2002;166:111–117. 39 Rowland TW. Aerobic exercise testing protocols. In: Rowland TW, ed. Pediatric Laboratory Exercise Testing. Champaign, IL: Human Kinetics; 1993:19 – 42. 40 Rowland TW, Cunningham LN. Oxygen uptake plateau during maximal treadmill testing in children. Chest. 1992;101: 485– 489. 41 LeMura LM, Von Duvillard SP, Cohen SL, et al. Treadmill and cycle ergometry testing in 5- to 6-year-old children. Eur J Appl Physiol. 2001;85:472– 478.

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Exercise Testing of Children With Spina Bifida Appendix 1. Adapted Hoffer Classification6,7 Level of Ambulation

Description

Normal

Independent and unrestricted ambulation without use of assistive devices

Community

Independent outdoor ambulation with or without use of braces or assistive devices; use of wheelchair for longer distances

Household

Use of braces or assistive devices for indoor ambulation; use of wheelchair for outdoor locomotion

Nonfunctional

Walking only in therapeutic situations

None

Wheelchair dependent

Appendix 2. Terminologya Term

Oxygen uptake (L/min); determined from cardiac output (heart rate ⫻ stroke volume) and arterial–mixed-venous oxygen content differences (⫽Fick formula)

V˙ O2peak ˙ V˙ O2max ˙

Highest level of oxygen uptake (V˙ O2) attained during a single test without necessity of flattening of the V˙ O2 curve ˙ ˙ Maximum possible attainable level of oxygen utilization by both cardiorespiratory and neuromuscular systems, characterized by flattening of the V˙ O2 curve despite an increase in workload; often determined in more than one test session; in people who ˙ and V˙ O max are interchangeable are healthy, V˙ O2peak 2 ˙ ˙ Carbon dioxide exhaled (L/min)

V˙ CO2 ˙ RER

a

Explanation

V˙ O2 ˙

Respiratory exchange ratio; calculated as V˙ CO2/V˙ O2 ˙ ˙

˙ VE

Minute ventilation (L/min)

HR

Heart rate (bpm)

Based on: Wasserman K, et al. Principles of Exercise Testing and Interpretation. 4th ed. Philadelphia, PA: Lippincott Williams & Wilkins; 2005.

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Case Report Quantitative Measurement of Poststroke Spasticity and Response to Treatment With Botulinum Toxin: A 2-Patient Case Report Elizabeth Cousins, Anthony B. Ward, Christine Roffe, Lesley D. Rimington, Anand D. Pandyan E. Cousins, BSc (Hons), is a PhD student, Institute for Life Course Studies, Keele University, Keele, Staffordshire, United Kingdom. A.B. Ward, BSc, FRCP(Ed), FRCP, is Director, North Staffordshire Rehabilitation Centre, and Professor of Rehabilitation Medicine, University Hospital of North Staffordshire, Stoke on Trent, Staffordshire, United Kingdom. C. Roffe, MD, FRCP, is Stroke Physician, University Hospital of North Staffordshire, Stoke-on-Trent, Staffordshire, United Kingdom; Clinical Lead, Midlands Stroke Research Network; and Reader, Institute for Life Course Studies, Keele University. L.D. Rimington, PhD, is Lecturer, Institute for Life Course Studies, Keele University. A.D. Pandyan, PhD (BioEng), is Senior Lecturer, Institute for Life Course Studies, Keele University, Keele, Staffordshire, United Kingdom ST5 5BG. Address all correspondence to Dr Pandyan at: [email protected]. [Cousins E, Ward AB, Roffe C, et al. Quantitative measurement of poststroke spasticity and response to treatment with botulinum toxin: a 2-patient case report. Phys Ther. 2009;89:688 – 697.]

Background and Purpose. Spasticity (hypertonicity) is a frequent problem that can develop after stroke and can lead to a number of secondary complications, such as contractures and pain. Consequently, many rehabilitation resources are used in treating the condition and its secondary complications. At present, the clinical assessment of spasticity incorporates descriptive scales of resistance to passive movement, but the use of a neurophysiological measure of muscle activity levels has been advocated. This case report focuses on the diagnosis of spasticity through the use of a neurophysiological measure.

Case Descriptions. Two individuals who required botulinum toxin treatment for poststroke spasticity were assessed over a course of 20 weeks with both clinical (Modified Ashworth Scale) and neurophysiological (surface electromyography recording of levels of muscle activity) measures of spasticity. Additionally, arm function, arm movement, and pain were measured. The individuals’ responses to treatment with botulinum toxin and overall recovery after stroke are described.

Outcomes. There were discrepancies between the clinical and the neurophysiological measures of spasticity. The clinical measure of spasticity was not effective in consistently identifying the presence of spasticity and, therefore, also was ineffective in documenting the individuals’ responses to treatment. The neurophysiological measure was able to identify when muscle activity levels had been reduced, but a reduction in muscle activity levels did not always correspond with a reduction in Modified Ashworth Scale scores.

Discussion. The accurate identification of spasticity is important not only for assessment but also for the selection of appropriate treatments after stroke.

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troke is a leading cause of adult disability, with a third of people who have survived acute stroke being left with moderate or severe levels of disability.1 The recovery of the affected upper extremity after stroke is particularly concerning, with an estimated 40% of patients not regaining functional use of this limb.2– 4 The known consequences of stroke considered to be responsible for this loss of function include muscle weakness, loss of dexterity, and spasticity (hypertonicity).5

Spasticity is a neurological impairment that frequently occurs after stroke and is believed to contribute not only to a loss of function but also to the development of joint contractures and pain. Spasticity is defined as “disordered sensorimotor control, resulting from an upper motor neuron lesion, presenting as intermittent or sustained involuntary activation of muscles.”6(p5) Rehabilitation resources can be invested in identifying spasticity, attempting to prevent its development, and treating the condition once it is established. Pharmacological methods are used routinely to treat established spasticity, and intervention is recommended when spasticity causes functional problems.7 Given the effects attributed to spasticity, effective management might involve initiating treatment at the first signs of spasticity as opposed to waiting until either functional problems or secondary complications have developed. Achieving this goal would require a method for accurately identifying spasticity. Physical therapists are highly involved in the management of poststroke spasticity and are increasingly becoming involved in the decision-making processes underlying the use of pharmacological agents, such as botulinum toxin A. Thus, the accurate assessment of spasticity is a key role for any neurological physical therapist; that is, there is a need for a way in which to identify the presence of (or rule out) abnormal muscle activation. July 2009

The assessment of spasticity in clinical practice usually is accomplished with descriptive scales for evaluating the resistance to passive movement at a nominal or ordinal level of measurement8; one of the most frequently used scales is the Modified Ashworth Scale9 (MAS). The MAS has been criticized— both its reliability and its validity having been challenged8,10,11— because it is unable to distinguish between neurological and mechanical contributions to the stiffness levels observed during passive movement. It is, therefore, an indirect measure of spasticity because it cannot establish the presence of (or rule out) abnormal muscle activation. Nevertheless, it is unlikely that scales such as the MAS will cease to be used by clinicians for the foreseeable future.12 It has been advised that the assessment of spasticity should include neurophysiological measurements of muscle activity levels,10 which would provide a direct measure of spasticity, according to the current understanding of the phenomenon. This case report focuses on the diagnosis of spasticity through the use of a neurophysiological measure. The report describes 2 individuals*

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on May 29, 2009, at www.ptjournal.org.

who developed poststroke spasticity and who subsequently were given botulinum toxin type A (BoNT-A) as part of the management of their spasticity. A neurophysiological method of spasticity assessment was used alongside the more traditional MAS. The information gained through the use of this neurological assessment tool, both in the initial identification of upper-limb spasticity and in the subsequent evaluation of the response to treatment with BoNT-A, is discussed. Repeat measurements of upper-limb function, arm movement, and pain for both individuals allow for further discussion of how the information gained through an accurate diagnosis of spasticity can be applied in clinical practice.

Measures * The 2 individuals had been recruited into a randomized controlled trial (RCT) but were subsequently unmasked and removed from the analysis of the RCT because of the clinical course of their recovery. The RCT had investigated the early use of botulinum toxin (BTX), but both individuals developed spasticity after the intervention and required pharmacological treatment. They, therefore, were withdrawn from the trial so that their physicians could be informed of any treatment with BTX. Unmasking revealed that both individuals had been randomly assigned to receive a placebo; therefore, neither individual had received any BTX before the treatment described in this case report. When the 2 individuals were removed from the RCT, the decision was made to continue with the assessments that they would have received had they remained in the trial and to consider their cases as individual case reports. The RCT had received ethical approval from the Local Research Ethics Committee, and written informed consent was obtained from all participants.

Spasticity, passive and active ranges of motion in the elbow and wrist joints, arm function, and pain were first assessed at 34 days after stroke for one of the individuals and at 18 days after stroke for the other individual. Repeat measurements were obtained at 4, 8, 12, and 20 weeks after the initial assessment. Spasticity was assessed at the elbow and wrist with a neurophysiological measure13 and the MAS.9 Surface electromyography (EMG) electrodes† were initially placed on the biceps

† Biometrics Ltd, Units 25–26, Nine Mile Point Ind Est, Cwmfelinfach, Gwent, United Kingdom.

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Measurement of Poststroke Spasticity and Treatment With Botulinum Toxin and triceps muscles, the long wrist and finger flexor muscles, and the long wrist and finger extensor muscles. The SENIAM (surface electromyography for the noninvasive assessment of muscles) recommendations were followed for EMG electrode placement and, when available, for the positioning of the sensors over the muscles.14 For the elbow measurement, an electrogoniometer† was positioned across the elbow joint (medial aspect). The individual was sitting with the shoulder abducted to 90 degrees (or as close to this position as could be achieved without pain) and in external rotation so that the thumb was uppermost. The assessor then manually moved the elbow from maximal flexion to maximal extension. This passive movement was made initially at a low velocity and then was repeated at a high velocity. For the wrist measurement, the electrogoniometer was placed across the wrist joint (medial aspect). The arm was repositioned with the shoulder in the neutral position, the elbow at 90 degrees, and the forearm fully supported and parallel to the floor, mid pronation/supination, so that the palm was facing medially with the thumb uppermost. The same technique of manual displacement from maximal flexion to maximal extension at low and high velocities was used. The displacement (ie, passive range of motion) and EMG data were simultaneously recorded at 1,000 Hz at each testing point and saved for subsequent analysis. All data were obtained using the DataLINK data acquisition system.† The MAS measurements were obtained during the fast passive movements of the elbow and wrist. The active range of motion was that achieved by the individual from the 690

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starting position—maximal extension for elbow flexion, maximal extension for elbow extension, and from neutral for the wrist. These active movements were made with the limb supported; that is, the individual did not have to maintain the limb against gravity. Angular displacement and EMG activity† were recorded during these movements. The active range of motion of the elbow was directly comparable to the passive range of motion achieved by the assessor, as the active range of motion began at the same position as the passive range of motion. For the wrist, the active range of motion began at a neutral position; therefore, the value that was comparable to the value for the passive range of motion (from maximal flexion to maximal extension) was the total for active flexion and active extension combined. Arm function was assessed with the Action Research Arm Test, a test of arm function with established reliability and validity for people with stroke.15 Pain was rated by the individual with a 5-point verbal descriptor scale: no pain, mild pain, moderate pain, severe pain, or pain could not be worse.

Data Analysis Raw EMG data were notch filtered (50 Hz) and then smoothed with root-mean-square methods (50millisecond window width). For the analysis of spasticity, the average integrated EMG activity (referenced to angular displacement) was calculated during both low-velocity and high-velocity passive stretches by use of Mathcad (version 12.1).‡

‡ PTC Corporate Headquarters, 140 Kendrick St, Needham, MA 02494.

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Patient History and Review of Systems Mr A Examination. Mr A was a 72-yearold man who had been admitted to a hospital with a first-instance unilateral stroke with right-side hemiplegia. Clinically, the stroke had been classified as partial anterior circulation syndrome, and a computed tomography scan showed a left parietal infarct with a hemorrhagic conversion. Mr A was retired, lived with his wife and, before his stroke, was leading an independent life. He had no previous history of upperlimb functional problems. The baseline assessments for Mr A took place 34 days after the stroke. The measurements are shown in the Table, with the exception of the neurophysiological spasticity assessments, which are shown in Figure 1. At baseline, Mr A had no strong clinical signs of flexor muscle spasticity (as assessed with the MAS) at either the elbow or the wrist (Table), but the neurophysiological measure revealed a velocity-dependent increase in muscle activity at both the elbow and the wrist, although the increase was more marked at the wrist (Fig. 1). Mr A had no active movement or arm function at the baseline assessment, nor did he report any pain in his arm (Table). Four weeks later, Mr A had developed clinical signs of spasticity, that is, increased resistance to passive movement (as recorded with MAS scores) and decreased range of motion, at both the elbow and the wrist (Table). The neurophysiological assessment demonstrated that the level of spasticity remained similar to that seen at the baseline. Figure 2 shows the neurophysiological spasticity at Mr A’s elbow and wrist; almost immediately after the limb was moved into extension, the flexor muscle ac-

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Measurement of Poststroke Spasticity and Treatment With Botulinum Toxin Table. Results for Mr A and Mr B Baseline Patient Mr Ab

Measure

a

Elbow

Wrist

Elbow

Wrist

Elbow

Wrist

Elbow

Wrist

54

51

31

73

40

99

41

29

66

Active flexion (°)

0

0

0

0

0

0

0

0

0

0

Active extension (°)

0

0

0

0

0

0

0

0

0

0

0

0

None

Moderate

0

0 Severe

0 Moderate

3

3

3

4

3

3

3

3

98

93

104

94

89

93

78

98

94

97

Active flexion (°)

67

0

32

20

81

13

78

42

94

54

0

0

5

12

64

35

89

45

102

64

Arm function (ARAT) score (total⫽57)

1⫹

0 Could not be worse

Passive range of motion (°)

Active extension (°)

0

Pain

0

None

MAS score

c

Week 20

Wrist

MAS score

b

Week 12

129

Pain

a

Week 8

Elbow

Passive range of motion (°)

Arm function (ARAT) score (total⫽57)

Mr Bc

Week 4

3

Moderate 3

3

2

1

6

20

Mild

None

None

2

1

1⫹

1⫹

1⫹

0

ARAT⫽Action Research Arm Test, MAS⫽Modified Ashworth Scale. For Mr A, botulinum toxin type A treatment was administered 5 days after the week 4 measurements were obtained. For Mr B, botulinum toxin type A treatment was administered 1 week before the week 4 assessment.

tivity levels began to increase, and this activity continued throughout the rest of the stretch. This increase in activity was present in the slowand fast-velocity passive stretches for both the elbow and the wrist. In addition, the level of activity at the wrist joint was greater with the high-velocity movement, indicating a velocity-dependent component to the spasticity at this joint. Mr A still did not have any active movement or arm function, but he had now begun to experience pain in the upper extremity (Table). Intervention. Subsequent to the measurements obtained 4 weeks after the baseline, a clinical decision was made to administer to Mr A BoNT-A injections to manage his spasticity. Botulinum toxin type A was chosen because of the focal nature of its action, as Mr A complained primarily about pain and stiffness in the upper extremity. The muscles selected for the injections were the biceps brachii, brachialis, brachioradialis, flexor digitorum superficialis, and flexor digitorum profundus musJuly 2009

cles; Mr A received a total dose of 400 U of BoNT-A (Botox§) distributed among these muscles 5 days after the week 4 measurements were obtained. During the week after the BoNT-A injections were given, Mr A was discharged from inpatient care and returned home with support. Outpatient physical therapy and oc§

Allergan Inc, 2525 Dupont Dr, PO Box 19534, Irvine, CA 92623-9534.

cupational therapy were arranged but did not commence until 3 weeks after discharge. Outcome. The MAS scores for Mr A remained high throughout the follow-up, never being less than 3, indicating that clinical signs of spasticity remained at both the wrist and the elbow. In contrast, the neurophysiological measure of spasticity at

Figure 1. Spasticity levels for Mr A, expressed as average integrated electromyography (EMG) activity (millivolts) during passive stretching.

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Figure 2. (A) Electromyography (EMG) activity in the biceps muscle during slow and fast passive stretching into extension of the elbow for Mr A at 4 weeks after the baseline (before botulinum toxin type A injections). (B) EMG activity in the long wrist flexor muscles during slow and fast passive stretching into extension of the wrist for Mr A at 4 weeks after the baseline (before botulinum toxin type A injections).

the elbow suggested a decrease in spasticity (Fig. 3A); the response to the passive stretch was of a much smaller magnitude than the response observed 4 weeks earlier, before the BoNT-A injections were given. The levels of muscle activity in the elbow

spasticity assessments continued to be low for the remainder of the observation period, although by the final measure (week 20 after the baseline), there was some increase in muscle activity levels during the fast stretch. After injection with BoNT-A,

the neurophysiological responses at the wrist remained similar to those observed before the intervention (Fig. 3B); the neurophysiological measure indicated a decrease only at the final (week 20) assessment. Therefore, although both the clinical

Figure 3. (A) Electromyography (EMG) activity in the biceps muscle during slow and fast passive stretching into extension of the elbow for Mr A at 8 weeks after the baseline (after botulinum toxin type A injections). (B) EMG activity in the long wrist flexor muscles during slow and fast passive stretching into extension of the wrist for Mr A at 8 weeks after the baseline (after botulinum toxin type A injections).

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Measurement of Poststroke Spasticity and Treatment With Botulinum Toxin and the neurophysiological measures indicated signs of spasticity at the wrist, there was inconsistency between the clinical findings and the neurophysiological observations for the elbow. Mr A did not regain any active movement or functional capabilities in the upper extremity during the observation period. The limitations in the range of motion at the elbow remained, possibly indicating adaptive shortening. Mr A continued to experience pain in the upper extremity, which was at its highest level at the week 8 assessment and was still present, albeit at a lower level, at the final (week 20) assessment (approximately 6 months after the stroke). Mr B Examination. Mr B was a 54-yearold man who had been admitted to a hospital with a first-instance unilateral stroke with right-side hemiplegia. Clinically, the stroke had been classified as total anterior circulation syndrome, and a computerized tomography scan showed a left parietal infarct. Mr B worked full time as a prison warden before his stroke and lived with his wife and their 5-year-old son. The baseline assessments for Mr B took place 18 days after the stroke. The measurements are shown in the Table, with the exception of the neurophysiological spasticity assessments, which are shown in Figure 4. Mr B had indications of high levels of spasticity on both the clinical scale (MAS score of 3 at both the elbow and the wrist) and the neurophysiological measure (Fig. 4). The increase in muscle activity levels at the wrist was clearly demonstrated by the neurophysiological measure (Fig. 5A), which revealed a steady increase in the activity of the flexor muscles as the wrist was moved toward extension. Mr B had active movement only in the elbow flexor muscles, and he July 2009

Figure 4. Spasticity levels for Mr B, expressed as average integrated electromyography (EMG) activity (millivolts) during passive stretching.

had no arm function at the baseline assessment. Intervention. The clinical signs of spasticity resulted in a decision to treat the spasticity early with pharmacological interventions, initially baclofen and then later BoNT-A because the therapy team believed that there had been an insufficient response to the baclofen. Botulinum toxin type A was administered 38 days after admission to the hospital (20 days after the baseline assessment); the elbow flexor muscles were injected with 200 U of BoNT-A (Botox) divided among the biceps, brachialis, and brachioradialis muscles. The BoNT-A injections were given 1 week before the week 4 assessment (which took place approximately 6 weeks after the stroke). Mr B remained an inpatient throughout the course of the observation period but was scheduled for discharge to his home shortly after the final assessment. Outcome. The clinical signs of spasticity for Mr B, as measured with the MAS, remained high immediately after the BoNT-A injections were given but subsequently lessened; by the final assessment (week 20 after the baseline), no clinical evidence of

spasticity was seen at the wrist, and only minimal evidence was seen at the elbow. The neurophysiological measure revealed a sharp decrease in muscle activity levels at both the elbow and the wrist after the BoNT-A injections were given (in contrast to the clinical MAS measure at week 4), and these levels remained low throughout the follow-up. The neurophysiological measure (Fig. 5B) showed that although the wrist flexor muscles still responded to the fast stretch, the magnitude of the response was smaller than that observed at the baseline, and the response of the same muscles to the slow stretch was limited primarily to the end range of motion into extension. Although there was some increase in muscle activity levels at the week 8 assessment for the wrist, the levels decreased at later assessments (Fig. 4). Mr B experienced a return of active movement at both the elbow and the wrist in both the flexor and the extensor directions at week 4, and this movement continued to improve throughout the follow-up. By week 12, Mr B could actively move his elbow and wrist through the same range as the assessor could move them passively. Arm function recov-

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Figure 5. (A) Electromyography (EMG) activity in the long wrist flexor muscles during slow and fast passive stretching into extension of the wrist for Mr B at baseline (before botulinum toxin type A injections). (B) EMG activity in the long wrist flexor muscles during slow and fast passive stretching into extension of the wrist for Mr B at 4 weeks after the baseline (after botulinum toxin type A injections).

ery began slightly later than active movement recovery, but Mr B had made good progress by the final assessment, with an Action Research Arm Test score of 20. This score indicated that he had both proximal recovery and distal recovery and was able lift his hand onto a table and grasp an object placed on the table. The passive range of motion at both joints remained stable, indicating no development of contractures. Although Mr B experienced moderate pain in the upper limb at the week 4 assessment, this pain did not linger, and he did not complain of pain from week 12 onward.

Discussion This case report documented the progress of 2 individuals who had stroke and who developed spasticity in their upper limbs early after the onset of a stroke. Both individuals had experienced severe disabilities as a consequence of the stroke, with no recovery of upper-extremity function in the first few weeks after the stroke. Their prognosis for further functional recovery of the upper extremity, therefore, was limit694

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ed.16,17 Despite early treatment with BoNT-A, 1 of the 2 individuals continued to demonstrate clinical signs related to spasticity and associated problems of contractures and pain. The other individual did not, and he progressed enough to regain some upper-limb function. Discrepancy Between Clinical and Neurophysiological Measures of Spasticity There were inconsistencies between the 2 measures of spasticity, that is, the MAS and the neurophysiological measure. The MAS testing took place simultaneously with the fast passive stretch; this strategy would result in the starting position and velocity of movement during the procedure being the same for both the neurophysiological measure and MAS testing. The starting position for MAS testing was sitting rather than supine,18 but the procedures used in the fast stretch closely followed the protocols described for the elbow by Bohannon and Smith9 in all other aspects. We do not believe that testing in the sitting position would have adversely affected the reliability of

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the MAS, as the starting position was standardized throughout as recommended by Pandyan et al.11 The MAS failed to consistently detect increased levels of muscle activity indicative of spasticity in Mr A at the baseline assessment and was not able to detect decreased levels of muscle activity after the injection of BoNT-A into the elbow flexor muscles in Mr A. These inconsistencies could be attributable, in part, to the different constructs of the 2 measures. The MAS is a measure of resistance to passive movement, whereas the neurophysiological measure quantifies levels of muscle activity. Thus, the neurophysiological measure, unlike the MAS, is a direct measure of spasticity, as defined by the Support Programme for Assembly of Database for Spasticity Measurement consortium.5 Although muscle activity can contribute to an increase in the resistance to passive movement, this relationship is confounded by a variety of other biomechanical factors.5 For example, for Mr A, the high residual stiffness levels documented by MAS testing at the elbow, despite the July 2009

Measurement of Poststroke Spasticity and Treatment With Botulinum Toxin reduction in the levels of muscle activity, may have been a reflection of adaptive shortening that had already taken place. The method for assessing the response to passive stretching involved the use of a handheld tool and therefore would have allowed some variations in the velocity at which the limb was moved at different assessment sessions. It has been acknowledged that muscle activity levels could be affected by the velocity of the passive stretch, but controlling for this effect would necessitate the use of a motorized assessment system. The use of a handheld tool for spasticity assessment offers greater flexibility in the assessment process. Although this method can result in some variations between assessment sessions, the velocity of movement can be recorded and examined subsequently by the assessor. Manual testing of this nature is more feasible for adoption by clinicians because it can be used at a patient’s bedside and, therefore, can be used for patients with severe impairments after stroke, such as the 2 individuals described here, who may not be able to tolerate a motorized assessment system. Examination of the mean velocities at which the limbs were moved showed good consistency for the slow movement, with mean velocities ranging from 3°/s to 13°/s for Mr A and from 8°/s to 17°/s for Mr B. There were more variations in the velocities of the fast movement, but in all instances, there was a distinct difference between the slow and the fast passive movements at each assessment. A primary concern with these variations in velocities would be underestimation of the presence of spasticity as a result of not detecting a velocity-dependent component if the limb was moved too slowly. The mean velocities of the fast passive movement for Mr A ranged from July 2009

27°/s to 58°/s at the wrist and from 22°/s to 104°/s at the elbow. The mean velocities of the fast movement were much lower at week 4 (32°/s) and week 20 (22°/s) than at the other assessment points. Interestingly, although it might be expected that movement at a lower velocity would result in less EMG muscle activity being recorded, these 2 assessment points actually had higher levels of EMG muscle activity seen in Mr A’s elbow flexor muscles during the observation period (Fig. 1). It is possible, though, that even higher levels of muscle activity could have been recorded had the limb been moved at a higher velocity at these assessment points. For Mr B, the mean velocities of the fast movement ranged from 73°/s to 122°/s for the wrist and from 51°/s to 108°/s for the elbow. It is acknowledged that large variations in the velocities at which a limb is moved between assessment points is undesirable. However, given that in both individuals the highest levels of muscle activity were observed on the occasions when the velocity of perturbation was lower than usual, we believe that the presence of spasticity was not missed in these cases. It is important that clinicians using handheld techniques to measure muscle activity levels also record the velocities at which the limb was moved, when possible. We could not eliminate differences in the amplitudes of the signals from the surface EMG electrodes at consecutive assessments, but we reduced them by adopting the standardized EMG procedures described by SENIAM.14 Clinicians interpreting the results of spasticity measurements should consider these factors, which may cause differences in measurements. In its present form, the neurophysiological measure of spasticity is of primary value as a diagnostic tool, identifying the presence of abnormally

increased muscle activity levels. Because of the known errors in measurements that occur with this tool, it should be use with caution for clinical measurements if identifying subtle changes in muscle activity levels over time is the goal. Marked trends, however, can be observed, and these trends can contribute to a clinician’s understanding of an individual’s spasticity. Early Identification of Spasticity and Potential Prevention of Secondary Complications of Spasticity Although the neurophysiological measure revealed signs of spasticity for Mr A at the baseline, he was not treated with BoNT-A until clinical signs of spasticity had also developed. This finding raises the question of whether treatment with BoNT-A should have been used prophylactically to prevent the posturing that is associated with abnormal muscle activity and that could have contributed to adaptive shortening. The management of poststroke spasticity with BoNT-A treatment is one of several strategies that can be used by a rehabilitation team. Regardless of the treatment selected, however, the need for accurate assessment and monitoring of the effectiveness of the chosen treatment remains paramount. Treatment Strategies for Patients After Injections With Botulinum Toxin Type A The focus of this case report was to examine how the adoption of a neurophysiological measure of spasticity can assist in diagnostic processes for clinicians and thus direct treatment strategies. However, it is important to acknowledge that the contrasting outcomes for the 2 individuals described in this case report could have been influenced by their different rehabilitation programs. Both patients received specialized stroke rehabilitation, but discharge from

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Measurement of Poststroke Spasticity and Treatment With Botulinum Toxin inpatient care occurred much earlier for Mr A. After he was given injections of BoNT-A, Mr A received only 1 week of therapy before being discharged from the hospital, and there was a gap of 3 weeks until outpatient therapy began. Once therapy was reinstated, it took place on a weekly basis, as opposed to the daily treatments that Mr A had been receiving as an inpatient. In contrast, Mr B remained an inpatient for 6 months after the stroke and thus continued to receive an intensive therapy program throughout the follow-up, including the period immediately after the BoNT-A injections. Guidelines for the use of BoNT-A clearly indicate that a program of therapy is requisite after injections,18 and it is possible that the additional functional benefit observed in Mr B was attributable to his concomitant intensive therapy program. Repeated Cycles of Botulinum Toxin Type A Treatment The case of Mr A highlights the problems of using a confounded measure, such as the MAS, to quantify the effectiveness of spasticity treatment: it is possible for people who respond to treatment to be inappropriately identified as nonresponders. The continued signs of spasticity at the wrist with both the clinical and the neurophysiological spasticity measures could indicate that Mr A did not respond to the BoNT-A treatment. However, this possibility seems unlikely given the response observed at the elbow with the neurophysiological measure. Other reasons for the continued signs of wrist spasticity could be either inadequate dosage or injections into the wrong muscle (ie, in Mr A, only the finger flexor muscles and not the wrist flexor muscles were injected). Currently, it is advised that there be 12 weeks between cycles of treatment with BoNT-A19; thus, in the event of insufficient dosage or incorrect selection of muscles for injection, 696

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there is an increased likelihood of secondary complications becoming established before a clinician can repeat the injection. However, some preliminary data have suggested that it may be possible to reinject BoNT-A within this 12-week time frame.20 Monitoring with a neurophysiological measure could assist in the selection of patients for whom such a treatment approach may be appropriate. For example, it might have been considered that the treatment dosage was insufficient for Mr A given the sustained clinical signs of spasticity after the BoNT-A injections were given and thus that reinjection should be considered. However, an analysis of the neurophysiological measure would show that this option would be inappropriate at the elbow, where BoNT-A had successfully shut down the flexor muscles, but might be worth considering for the wrist. The 3 key issues outlined by this case report are as follows. There are discrepancies between the spasticity measure of the MAS and the neurophysiological measure of increased muscle activity. The MAS may lack sensitivity and, therefore, is an inadequate tool for identifying spasticity and monitoring its response to treatment. The neurophysiological measure of spasticity described in this case report is a bedside tool that can be adopted by clinicians to aid in identifying and monitoring the presence of spasticity. All authors provided concept/idea/project design. Ms Cousins, Dr Rimington, and Dr Pandyan provided writing. Ms Cousins provided data collection. Ms Cousins, Dr Roffe, and Dr Pandyan provided data analysis. Dr Roffe, Dr Rimington, and Dr Pandyan provided project management. Dr Pandyan provided fund procurement and facilities/ equipment. Dr Roffe provided patients and institutional liaisons. Dr Ward, Dr Roffe, Dr Rimington, and Dr Pandyan provided consultation (including review of manuscript before submission).

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The randomized controlled trial from which the patients in this case report were drawn had received unrestricted educational support from the North Staffordshire Medical Institute and Allergan Ltd. Dr Ward has received honoraria for lectureships and advisory work from Allergan Inc, Medtronic, and Ipsen Ltd. He also has received nonattributory and research grants for training and research products from Allergan Europe Ltd. Dr Pandyan has received unrestricted educational support from Allergan Ltd and Biometrics Ltd and honoraria for speaking from Allegan Ltd and Elan Pharma. This article was received February 1, 2008, and was accepted March 19, 2009. DOI: 10.2522/ptj.20080040

References 1 Reducing Brain Damage: Faster Access to Better Stroke Care. London, United Kingdom: National Audit Office; 2005. 2 Parker VM, Wade DT, Langton Hewer R. Loss of arm function after stroke: measurement, frequency, and recovery. Int Rehabil Med. 1986;8:69 –73. 3 Heller A, Wade DT, Wood VA, et al. Arm function after stroke: measurement and recovery over the first three months. J Neurol Neurosurg Psychiatry. 1987;50: 714 –719. 4 Broeks J, Lankhorst G, Rumping K, Prevo A. The long term outcome of arm function after stroke: results of a follow-up study. Disabil Rehabil. 1999;21:357–364. 5 Pandyan AD, Gregoric M, Barnes MP, et al. Spasticity: clinical perceptions, neurological realities and meaningful measurement. Disabil Rehabil. 2005;27:2– 6. 6 Barnes MP. An overview of the clinical management of spasticity. In: Barnes MP, Johnson GR, eds. Upper Motor Neurone Syndrome and Spasticity: Clinical Management and Neurophysiology. Cambridge, United Kingdom: Cambridge University Press; 2001:1–11. 7 Ward T, Koko C. Pharmacological management of spasticity. In: Barnes MP, Johnson GR, eds. Upper Motor Neurone Syndrome and Spasticity: Clinical Management and Neurophysiology. Cambridge: Cambridge University Press; 2001:165–187. 8 Platz T, Eickhof C, Nuyens G, Vuadens P. Clinical scales for the assessment of spasticity, associated phenomena, and function: a systematic review. Disabil Rehabil. 2005;27:7–18. 9 Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther. 1987;67: 206 –207. 10 Kumar RTS, Pandyan AD, Sharma AK. Biomechanical assessment of post-stroke spasticity. Age Ageing. 2006;35:371–375.

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Measurement of Poststroke Spasticity and Treatment With Botulinum Toxin 11 Pandyan AD, Johnson GR, Price CIM, et al. A review of the properties and limitations of the Ashworth and Modified Ashworth Scales as measures. Clin Rehabil. 1999;13: 373–383. 12 Johnson GR. Outcome measures of spasticity. Eur J Neurol. 2002;9(suppl 1): 10 –16. 13 Pandyan AD, Vuadens P, van Wijck FMJ, et al. Are we underestimating the clinical efficacy of botulinum toxin (type A)? Quantifying changes in spasticity, strength and upper limb function after injections of Botox to the elbow flexors in a unilateral stroke population. Clin Rehabil. 2002;16: 654 – 660.

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14 Hermens HJ, Freriks B, Merletti RE, et al. European Recommendations for Surface Electromyography: Results of the SENIAM Project. Enschede, the Netherlands: Roessingh Research and Development; 1999. 15 Lyle RC. A performance test for assessment of upper limb function in physical rehabilitation treatment and research. Int J Rehabil Res. 1981;4:483– 492. 16 Feys H, De Weerdt W, Nuyens G, et al. Predicting motor recovery of the upper limb after stroke rehabilitation: value of a clinical examination. Physiother Res Int. 2000;5:1–18. 17 Pandyan AD, Cameron M, Powell J, et al. Contractures in the post-stroke wrist: a pilot study of its time course of development and its association with upper limb recovery. Clin Rehabil. 2003;17:88 –95.

18 Ward AB, Aguilar M, De Beyl Z, et al. Use of botulinum toxin type A in management of adult spasticity: a European consensus statement. J Rehabil Med. 2003;35:98 –99. 19 Barnes M, Bhakta B, Moore P, et al. The Management of Adults With Spasticity Using Botulinum Toxin: A Guide to Clinical Practice (April 2001). Surrey, United Kingdom: Radius Healthcare; 2001. 20 Turner-Stokes, Ashford S. Serial injection of botulinum toxin for muscle imbalance due to regional spasticity in the upper limb. Disabil Rehabil. 2007;23: 1806 –1812.

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Perspective A Guide to Interpretation of Studies Investigating Subgroups of Responders to Physical Therapy Interventions Mark Hancock, Robert D. Herbert, Christopher G. Maher M. Hancock, PT, PhD, is Lecturer, Back Pain Research Group, The University of Sydney, Sydney, New South Wales, Australia. Mailing address: Faculty of Health Sciences, The University of Sydney, PO Box 170, Lidcombe 1825, New South Wales, Australia. Address all correspondence to Dr Hancock at: M.Hancock@usyd. edu.au. R.D. Herbert, PT, PhD, is Senior Research Fellow, The George Institute for International Health, The University of Sydney.

Many researchers and clinicians believe the effectiveness of existing physical therapy interventions can be improved by targeting the provision of specific interventions at patients who respond best to that treatment. Although this approach has the potential to improve outcomes for some patients, it needs to be implemented carefully because some methods used to identify subgroups can produce biased or misleading results. The aim of this article is to assist readers in assessing the validity and generalizability of studies designed to identify subgroups of responders to physical therapy interventions. The key messages are that subgroups should be identified using high-quality randomized controlled trials, the investigation should be limited to a relatively small number of potential subgroups for which there is a plausible rationale, subgroup effects should be investigated by formally analyzing statistical interactions, and findings of subgroups should be subject to external validation.

C.G. Maher, PT, PhD, is Director, The George Institute for International Health, The University of Sydney. [Hancock M, Herbert RD, Maher CG. A guide to interpretation of studies investigating subgroups of responders to physical therapy interventions. Phys Ther. 2009;89: 698 –704.] © 2009 American Physical Therapy Association

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dentifying patients who respond best to certain interventions has the potential to improve outcomes for existing and new physical therapy interventions. This is particularly the case in conditions, such as back pain, that are considered heterogeneous. It is unlikely that any one intervention for heterogeneous conditions will be highly effective for all patients. Some researchers1 have reported that interventions previously shown to have little effect when provided to heterogeneous populations can be more effective when provided to selected subgroups of patients. Characteristics that identify subgroups of patients who respond differently to a specific intervention are called treatment effect modifiers2,3 or effect moderators. A patient’s status for a given effect modifier provides information on how much additional benefit the patient is likely to gain from a specific intervention. For example, for a patient with an acute stroke, the type of stroke (ischemic or hemorrhagic) is a powerful effect modifier for response to anticoagulant therapy. The treatment has been shown to be highly effective for people whose stroke was caused by a clot4,5 but could be harmful or even fatal for those with a hemorrhagic stroke. Effect modifiers must be differentiated from prognostic factors. Prognostic factors are characteristics that identify patients who recover at different rates or have different outcomes. Prognostic factors are useful in providing patients with a more accurate prognosis, but they do not provide any information about which patients will respond best to a specific intervention. An example of a prognostic factor for recovery from low back pain is initial pain intensity. Patients with lower initial pain intensity typically have been shown to recover more quickly than patients July 2009

with higher pain intensity, regardless of intervention.6,7 Although it may be tempting to presume that low pain intensity also predicts response to treatment, this assumption does not logically follow. It is quite possible that a particular intervention is most effective when applied to people with more intense pain, or that its effectiveness does not depend on pain intensity.

studies are conducted to determine whether particular variables predict the outcome of interest. In the validation stage, variables found to be informative in the derivation study are tested in a new setting with new patients to assess internal and external validity. Finally, impact analysis studies investigate whether the use of the CPR in clinical practice results in better outcomes for patients.

It is important that studies investigating subgroups of patients who respond best to particular treatments use appropriate design and analysis strategies. In some studies, single predictors are investigated, whereas other studies investigate combinations of predictors. Regardless of whether a single predictor or combinations of predictors are used, the design and analysis must match the aim of identifying specific predictors of response to the intervention. In particular, it is important to avoid using a design and analysis that are suitable for identifying prognostic factors (ie, predictors of outcome) when the intention is to identify specific predictors of subgroups of patients who respond best to the particular intervention.

Adherence to generic guidelines for development and validation of CPRs is important but does not obviate the need to use study designs and analyses appropriate for a specific research question. This important point was emphasized in an instructional article on CPRs by Beattie and Nelson in which the authors stated that “it is important to note that different research methods are needed in the development phase of a clinical prediction rule based upon its proposed use.”13(p159) Studies investigating diagnosis typically use crosssectional designs, studies of prognosis use longitudinal designs (often single-arm studies), and studies of effect modification use controlled (2arm) trials. It has become common for researchers to use study designs and analyses that are appropriate for identifying prognostic factors (ie, nonspecific predictors of outcome) but to interpret the results as if they had identified subgroups of responders to treatment.9 –12 Clinical predic-

Clinical prediction rules (CPRs) originally were used to quantify the usefulness of clusters of patient characteristics (eg, history and physical examination findings) for diagnosis and prognosis. However, CPRs also can be used to identify patients who respond best to certain interventions. Publications reporting on this sort of CPR have become more numerous in the physical therapy literature,8 –12 especially in back pain research. A large body of literature has described the stages of development of CPRs.13–15 The 3 main stages described in the literature are derivation, validation, and impact analysis.13–15 In the derivation stage,

Available With This Article at www.ptjournal.org • Discussion Podcast: Hancock and Herbert talk with Childs, Fritz, and Riddle (participants subject to change). • Audio Abstracts Podcast This article was published ahead of print on May 21, 2009, at www.ptjournal.org.

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Interpreting Studies of Responders to Physical Therapy Interventions tion rules can be used to identify subgroups of patients who respond best to certain interventions, but only if the appropriate design is used.

mates of the effect of treatment because there is no control group not receiving the treatment; thus, singlearm trials cannot identify factors associated with the effect of treatment.

Research into subgroups of responders using CPRs has the potential to advance the science and practice of physical therapy and to improve outcomes for patients, but it also can produce biased or misleading results if not conducted and interpreted correctly. The aim of this article is to assist readers in interpreting the validity of studies investigating subgroups of responders to physical therapy interventions by considering key issues in study design and analysis. The focus will be on design and analysis of CPRs of subgroup effects using randomized controlled trials (RCTs). The article is structured so that each key issue is discussed and then summarized. The Appendix lists the 6 key points.

It is important to use controlled trials in all stages of the development of a CPR that aims to identify subgroups of responders to treatment. In the derivation stage of a CPR, a wide range of predictor variables may be examined to develop the CPR. In the validation stage, the CPR is tested for internal and external validity in new samples of patients. As both the development and validation studies assess the effect of treatment, both require controlled trials.

Study Design When the aim of a study is to identify factors associated with the effect of an intervention, the study must use an experimental design that can estimate the effect of that intervention. As the effect of treatment is assessed by comparing outcomes in patients receiving the treatment with outcomes in a control group who do not receive the treatment, the study must have 2 groups. Preferably, the study should be a well-conducted RCT. Similarly, if the aim of the study is to identify patient characteristics that would help a clinician choose between 2 interventions (eg, spinal manipulation or exercise) for a specific patient, the appropriate design is an RCT with patients randomly assigned to receive spinal manipulation or exercise. It is important to realize that only RCTs can provide a rigorous test of whether a subgroup characteristic is associated with response to intervention. Single-arm trials cannot provide rigorous esti700

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We are aware of one example that appears to justify the use of singlearmed trials to identify treatment effect modifiers. Flynn and colleagues11 used a single-armed trial to demonstrate that a particular clinical presentation was associated with a particularly good outcome in patients receiving manipulation for low back pain. Subsequently, Childs and colleagues8 validated the CPR with a randomized trial. In our opinion, there is no reason to expect that factors found in single-arm trials to be predictive of outcome will subsequently be found in 2-arm trials to be predictive of response to treatment. Where researchers believe there is a rationale for why a CPR derived in a single-arm study also may predict response to an intervention, the CPR should be investigated in a controlled trial before any suggestion about the role in predicting response to treatment is made. When a CPR is developed in a single-arm trial, any subsequent evaluation in a controlled study should be considered a derivation study and not a validation study. The reasoning is that the single-arm trial derived a CPR for prognosis, whereas the controlled trial derived a CPR for

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response to treatment. The analyses in the 2 studies are quite different; therefore, replication clearly has not occurred. We also would caution that use of the term “validation study” may be misleading, as it suggests a single study can validate a CPR. A series of studies usually is required to validate any CPR, regardless of whether it investigates diagnosis, prognosis, or response to treatment. Validation studies could include replication in similar clinical scenarios to show that the original result was not just due to chance (internal validation) through to testing in different scenarios to establish how generalizable the CPR is (external validation). Several previous studies that have claimed to identify subgroups of responders to intervention used singlearm trials with no control group.9 –12 As these studies did not include a control group, they could not estimate the effect of treatment (that is, they could not estimate the difference between treated and control groups) and, therefore, could not identify factors that modify the effect of a intervention. Studies that do not contrast outcomes between treatment and control groups can identify nonspecific predictors of outcome (or prognostic factors), but they cannot identify treatment effect modifiers. The following hypothetical example illustrates why a single-arm study design cannot validly identify subgroups of responders to treatment. A single-arm study investigated 100 patients with ankle fractures who received treatment with passive accessory mobilization of the ankle. The outcome measure was pain, as assessed with a 0 to 10 visual analog scale (VAS), at 6 weeks after cast removal. Two features (nondisplaced fracture and nonsurgical management) predicted a good outcome at 6 weeks and were included in a CPR. July 2009

Interpreting Studies of Responders to Physical Therapy Interventions Patients who met the CPR had a 6-week mean VAS score of 2/10, whereas patients who were negative on the CPR had a mean VAS score of 5/10 at 6 weeks after cast removal. Is it, therefore, appropriate to conclude that the CPR identifies patients with ankle fractures who respond best to passive accessory mobilization? Let us now imagine that the same study was a placebo controlled trial. Patients in the control group who met the CPR had a mean 6-week VAS score of 4/10. Patients in the control group who were negative on the CPR had a mean 6-week VAS score of 7/10. Therefore, the patients who met the CPR and received passive accessory mobilization (2/10) were, on average, 2 points better than those who met the rule and did not receive treatment (4/10) (Table). The patients who were negative on the CPR and received physical therapy (5/10) also were, on average, 2 points better than those who were negative on the CPR and did not receive physical therapy (7/10) (Table). That is, while those patients who met the CPR had better outcomes, they did not have a greater response to the treatment (compared with the control group) than those patients who did not meet the CPR (Table). The single-arm trial demonstrates that in a group of patients with ankle fractures who receive passive accessory mobilization, the outcome (regardless of treatment) is better in those who meet the CPR. The single-arm trial does not demonstrate that the CPR identifies a subgroup of patients who respond best to passive accessory mobilization. A number of studies have used RCTs to evaluate whether a certain patient profile is associated with response to treatment.8,16 –19 For example, Childs and colleagues8 conducted an RCT that demonstrated patient characteristics predicted response to spinal July 2009

Table. Hypothetical Example: Mean Pain Score (Out of a Maximum Score of 10) in Patients With Ankle Fractures Treated With Passive Accessory Mobilizationa Status on CPR

Treated With Passive Accessory Mobilization

Control Group

Benefit of Treatment

2/10

4/10

2/10 2/10

CPR positive CPR negative

5/10

7/10

Benefit of being CPR positive

3/10

3/10

a

The second column results represent the usefulness of the clinical prediction rule (CPR) as a prognostic factor. These data can be obtained only when an uncontrolled study is available. The far right column represents the effectiveness of the treatment compared with a control condition. These data can be obtained only when a treatment group and a control group are present. The difference in benefit of treatment between the CPR positive group (2/10) and the CPR negative group (2/10) determines the usefulness of the CPR in identifying patients who respond best to the intervention.

manipulation and exercise compared with exercise alone. Their data provide a direct test of the hypothesis that certain subgroups respond better than others to manipulation. Underwood and colleagues’ analysis of the UK BEAM trial revealed that age, work status, age of leaving school, pain and disability, quality of life, and beliefs were prognostic factors for recovery from low back pain, but the same factors did not predict response to manipulation, exercise, or both treatments combined.19 Up to this point we have argued that CPRs that identify predictors of response to treatment must use 2-armed (controlled) trials. Ideally, we would like a CPR to be tested in a high-quality randomized trial. We know from surveys that trials of physical therapy20 vary enormously in methodological quality. This is of concern because trials of low quality are associated with exaggerated treatment effects.21 Key point 1: Treatment effect modifiers should be investigated in an RCT before any conclusion regarding their role in predicting response to treatment is drawn.

Predictor Variables Even when predictors of response to treatment are investigated in highquality randomized trials, they are

still prone to spurious findings.22–24 A major reason for this is that the analyses often are conducted post hoc and involve investigation of a large number of variables with no plausible rationale for being predictors of response to intervention. Many authors22–24 have warned about the risks associated with multiple subgroup analyses in controlled trials. With a critical P value of .05, the chance of a falsely significant finding is as high as 5% for each predictor investigated. Consequently, when a large number of predictors are investigated, it usually is likely that one or more predictors will incorrectly be found to be a statistically significant predictor of response to intervention. The most appropriate way to deal with this problem is to define a limited number of plausible predictor variables prior to the conduct of the trial. Ideally, these predictors should be specified explicitly in a trial protocol that is published when the trial is registered. In a derivation study, it is reasonable to investigate a somewhat wider range of variables, but the results then need prospective validation in a future trial prior to being recommended for clinical practice. The study by Childs et al8 is a good example of an RCT in which the risk of spurious findings was limited by making the subgroup analysis the primary analysis of the study. In that

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Interpreting Studies of Responders to Physical Therapy Interventions study, only one predictor variable (positive or negative on the CPR) was investigated. Key point 2: Studies investigating treatment effect modifiers should limit the analyses to a small number of plausible predictors (subgroups) that are nominated prior to the conduct of the trial.

Analysis Strategy A common25–30 and seemingly logical approach to the evaluation of treatment effect modifiers is to examine the effectiveness of treatment compared with a control condition in subgroups of patients from a trial. Researchers who analyze their data in this way often find statistically significant effects of treatment in some subgroups but not others, and they may claim that this provides evidence that some subgroups respond differently than others. An example of this approach is the low back pain study by Gudavalli et al.27 These authors reported a statistically significant effect in favor of “flexiondistraction” treatment compared with active exercise in patients with radiculopathy (P⫽.05) but not in patients without radiculopathy (P⫽.13). They concluded that people with radiculopathy respond best to flexion-distraction treatment. However, this conclusion was based on a flawed analysis.31–33 Simulation studies show that even when there is no subgroup effect, researchers can expect to find significant effects of treatment in one subgroup only (P⬍.05) in 7% to 64% of tests.31 The correct analysis involves a test of interaction. That is, the correct analysis involves demonstrating that the effect of flexion-distraction compared with active exercise for one subgroup (patients with radiculopathy) is greater than the effect of flexion-distraction compared with active exercise in the other subgroup (patients without radiculopa702

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thy). The size of the interaction tells us how much more benefit (compared with the control condition) patients in the subgroup received from treatment compared with those not in the subgroup. Simulation studies show that when there is no subgroup effect, researchers can expect to find statistically significant interaction effects (P⬍.05) in 5% of tests, as is expected. That is, tests of interactions are much less prone than tests within subgroups to false positive findings.31 Key point 3: Identification of treatment effect modifiers should be based on tests of interactions.

Sample Size It is important to note that a test of interaction requires a significantly larger sample size to achieve the same level of statistical power or statistical precision than a test of the overall effect. When about half of the participants are in each subgroup, 4 times as many participants are required for a test of interaction than would be required for a test of a main effect of the same size.31 When the subgroups are not equal in size, as is usually the case, even greater sample sizes are required. Most randomized trials are powered only for tests of the main effect of treatment, so they have insufficient power to detect an interaction effect. Readers of reports of CPRs can inspect the confidence intervals around estimates of interaction effects to ascertain how much uncertainty is associated with a particular CPR. If a study is underpowered for testing an interaction, it will have wide confidence intervals and will risk incorrectly finding the effect modifier to be uninformative. A potential solution to the problem of inadequate power for testing interactions is to combine data from similar RCTs using metaanalysis techniques.34

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Key point 4: Studies investigating treatment effect modification require significantly larger sample sizes than studies of main effect. Convincing evidence of treatment effect modification requires precise estimates of interactions, as evidenced by narrow confidence intervals.

Subgroups Where the Mean Effect Is Close to Zero When a treatment has a moderate or large mean effect across all patients included in a trial, the researchers may be less inclined to investigate the presence of subgroups of responders. It is when treatments have small effects that researchers often will want to look for subgroups, but this is the context in which subgroup effects are least plausible. Where there are moderate or large effects, it is possible that a proportion of patients could receive a large effect while other patients receive no benefit from the treatment. However, where the mean effect is close to zero, the only way that a proportion of patients can receive a large effect is if the treatment is actually harmful (compared with the control condition) for other patients. Although, theoretically, this is possible, it would seem unlikely in most situations. Thus, in most situations, evidence of subgroup effects should be treated with caution if the main effect of treatment is small. Key point 5: Evidence of effect modification should be treated cautiously when the main (pooled) effect of treatment is close to zero.

Validation When researchers identify treatment effect modifiers using a particular set of data (for instance, data from a particular randomized trial), there is always the risk that the result is applicable only to the specific population from which the sample was drawn. In general, effect modifiers will be July 2009

Interpreting Studies of Responders to Physical Therapy Interventions less predictive when they are applied to data other than the sample on which they were identified. This is particularly the case when CPRs are developed to investigate the ability of combinations of variables to predict response to an intervention. For this reason, it is important to externally validate effect modifiers, including CPRs, before recommending them for use in clinical practice.13–15 External validation involves testing the validity of the effect modifier on other populations. We can differentiate “narrow” external validation, which involves testing in settings and in patients very similar to those of the original trial, and “broad” external validation, which involves testing in different settings and on different types of patients. An effect modifier that has been broadly validated is one that is widely applicable. Generalizability is important if an effect modifier is to be recommended for use in clinical practice to select patients who will respond best to a specific intervention, where many things, including the patients, settings, co-interventions, and clinicians, will be different from the original trial in which the CPR was developed. Key point 6: Effect modifiers should be externally validated before they are incorporated into guidelines for clinical practice.

Summary This article has identified a number of features that enhance the validity of studies designed to identify subgroups of patients who respond best to intervention. The Appendix provides a list of the key principles to be considered when interpreting studies investigating subgroups of responders to physical therapy interventions.35 All authors provided concept/idea/project design and writing and reviewed the final manuscript.

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Dr Herbert’s and Dr Maher’s fellowships are funded by the National Health and Medical Research Council of Australia. This article was received November 3, 2008, and was accepted April 6, 2009. DOI: 10.2522/ptj.20080351

References 1 Brennan GP, Fritz JM, Hunter SJ, et al. Identifying subgroups of patients with acute/subacute “nonspecific” low back pain: results of a randomized clinical trial. Spine. 2006;31:623– 631. 2 Kopec JA, Esdaile JM. Functional disability scales for back pain. Spine. 1995;20: 1943–1949. 3 Pocock SJ, Collier TJ, Dandreo KJ, et al. Issues in the reporting of epidemiological studies: a survey of recent practice. BMJ. 2004;329:883. 4 Kwiatkowski TG, Libman RB, Frankel M, et al; National Institute of Neurological Disorders and Stroke Recombinant Tissue Plasminogen Activator Stroke Study Group. Effects of tissue plasminogen activator for acute ischemic stroke at one year. N Engl J Med. 1999;340:1781–178 5 National Institute of Neurological Disorders and Stroke Recombinant Tissue Plasminogen Activator Stroke Study Group. Tissue plasminogen activator for acute ischemic stroke. N Engl J Med. 1995; 333:1581–158 6 Croft PR, Dunn KM, Raspe H. Course and prognosis of back pain in primary care: the epidemiological perspective. Pain. 2006; 122:1–3. 7 Hancock MJ, Maher CG, Latimer J, et al. Can rate of recovery be predicted in patients with acute low back? Development of a clinical prediction rule. Eur J Pain. 2009;13:51–55. 8 Childs JD, Fritz JM, Flynn TW, et al. A clinical prediction rule to identify patients with low back pain most likely to benefit from spinal manipulation: a validation study. Ann Intern Med. 2004;141: 920 –928. 9 Cleland JA, Childs JD, Fritz JM, et al. Development of a clinical prediction rule for guiding treatment of a subgroup of patients with neck pain: use of thoracic spine manipulation, exercise, and patient education. Phys Ther. 2007;87:9 –23. 10 Fernandez-de-las-Penas C, Cleland JA, Cuadrado ML, Pareja JA. Predictor variables for identifying patients with chronic tension-type headache who are likely to achieve short-term success with muscle trigger point therapy. Cephalalgia. 2008;28:264 –275. 11 Flynn T, Fritz J, Whitman J, et al. A clinical prediction rule for classifying patients with low back pain who demonstrate short-term improvement with spinal manipulation. Spine. 2002;27:2835–2843.

12 Iverson CA, Sutlive TG, Crowell MS, et al. Lumbopelvic manipulation for the treatment of patients with patellofemoral pain syndrome: development of a clinical prediction rule. J Orthop Sports Phys Ther. 2008;38:297–309. 13 Beattie P, Nelson RM. Clinical prediction rules: what are they and what do they tell us? Aust J Physiother. 2006;52:157–163. 14 Laupacis A, Sekar N, Stiell IG. Clinical prediction rules: a review and suggested modifications of methodological standards. JAMA. 1997;277:488 – 494. 15 McGinn TG, Guyatt GH, Wyer PC, et al; Evidence-Based Medicine Working Group. Users’ guides to the medical literature, XXII: how to use articles about clinical decision rules. JAMA. 2000;284:79 – 84. 16 Kalauokalani D, Cherkin DC, Sherman KJ, et al. Lessons from a trial of acupuncture and massage for low back pain: patient expectations and treatment effects. Spine. 2001;26:1418 –1424. 17 Klaber Moffett JA, Carr J, Howarth E. High fear-avoiders of physical activity benefit from an exercise program for patients with back pain. Spine. 2004;29: 1167–1172. 18 Stewart MJ, Maher CG, Refshauge KM, et al. Randomized controlled trial of exercise for chronic whiplash-associated disorders. Pain. 2007;128:59 – 68. 19 Underwood MR, Morton V, Farrin A; Team UBT. Do baseline characteristics predict response to treatment for low back pain? Secondary analysis of the UK BEAM dataset [ISRCTN32683578]. Rheumatology (Oxford). 2007;46:1297–1302. 20 Moseley AM, Herbert RD, Sherrington C, Maher CG. Evidence for physiotherapy practice: a survey of the Physiotherapy Evidence Database (PEDro). Aust J Physiother. 2002;48:43– 49. 21 Schulz KF, Chalmers I, Hayes RJ, Altman DG. Empirical evidence of bias: dimensions of methodological quality associated with estimates of treatment effects in controlled trials. JAMA. 1995;273:408 – 412. 22 Brookes ST, Whitley E, Peters TJ, et al. Subgroup analyses in randomised controlled trials: quantifying the risks of falsepositives and false-negatives. Health Technol Assess. 2001;5:1–56. 23 Moye LA, Deswal A. Trials within trials: confirmatory subgroup analyses in controlled clinical experiments. Control Clin Trials. 2001;22:605– 619. 24 Yusuf S, Wittes J, Probstfield J, Tyroler HA. Analysis and interpretation of treatment effects in subgroups of patients in randomized clinical trials. JAMA. 1991;266:93–98. 25 Callaghan MJ, Selfe J, McHenry A, Oldham JA. Effects of patellar taping on knee joint proprioception in patients with patellofemoral pain syndrome. Man Ther. 2008;13:192–199. 26 Clegg DO, Reda DJ, Harris CL, et al. Glucosamine, chondroitin sulfate, and the two in combination for painful knee osteoarthritis. N Engl J Med. 2006;354: 795– 808.

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Interpreting Studies of Responders to Physical Therapy Interventions 27 Gudavalli MR, Cambron JA, McGregor M, et al. A randomized clinical trial and subgroup analysis to compare flexiondistraction with active exercise for chronic low back pain. Eur Spine J. 2006;15:1070 –1082. 28 Pearson AM, Blood EA, Frymoyer JW, et al. SPORT lumbar intervertebral disk herniation and back pain: does treatment, location, or morphology matter? Spine. 2008;33:428 – 435. 29 Skargren EI, Carlsson PG, Oberg BE. Oneyear follow-up comparison of the cost and effectiveness of chiropractic and physiotherapy as primary management for back pain: subgroup analysis, recurrence, and additional health care utilization. Spine. 1998;23:1875–1883. 30 Yip YB, Tse H-MS, Wu KK. An experimental study comparing the effects of combined transcutaneous acupoint electrical stimulation and electromagnetic millimeter waves for spinal pain in Hong Kong. Comp Ther Clin Pract. 2007;13:4 –14. 31 Brookes ST, Whitely E, Egger M, et al. Subgroup analyses in randomized trials: risks of subgroup-specific analyses: power and sample size for the interaction test. J Clin Epidemiol. 2004;57:229 –236. 32 Klebanoff MA. Subgroup analysis in obstetrics clinical trials. Am J Obstet Gynecol. 2007;197:119 –122. 33 Lagakos SW. The challenge of subgroup analyses: reporting without distorting. N Engl J Med. 2006;354:1667–1669. 34 Schellingerhout JM, Verhagen AP, Heymans MW, et al. Which subgroups of patients with non-specific neck pain are more likely to benefit from spinal manipulation therapy, physiotherapy, or usual care? Pain. 2008;139:670 – 680. 35 Beneck GJ, Kulig K, Landel RF, Powers CM. The relationship between lumbar segmental motion and pain response produced by a posterior-to-anterior force in persons with nonspecific low back pain. J Orthop Sports Phys Ther. 2005;35: 203– 209.

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Appendix Key Principles for Assessing Points Determining the Validity of Trials Reporting Subgroups of Responders to Interventions Key point 1: Treatment effect modifiers should be investigated in a randomized controlled trial before any conclusion regarding their role in predicting response to treatment is drawn. Key point 2: Studies investigating treatment effect modifiers should limit the analyses to a small number of plausible predictors (subgroups) that are nominated prior to the conduct of the trial. Key point 3: Identification of treatment effect modifiers should be based on tests of interactions. Key point 4: Studies investigating treatment effect modification require significantly larger sample sizes than studies of main effect. Convincing evidence of treatment effect modification requires precise estimates of interactions, as evidenced by narrow confidence intervals. Key point 5: Evidence of effect modification should be treated cautiously when the main (pooled) effect of treatment is close to zero. Key point 6: Effect modifiers should be externally validated before they are incorporated into guidelines for clinical practice.

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Perspective Assessment of Physical Functioning: A Conceptual Model Encompassing Environmental Factors and Individual Compensation Strategies Kristin M. Tomey, MaryFran R. Sowers Commonly studied physical functions include activities such as walking and climbing stairs. Despite the acknowledged role of environmental factors and behavioral strategies to compensate for reduced performance capacity or environmental barriers in characterizing physical functioning, most assessments do not take these factors into account. This article presents a new conceptual model for assessment of relevant physical functioning while accounting for habitual environmental factors and compensation strategies.

K.M. Tomey, PhD, is Assistant Research Scientist, Department of Epidemiology, School of Public Health, University of Michigan, 109 Observatory St, Room 1867, Ann Arbor, MI 48109-2029 (USA). Address all correspondence to Dr Tomey at: [email protected]. M.R. Sowers, PhD, is John G. Searle Professor of Public Health and Professor of Epidemiology, Department of Epidemiology, School of Public Health, University of Michigan. [Tomey KM, Sowers MR. Assessment of physical functioning: a conceptual model encompassing environmental factors and individual compensation strategies. Phys Ther. 2009;89:705–714.] © 2009 American Physical Therapy Association

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imitations in physical functioning are important to consider because of their widespread prevalence and their link to: (1) decreased quality of life, (2) increased risk of disability, falls and fractures, and depression, and (3) increased health care costs.1–7 With the rising prevalence of physical limitations and attendant social, physical, and financial costs, it is increasingly relevant to examine the adequacy and completeness of our conceptualization of such limitations. It also is valuable to determine whether physical functioning assessments are adequate in identifying pertinent contributors to physical functioning capacity as well as performance ability. Recognizing the environment in which initiation and progression of physical functioning limitations occur is essential in understanding these limitations. The World Health Organization (WHO) acknowledges the centrality of the environment when it defines activity limitations as “problems in activity that occur as a result of an interaction between a health condition and the context in which the person exists.”8,9 This environmental context can range from exposures such as air pollution and general neighborhood conditions10,11 to more immediate environmental factors such as inadequate lighting or icy sidewalks, which can facilitate or hinder physical functioning. The degree to which individuals can and do deal with diminished abilities

Available With This Article at www.ptjournal.org • Audio Abstracts Podcast This article was published ahead of print on May 14, 2009, at www.ptjournal.org.

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and environmental challenges determines how well they will function in their real-life setting.9 –12 Common compensation and coping strategies, for example, include modifying the way an activity is performed, recruiting external supports such as an assistive device or another person, and avoidance.13–17 Many assessments of functioning do not capture the broad dynamic of personal, social, environmental, and compensatory strategies in physical functioning performance.8,12,18 –21 Various conceptual models depicting interactions between the environment and physical functioning tend to be focused on interventions at the individual level (eg, clinically oriented models guiding assessment and treatment of patients)22,23 or are public health-oriented models aimed at intervening at the community level (eg, improving access for people with disabilities).24 Conceptual models describing aging-related physical functioning difficulties tend to focus on development of these limitations1 and are not readily translated to the assessment realm. The purpose of this article is to present a new conceptual model— Physical Functioning Assessment in Your Environment (PF-E)—for the assessment of physical functioning status. In the model, physical functioning is conceptualized as being supported by physical abilities such as walking, reaching, vision, and hearing, as well as by those in the cognitive domain such as spatial orientation, short-term memory, intelligible speech, and alertness.2 The model also addresses habitual environmental factors and compensation and coping strategies. The conceptual model draws upon constructs identified in the 2001 International Classification of Functioning, Disability and Health (ICF)8,25 and the ideas and research of

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Fried,13,14 Agree,18 Kielhofner,22 Lawton,26 –28 and others.15–17,29 The development of this conceptual model is motivated by the escalating prevalence of limited physical functioning, the desire to broaden the focus of current conceptualizations of physical functioning used in clinical treatment paradigms; the limited incorporation of cognitive aspects in characterizing physical functioning, lack of assessments incorporating the breadth of personal and community factors that impinge upon living with physical functioning limitations, and failure to include assessment of potentially modifiable community-level factors.

Prevalence of Limited Physical Functioning Difficulties Limitations in physical functioning are fairly common among middleaged and older Americans. Among those 60 to 69 years of age, 21% reported difficulty or inability to walk 0.4 km (0.25 mile),7 and this proportion increased to 30% and 49% in the 70- to 79-year-old and ⱖ80-year-old age groups, respectively. In a population-based survey of Americans over 65 years of age, 12% had difficulty hearing normal conversation, and 11% had difficulty seeing words or letters in newsprint.30 Among those 45 to 64 years of age, 16% were limited in their ability to engage in work, school, play, or other activities for health reasons.31

The ICF: A Broad Framework of Health and Human Functioning The WHO’s ICF8 represents a detailed examination of both environmental factors and individual-level factors as they relate to health and human functioning. Although this classification system is not specifically focused on physical functioning assessment, it does provide a framework upon which conceptual

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Figure 1. International Classification of Functioning, Disability and Health model of disability. Reprinted with permission of the World Health Organization from: International Classification of Functioning, Disability and Health: Short Version. Geneva, Switzerland: World Health Organization; 2001:26.

models can be developed. The classification system addresses the biological, psychological, social, and environmental components of disability (schematic shown in Fig. 1; accompanying definitions shown in the Table). In the ICF context, a health condition includes diseases, disorders, injury, or trauma; aging; and congenital anomalies that interrelate with 3 functioning components: (1) body functions and body structures, (2) activities, and (3) participation. Figure 1 shows the inter-

play of these functioning components with contextual aspects, including environmental and personal factors. The ICF broadly characterizes environmental factors, considering products and technology, the natural environment and human-made changes to the environment, social support and relationships, attitudes, and the availability of services, systems, and policies. Although this WHOendorsed classification incorporates

a broad set of environmental components, it recognizes, but does not classify, personal factors, such as age and sex, which are acknowledged as integral to functioning, disability, and health.8,25 The ICF characterizes disability as a problem in 1 of the 3 functioning components after contextual factors are considered. Deficits in body structure or function are identified as impairments, difficulties with tasks or actions are labeled activity limi-

Table. Terms and Definitions Used in the 2001 International Classification of Functioning, Disability and Health8 Condition

Definition

Health conditions

Diseases, disorders, injury, or trauma; aging and congenital anomalies

Body function

Physiological functions of body systems

Body structure

Anatomical parts of the body

Activity

Execution of a task or action by an individual

Social participation

Involvement in a life situation

Impairment

Problems in body function or body structure that occur as a result of an interaction between a health condition and the context in which the person exists; a disability

Activity limitation

Problems in activity that occur as a result of an interaction between a health condition and the context in which the person exists; a disability

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Assessment of Physical Functioning tations, and problems with social participation are termed participation restrictions. Impairments, activity limitations, and participation restrictions are considered disabilities (ie, if the interaction between a person’s health condition and the contextual influences surrounding that person results in less than a full range of functioning, that person is considered disabled). The ICF provides 2 important qualifiers to describe severity of activity limitations: the performance qualifier, which describes what an individual does in his or her current environment, and the capacity qualifier, meant to represent the environmentally adjusted ability of the individual. Whereas the former qualifier describes the features of an individual’s environment, the latter qualifier describes an individual’s ability to execute a task or an action in a standard or uniform environment. Thus, the discrepancy between capacity and performance in the ICF classification provides a useful guide as to what can be done to enhance the individual’s environment to aid in improving functioning and is highly consistent with use in developing policies. Given the breadth of possibilities afforded by the ICF, it is useful to consider this framework as a point of reference when evaluating existing models.

Physical Functioning and the Environment: Models and Assessments Focused on the Individual Contribution of Conceptual Model Incorporating the Home Environment and Physical Functioning Seminal work that conceptualized the role of an individual’s home environment in physical functioning performance was published by Lewin32 in his person-environment (PE) fit and Life Space models.

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Person-environment fit describes the level of accommodation provided by a person’s environment for performance of activities. The PE fit model has 2 interactive components: the person component and the environment component. The person component is defined as a set of competencies, including biological health, sensory and motor skills, and cognitive function, and the environment component is defined in terms of demands. Demands are expressed as environmental “press” (ie, the strength with which the environment demands a response from the person). The concept of PE fit is represented in Figure 2, showing Lawton’s presscompetence model,28 wherein an individual with a given competence interacts with an environmental situation having a given “press” or demand. The central line, labeled “adaptation level,” represents a theoretical level where the environmental press level matches the competence of the person. In terms of physical functioning, physical barriers in the environment are not necessarily problems per se. Instead, the magnitude of problems differs for different people, depending on each person’s competence level.28 If environmental press is too strong or too weak relative to the level of competence, negative affect and maladaptive behavior will occur. In a related concept, the environmental docility hypothesis, Lawton and Simon26 postulated that individuals with lower competence are more sensitive than those with higher competence to the demands of their environment. This phenomenon is portrayed in Figure 2 by the relatively narrow bands of maximum comfort and performance associated with low competence compared with the wider bands associated with high competence. Home and neighborhood environments, therefore, become critically important for individuals with less physical and cognitive capacity.33

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Lawton’s ecological model was developed to explain the interaction between an individual and his or her home environment; however, the model’s focus is on the home environment, and the context of outdoor public space is very different in terms of the ideal level of press. Whereas the home environment optimally will be adapted to an individual with a specific competence level (expected to decline with age), public space serves the entire community and a wide range of competence levels. Therefore, in extending this concept to the public health realm, the ideal amount of press would be different than that for an individual’s home environment. Clinically Oriented Conceptual Models and Assessments Many physical functioning conceptual models acknowledge environmental factors, but the majority of these models were developed to guide the assessment and treatment of clinical endpoints. Such models offer a comprehensive portrayal of the individual’s process of adaptation to shifting environmental demands or an altered “performance capacity” (eg, diminished physical or cognitive ability),22,34 and related assessments reflect these considerations. Outcomes typically included in such assessments are improvement of physical capacity, behavior modification to compensate for lower capacity or a more demanding environment, modification of expectations and goals, and modification of the home environment. For example, both the Canadian Occupational Performance Measure, based on the Canadian Model of Occupation Performance,34 and the Occupational Performance History Interview II,22 rooted in the Model of Human Occupation, are specifically intended for use as initial assessments on which occupational therapy goals and treatment are developed.

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Figure 2. Lawton’s press-competence model. Reprinted with permission of the American Psychological Association from: Lawton MP, Nahemow L. Ecology and the aging process. In: Eisdorfer C, Lawton MP, eds. The Psychology of Adult Development and Aging. Washington, DC: American Psychological Association; 1973. Copyright 1973 by the American Psychological Association.

Thus, although environmental, compensation, and coping factors are incorporated into these assessments, they are ultimately aimed at changing individual behaviors and environments. Furthermore, these and other assessments such as the Craig Handicap Assessment and Reporting Technique (CHART35) are intended for use in people with existing physical functioning deficits. This setting is different from public health and prevention-oriented models and assessments, most of which are intended for use in the general population with a wide range of limitations and a range of developmental stages. Thus, although clinically oriented conceptual models offer insight into the individual realm, they do not address July 2009

opportunities to measure and change community-level factors.

Physical Functioning and the Environment: Models and Assessments Focused on Community-Level Factors Although social, political, and public health conceptual models offer insight into the interaction between individual and community-level factors as they relate to aging, physical functioning, and disability,36 they tend to focus on broad dynamics of the system and environmental factors rather than physical functioning performance in the context of these environmental factors. The “univer-

sal design” movement,24 for example, promotes support of cognition, vision, hearing and speech, body function, and mobility through incorporation of community-level features usable by everyone. Although the individual is recognized as a key element in the dynamic, the focal point is the environment. Questionnaires such as the Craig Hospital Inventory of Environmental Factors,37 the Facilitators And Barriers Survey of environmental influences on participation among people with lower limb Mobility impairments and limitations (FABS/M),38 and the Community Health Environment Checklist39 assess environmental barriers and absence of supports in physical functioning, participation, and life satis-

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Assessment of Physical Functioning faction, but they do not measure an individual’s physical functioning performance. In sum, although many conceptual models and assessments of physical functioning acknowledge both capacity and environment, they tend to be aimed at either individuallevel or community-level factors.

Physical Functioning Assessment: Need for Improvement Recently, some authors14,15,40 – 44 have argued that traditional assessments of physical function do not adequately capture “real-life” functioning performance. If the interplay among an individual’s performance capacity, his or her habitual indoor and outdoor environments, and his or her compensatory and coping strategies are not characterized, an incomplete picture of physical functioning performance results.45– 49 Furthermore, no conceptual model is identified in the description of many physical functioning assessments. Failure of existing assessments to specify the context in which respondents should report their functioning level limits the ability to fully capture and interpret such functional measures. For example, a different set of strategies is needed to negotiate life in a city high-rise apartment with an elevator versus a suburban 2-story house with a basement. Furthermore, when an assessment does not instruct respondents to report ability in performing tasks in a standard way (termed “capacity” by the ICF) or as usual performance, it is not possible to know how to correctly interpret the resulting data. Agree18 contended that the dynamic between the use of assistive technology and the amount of functional disability in the absence of modifications or adjustments is an important area of assessment. Agree defined residual disability as the degree of dis-

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ablement that remains after personal care or assistive technology has ameliorated some part of the total underlying need. She pointed out that with the use of equipment or human help, some individuals may report no problems at all—and, as such, this construct is an important, albeit underassessed, component when considering limitations in physical functioning. This important dynamic is identifiable in a cross-sectional assessment conducted in a nationally representative sample by the National Center for Health Statistics.50 In that study, 10.1% of the participants aged 45 to 64 years and 5.7% of those aged ⱖ65 years reported longterm use of an assistive technology, yet considered themselves as having no limitations. Thus, these individuals forestalled classifying themselves as having activity limitations through compensation strategies that modified their environments. Use of compensatory and coping strategies is common among people with reduced performance capacity. In a study of 248 older adults with osteoarthritis, only 3 respondents reported no adaptations in performing activities related to personal care, mobility, and household tasks, and they valued activities such as socializing, physical activities, and traveling.20 Thus, failure to capture such strategies when characterizing physical functioning performance precludes a comprehensive portrayal of an individual’s real-life performance. Furthermore, although research suggests that compensatory strategies reduce difficulty in performing physical functions,14,50 human help frequently is used as an endpoint to represent “poor functioning.”51 Although the assumption that human help is utilized in the most severe limitations in physical functioning, Hoenig and colleagues’15 research suggests that the choice of compensation strategy is determined, in part, by logistical factors rather than by

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severity. Individuals living with another person were more likely to use human help than to use of an assistive device. Research on strategies to compensate for increased environmental press among individuals with high performance capacity is not well addressed in the physical functioning literature. Weiss et al defined a compensatory strategy as “a way of achieving a result that is adopted frequently in the face of physical impairment or limitation and under usual conditions.”29(p1217) In Hoenig and colleagues’ 2006 study,15 those individuals with the best physical performance did not use compensatory strategies, but the context of the study was indoor mobility and, therefore, presumably less demanding than outdoor mobility. Weiss et al also pointed out that, under demanding environmental conditions, even the healthiest person would “appreciate a cane.” Barriers to neighborhood walking in the general population have been characterized extensively in the physical activity literature as lack of perceived personal safety, open space, and connected street networks, as well as high traffic volumes, among other features.52,53

A New Conceptual Model Describing Assessment of Physical Functioning Performance The PF-E conceptual model (Fig. 3) was developed to address the need for physical functioning assessments that reflect performance capacity, environmental factors, and coping and compensation strategies. This conceptual model is intended to serve as a guide for developing new and extending existing perceived and performance-based physical functioning assessments targeted toward middle-aged and older people living in urban and suburban areas.

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Figure 3. The Physical Functioning Assessment in Your Environment (PF-E) conceptual model, integrating the indoor and outdoor environments, compensation strategies, and physical functioning performance.

The model also highlights the opportunity to separately characterize home and neighborhood environments to identify possible areas of environmental improvement. Functions described by the PF-E conceptual model include those that support mobility in a broad sense, such as walking, climbing stairs, reaching, standing, seeing and reading, hearing, spatial orientation, and transportation, among others. The individual is represented in the box labeled “individual performance capacity” in Figure 3. A range of performance capacity levels is shown, from “high” at the top of the box to “low” in the bottom part of the box. This range of capacities can be thought of as differences among people or differences within an individual over time as they experience decline in functioning capacity.

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Within each unique environment, barriers and supports are present. Although neighborhood barriers and supports to physical functioning are unique for each community assessed, home supports and barriers will be unique to individuals (unless they are living in an institutional setting). Thus, it is clear that habitual existence in public and private environments collectively characterizes an individual’s unique environment. More-favorable environments are represented in the upper part of Figure 3, whereas less-favorable environments are shown at the bottom of the figure. Environmental press is shown in Figure 3 with arrows pointing from the neighborhood, through the indoor environment toward the individual’s performance capacity. The thick arrow portrays the larger influence of

environmental press on those individuals with lower performance capacity; a thinner arrow shows that environmental press has little impact on those individuals with high performance capacity. These arrows are dashed to distinguish them from the arrows to their right depicting the immediate process of physical functioning performance. The compensation strategies represented in this model are considered “performance qualifiers” within the ICF. Compensation strategies are used by individuals with a performance capacity in the range below “high” and by individuals who live in a less-favorable environment (those with greater press). Differences in use of compensation strategies are represented in Figure 3 by thicker arrows near the bottom of the individual performance capacity box, in-

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Assessment of Physical Functioning dicating more compensation, and by thinner arrows near the middle of the box, representing less reliance on these strategies. The illustration shows that individuals with a high level of performance capacity living in a favorable environment do not use compensation strategies for physical functioning performance. Positive compensation strategies (eg, use of a hearing aid) enhance a person’s performance capacity and improve physical functioning performance. Use of human help also is considered a compensation strategy, and this assistance may come from a family member, friend, or paid helper. Examples of human help include direct assistance, such as receiving help climbing stairs, traveling to a destination, or the performance of a task such as grocery shopping. Whereas the act of modifying the existing environment or moving to a new environment is considered compensation, once that transition has occurred, the new or modified environment simply becomes part of the habitual environment. In sum, integration of an individual’s unique environment, as well as compensation and coping strategies, into assessment of physical functioning performance is a key aspect of the model because such factors likely influence performance of an activity. The model is inclusive of a range of physical and cognitive functions but is meant to target assessment of functions relevant to an individual’s life. The model is intended for use in developing assessments for clinical settings, as well as the public health and policy realms. Characterization of the neighborhood environment draws attention to relevant community-level factors that may be changed through legislation.

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Rationale for Development of the PF-E Model The PF-E conceptual model was created to motivate the development of physical functioning assessments that include a range of individual and community-level factors that affect performance. Although this model builds upon and extends existing seminal conceptualizations, it also differs from them in key ways. The model presented here has drawn upon the ICF’s conceptualization of capacity and performance. In Figure 1, a shaded circle has been drawn around the area of focus for the PF-E model, which includes some aspects of ICF chapters on products and technology, the natural environment and human-made changes to environment, and support and relationships. These aspects are included because they are modifiable and may directly influence an individual’s capacity for physical functioning. Although the ICF does not propose a specific conceptualization of physical functioning per se, the PF-E model highlights physical functioning within the context of relevant home and community environmental factors. For example, in Figure 1, both use of a cane for walking and an environmental barrier such as low light would be classified into the “environmental factors” box (although they are classified into separate ICF chapters), whereas they are portrayed separately in Figure 3. Delineation of such factors allows conceptualization of interplay between the individual and different facets of the environment. In addition, the PF-E differs from the ICF in that not all of the compensation strategies proposed in the PF-E are classified in the ICF. For example, modifying the way an activity is performed to make it easier is not included in the ICF.

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The PF-E model incorporates ideas from Lawton26 –28; however, the public health approach presented here differs from his individually tailored approach to person-environment fit. Whereas Lawton’s research focused heavily on the home environment, the PF-E model incorporates the home and neighborhood environments. This is relevant because identifying the ideal amount of environmental press will be necessarily be different in someone’s home versus in the community.

Summary and Future Research Needs There is a need to improve understanding of physical functioning within an individual’s unique habitual environment.25,54 Capturing this information as early as midlife, when age-related physical functioning problems often develop,55 is valuable in characterizing decline in functioning across time. The proposed model is meant to guide assessment of a wide range of physical functioning tasks in middle-aged and older suburban and urban dwellers. This could include assessment of a group with diverse performance levels or of individuals with varying performance levels across time. The PF-E model is preliminary and, as such, will require empirical testing and conceptual refinement. It is presented as a comprehensive, but not all-encompassing, approach to assessment. For example, the environments considered do not necessarily include the workplace environment. This is a limitation of the model, because people habitually travel outside the realm presented. Future versions of the PF-E model may include a broader environment. The specification of the neighborhood environment as unique is important because it allows for identification of a community’s supports and barriers to physical functioning. July 2009

Assessment of Physical Functioning Although these differences could include nonmodifiable factors such as presence of hills, other identified barriers such as lack of pedestrian crosswalks could be improved through legislation. Thus, application of the model in assessing functioning within communities could help to improve functioning at the community level. Although efforts to make cities accessible for people with overt disabilities have been visible, making communities friendlier to people with milder physical functioning problems has not been widespread. Our emphasis on compensation strategies also is valuable beyond quantifying physical functioning performance because key compensation behaviors, once identified, can be modified. Additionally, intervention with an appropriate assistive device may improve physical functioning performance. Development of physical functioning assessments based on the PF-E model has the potential to add reallife depth to these assessments. Furthermore, gathering information on communities and individuals using a well-conceptualized and integrated model can eventually stimulate researchers and policy makers to make changes that would reduce demands on people with functional limitations and increase support for promoting community-level physical functioning. Dr Tomey provided concept/idea/project design. Both authors provided writing. Dr Sowers provided consultation (including review of manuscript before submission). Dr Tomey and Dr Sowers are funded, in part, with support from the National Institutes of Health, Department of Health and Human Services, through the National Institute on Aging (grants AG17104 and AG29835). This article was received July 11, 2008, and was accepted March 28, 2009. DOI: 10.2522/ptj.20080213

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References 1 Verbrugge LM, Jette AM. The disablement process. Soc Sci Med. 1994;38:1–14. 2 Royall DR, Lauterbach EC, Kaufer D, et al; Committee on Research of the American Neuropsychiatric Association. The cognitive correlates of functional status: a review from the Committee on Research of the American Neuropsychiatric Association. J Neuropsychiatry Clin Neurosci. 2007;19:249 –265. 3 Wolinsky FD, Miller DK, Andresen EM, et al. Effect of subclinical status in functional limitation and disability on adverse health outcomes 3 years later. J Gerontol A Biol Sci Med Sci. 2007;62:101–106. 4 Stevens JA, Olson S. Reducing falls and resulting hip fractures among older women. MMWR Recomm Rep. 2000;49(RR-2): 3–12. 5 Schieman S, Plickert G. Functional limitations and changes in levels of depression among older adults: a multiple-hierarchy stratification perspective. J Gerontol B Psychol Sci Soc Sci. 2007;62:S36 –S42. 6 Fried TR, Bradley EH, Williams C, Tinetti ME. Functional disability and health care expenditures for older persons. Arch Intern Med. 2001;161:2602–2607. 7 Ervin RB. Prevalence of functional limitations among adults 60 years of age and over: United States, 1999 –2002. Adv Data. 2006;375:1–7. 8 International Classification of Functioning, Disability and Health. Available at: http://www.who.int/classifications/icf/ site/index.cfm. Accessed May 2, 2008. 9 Jette AM. Toward a common language for function, disability, and health. Phys Ther. 2006;86:726 –734. 10 Schootman M, Andresen EM, Wolinsky FD, et al. Neighborhood conditions and risk of incident lower-body functional limitations among middle-aged African Americans. Am J Epidemiol. 2006;163:450 – 458. 11 Balfour JL, Kaplan GA. Neighborhood environment and loss of physical function in older adults: evidence from the Alameda County Study. Am J Epidemiol. 2002; 155:507–515. 12 Dixon RA, Ba¨ckman L. Concepts of compensation: integrated, differentiated and Janus-faced. In: Dixon RA, Ba¨ckman L, eds. Compensating for Psychological Deficits and Declines: Managing Losses and Promoting Gains. Mahwah, NJ: Erlbaum; 1995:3–19. 13 Fried LP, Bandeen-Roche K, Williamson JD, et al. Functional decline in older adults: expanding methods of ascertainment. J Gerontol A Biol Sci Med Sci. 1996;51:M206 –M214. 14 Fried LP, Young Y, Rubin G, BandeenRoche K; WHAS II Collaborative Research Group. Self-reported preclinical disability identifies older women with early declines in performance and early disease. J Clin Epidemiol. 2001;54:889 –901. 15 Hoenig H, Ganesh SP, Taylor DH Jr, et al. Lower extremity physical performance and use of compensatory strategies for mobility. J Am Geriatr Soc. 2006;54:262–269.

16 West SK, Munoz B, Rubin GS, et al. Compensatory strategy use identifies risk of incident disability for the visually impaired. Arch Ophthalmol. 2005;123:1242–1247. 17 Baltes PB, Baltes MM, eds. Successful Aging: Perspectives From the Behavioral Sciences. New York, NY: Cambridge University Press; 1990. 18 Agree EM. The influence of personal care and assistive devices on the measurement of disability. Soc Sci Med. 1999;48:427– 443. 19 Keysor J, Jette AM, Haley SM. Development of the Home and Community Environment (HACE) instrument. J Rehabil Med. 2005;37:37– 44. 20 Gignac MA, Cott C, Badley EM. Adaptation to disability: applying selective optimization with compensation to the behaviors of older adults with osteoarthritis. Psychol Aging. 2002;17:520 –524. 21 Bucks RS, Ashworth DL, Wilcock GK, Siegfried K. Assessment of activities of daily living in dementia: development of the Bristol Activities of Daily Living Scale. Age Ageing. 1996;25:113–120. 22 Kielhofner G, Burke JP, Igi CH. A model of human occupation, part 4: assessment and intervention. Am J Occup Ther. 1980;34: 777–788. 23 Townsend E, ed. Enabling Occupation: An Occupational Therapy Perspective. Ottawa, Ontario, Canada: Canadian Association of Occupational Therapists Publications ACE; 2002. 24 Story MF, Mueller JL, Mace RL. The Universal Design File: Designing for People of All Ages and Abilities. Rev ed. Raleigh, NC: Center for Universal Design, North Carolina State University; 1998. 25 Schneidert M, Hurst R, Miller J, Ustu ¨ n B. The role of environment in the International Classification of Functioning, Disability and Health (ICF). Disabil Rehabil. 2003;25:588 –595. 26 Lawton MP, Simon B. The ecology of social relationships in housing for the elderly. Gerontologist. 1968;8:108 –115. 27 Lawton MP. Three functions of the residential environment. In: Pastalan LA, Cowart ME, eds. Lifestyles and Housing of Older Adults: The Florida Experience. Binghamtom, NY: Haworth Press Inc; Journal of Housing for the Elderly. 1989:35–50. 28 Lawton MP. Competence, environmental press, and the adaptation of older people. In: Lawton MP, Windley PG, Byerts TO, eds. Aging and the Environment. New York, NY: Springer; 1982:33–59. 29 Weiss CO, Hoenig HM, Fried LP. Compensatory strategies used by older adults facing mobility disability. Arch Phys Med Rehabil. 2007;88:1217–1220. 30 Centers for Disease Control and Prevention. Prevalence of disabilities and associated health conditions among adults— United States, 1999. MMWR Morb Mortal Wkly Rep. 2001;50:120 –125. 31 Adams PF, Wilson Lucas J, Barnes PM. Summary health statistics for U.S. population: National Health Interview Survey, 2006. National Center for Health Statistics. Vital Health Stat. 2008:10(236).

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Assessment of Physical Functioning 32 Lewin K. Field Theory in Social Science. New York, NY: Harper & Brothers; 1951. 33 Oswald F, Hieber A, Wahl H, Mollenkopf H. Ageing and person: environment fit in different urban neighbourhoods. Eur J Ageing. 2005;2:88 –97. 34 Carswell A, McColl MA, Baptiste S, et al. The Canadian Occupational Performance Measure: a research and clinical literature review. Can J Occup Ther. 2004;71:210 – 222. 35 Whiteneck G, Brooks CA, Charlifue S, et al. Guide for use of the CHART: Craig Handicap Assessment and Reporting Technique. Available at: http://www. craighospital.org/research/CHART%20 Manual.pdf. Accessed May 2, 2009. 36 Putnam M. Linking aging theory and disability models: increasing the potential to explore aging with physical impairment. Gerontologist. 2002;42:799 – 806. 37 Whiteneck G, Meade MA, Dijkers M, et al. Environmental factors and their role in participation and life satisfaction after spinal cord injury. Arch Phys Med Rehabil. 2004;85:1793–1803. 38 Gray DB, Hollingsworth HH, Stark S, Morgan KA. A subjective measure of environmental facilitators and barriers to participation for people with mobility limitations. Disabil Rehabil. 2008;30: 434 – 457. 39 Stark S, Hollingsworth HH, Morgan KA, Gray DB. Development of a measure of receptivity of the physical environment. Disabil Rehabil. 2007;29:123–137. 40 Peel C, Sawyer Baker P, Roth DL, et al. Assessing mobility in older adults: the UAB Study of Aging Life-Space Assessment. Phys Ther. 2005;85:1008 –1119.

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41 Patla AE, Shumway-Cook A. Dimensions of mobility: defining the complexity and difficulty associated with community mobility. J Aging Phys Act. 1999;7:7–19. 42 Shumway-Cook A, Patla AE, Stewart A, et al. Environmental demands associated with community mobility in older adults with and without mobility disabilities. Phys Ther. 2002;82:670 – 681. 43 Bandinelli S, Pozzi M, Lauretani F, et al. Adding challenge to performance-based tests of walking: the Walking InCHIANTI Toolkit (WIT). Am J Phys Med Rehabil. 2006;85:986 –991. 44 Iwarsson S, Wahl HW, Nygren C, et al. Importance of the home environment for healthy aging: conceptual and methodological background of the European ENABLE-AGE Project. Gerontologist. 2007;47:78 – 84. 45 McHorney CA, Kosinski M, Ware JE Jr. Comparisons of the costs and quality of norms for the SF-36 health survey collected by mail versus telephone interview: results from a national survey. Med Care. 1994;32:551–567. 46 Coyne KS, Margolis MK, Gilchrist KA, et al. Evaluating effects of method of administration on walking impairment questionnaire. J Vasc Surg. 2003;38:296 –304. 47 Kelly-Hayes M, Jette AM, Wolf PA, et al. Functional limitations and disability among elders in the Framingham Study. Am J Public Health. 1992;82:841– 845. 48 Survey of Income and Program Participation (SIPP) 2004 panel questionnaire functional limitations and disability section. Available at: http://www.bls.census.gov/ sipp/top_mod/2004/quests/2004w5tm. pdf. Accessed May 6, 2008.

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49 Haywood KL, Garratt AM, Fitzpatrick R. Older people specific health status and quality of life: a structured review of selfassessed instruments. J Eval Clin Pract. 2005;11:315–327. 50 Madans J, Rasch B, Altman B. Exploring the impact of assistive device use on disability measurement. Available at: www. cdc.gov/nchs/ppt/citygroup/madans_ rasch_altman.ppt. Accessed May 14, 2008. 51 Boggatz T, Dijkstra A, Lohrmann C, Dassen T. The meaning of care dependency as shared by care givers and care recipients: a concept analysis. J Adv Nurs. 2007; 60:561–569. 52 Sallis JF, Cervero RB, Ascher W, et al. An ecological approach to creating active living communities. Annu Rev Public Health. 2006;27:297–322. 53 Trayers T, Lawlor DA. Bridging the gap in health inequalities with the help of health trainers: a realistic task in hostile environments? A short report for debate. J Public Health (Oxf). 2007;29:218 –221. 54 Pollard B, Johnston M. The assessment of disability associated with osteoarthritis. Curr Opin Rheumatol. 2006;18:531–536. 55 Pope SK, Sowers MF, Welch GW, Albrecht G. Functional limitations in women at midlife: the role of health conditions, behavioral and environmental factors. Women’s Health Issues. 2001;11:494 –502.

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Scholarships, Fellowships, and Grants News from the Foundation for Physical Therapy Applications Being Accepted for Foundation Funding

Access to the online system, as well as to the guidelines and application instructions for these and other Foundation programs, can be found at www.Foundationfor PhysicalTherapy.org under “Program Information.” For additional information, contact Karen Chesbrough, scientific program administrator, at 800/875-1378, ext 8505, or [email protected].

Schools receiving Honorable Mention awards for raising at least $3,000 include (schools donating at least $6,000 are shown in italics): Arcadia University; Boston University–Sargent College; Emory University; Indiana University; Ithaca College; Marquette University; Mayo School of Health Science; MGH Institute of Health Professions; Midwestern University; Quinnipiac University; Rosalind Franklin University of Medicine and Science; Sacred Heart University; SUNY Upstate Medical University; University of Alabama at Birmingham; University of Delaware; University of Evansville; University of Iowa; University of Oklahoma; University of Pittsburgh; University of Southern California; University of Wisconsin– Madison; and Virginia Commonwealth University.

Georgia State–Marquette Challenge Raises $200,050

Special Awards were presented to the following:

The Foundation for Physical Therapy’s online application system is now accepting applications for the 2009 Florence P. Kendall Doctoral Scholarships and 2010 research grants. The Foundation has 2 research grants currently available. Applications are due at 10:00 am (ET), August 19, 2009.

The Georgia State–Marquette Challenge was a great success as physical therapist students and physical therapist assistant students from 63 schools raised $200,050 for the Foundation. This year’s remarkable total pushes the total funds raised by the Marquette Challenge to more than $1,550,000 over its 21year history. The top student fundraising efforts were at the following schools: First Place: University of Miami—$17,301 Second Place: University of Colorado, Denver—$16,950 Third Place: Georgia State University— $11,309

July 2009

Most Successful Newcomer: Sacred Heart University— $10,365 Biggest Stretch School: University of Pittsburgh— $9,115 Most Successful PTA School: Somerset Community College— $2,175 The Foundation would like to recognize Marquette University students for annually matching the 2nd place total. To see a complete list of participating schools, visit the Foundation’s Web site at www. FoundationforPhysicalTherapy.org. In the latest grant cycle, 3 grants were supported by the Challenge. The 20th Marquette Challenge, co-sponsored by the University of Pittsburgh, fully funded a $40,000

research grant awarded to Susanne Morton, PT, PhD, University of Iowa, for her research project, “Motor Adaptation: A Novel Method for Retraining Locomotion Following Stroke.” The Challenge helped fund the 2009 Pediatric Research Grant Recipient, Jill C. Heathcock, PT, PhD, MPT, Ohio State University, for her project, “Training in Infants With Neonatal Stroke,” and the 2009 Geriatric Research Grant Recipient, Michael Lewek, PT, PhD, University of North Carolina Chapel Hill, for his project, “Biomechanical Influences on Motor Learning During Locomotor Retraining Post-Stroke.” The Challenge will also fund a Promotion of Doctoral Studies (PODS) award to be announced this summer. The Miami–Marquette Challenge kicks off at the National Student Conclave in Miami, Florida, on October 29, 2009.

21st Annual Split Raffle Raises $117,000 The 2009 Split Raffle raised $117,000 for the Foundation and its mission. Marilyn Moffat, PT, DPT, PhD, FAPTA, CSCS, and Master of Ceremonies Charles Wetherington announced the winners at the Foundation’s Dinner Dance at PT 2009 in Baltimore. Special thanks to this year’s volunteers who telephoned Foundation supporters urging participation in the Split Raffle: Caroline Bloom, PT; Melanie Gillar, PT, DPT, MA; Timothy Schell, PT; Brad Thuringer, PTA; and Louise Yurko, PT, MAEd. The Split Raffle drawing was conducted by the accounting firm of Larson Allen. At the Foundation’s office in Alexandria, Leena Saini,

Volume 89 Number 7 Physical Therapy ■ 715

Scholarships, Fellowships, and Grants CPA, manager of Larson Allen’s Nonprofit and Government Division, randomly drew nine $2,000 prize winning numbers from the ticket tumbler, followed by the final $10,000 grand prize ticket number. After participating in the Split Raffle each year since its inception (and never winning), Marilyn Moffat is the winner of the $10,000 grand prize. “Needless to say I was astounded that my number was the last one pulled,” said Moffat. Moffat is donating at least half of the prize to the Marilyn Moffat Endowment Fund for Geriatric Research, an endowment fund she established in 2007 as part of the Foundation’s major gifts campaign. To view the complete list of Split Raffle winners, please visit the Foundation’s

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Web site at www.Foundationfor PhysicalTherapy.org. Special thanks to all Split Raffle participants. In its 21-year history, the Split Raffle has raised more than $1.8 million. In 2008, nearly 80% of funds raised were used to fund doctoral scholarships for physical therapists who are emerging researchers.

Recent Publications by Foundation-Funded Researchers “Recovery of Thumb and Finger Extension and Its Relation to Grasp Performance After Stroke,” by Catherine E. Lang, Stacy L. DeJong, and Justin A. Beebe, was published electronically in May 2009 by the Journal of Neurophysiology.

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716 ■ Physical Therapy Volume 89 Number 7

“Biomechanical Impairments and Gait Adaptations Post-Stroke: Multi-Factoral Associations,” was published electronically in May be the Journal of Biomechanics. One of the authors, Michael D. Lewek, PT, MPT, received a $15,000 PODS II scholarship in 2002 to study “Knee Alignment and the Progression of Osteoarthritis” and is the 2009 winner of the $40,000 Geriatric Research Grant to study “Biomechanical Influences on Motor Learning During Locomotor Retraining Post-Stroke.”

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PTi o n a l

Research

Catherine Lang, PT, PhD, received a PODS I award in 1999 and a PODS II award in 2000. She also was the winner of the MaryLou Barnes Award in 2000 for pursuing research in areas related to neurological physical therapy. Stacy DeJong, PT, MPT, MS, received the Florence P. Kendall Doctoral Scholarship in 2007 and a $7,500 PODS I scholarship in 2008. Justin A. Beebe, PT, PhD, received a $15,000 PODS II scholarship in 2007 and 2008.

Results

Recognition

“Brief Assessment of Motor Function: Content Validity and Reliability of the Oral Motor Scales,” appeared in the June 2009 issue of the American Journal of Physical Medicine Rehabilitation (88:464– 472). One of the authors, Holly L. Cintas, PT, PhD, PCS, received a Doctoral Training Research Grant in 1989. “Frontal Plane Lower Extremity Biomechanics During Walking in Boys Who Are Overweight Versus Healthy Weight,” appeared in the Summer 2009 issue of Pediatric Physical Therapy (21[2]:187–193). One of the authors, Amy McMillan, PT, PhD, received Doctoral Training Research Grants in 1992, 1994, and 1995. [DOI: 10.2522/ptj.2009.89.7.715]

July 2009

New Third Edition! Are you a…. Clinician or student with a compelling story to tell about a patient or group of patients? Administrator or educator who implemented a unique program? Physical therapist who modiÄed an approach to risk management?

YOU’VE got information your profession needs… … and this tool gives you a systematic, step-by-step way to share it.

Writing Case Reports: A How-to Manual, Third Edition A Favorite of Schools and Clinics Alike for More Than a Decade ge 1

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Dealing with likelihood ratios Using International ClassiÄcation of Functioning, Disability and Health (ICF) language Checklists customized for different types of case reports Online-only supplements with regularly updated examples Edited by Irene McEwen, PT, PhD, FAPTA, this manual helps you select a case, successfully address each component of a case report, write clearly and effectively about your decision making, survive the peer-review process, and more! Item No: C-12 Member price: $49.95 Nonmember price: $84.95 Student member price: $42.95

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How current is your reference library? Order your copies of APTA’s essential resources for daily practice and professional education today! NEW EDITION! Writing Case Reports: A How-To Manual for Clinicians, 3rd Edition A Favorite of Schools and Clinics Alike for More Than a Decade

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Now in its third edition, with brand-new content AND the breezy style and cartoon breaks of the original, Writing Case Reports: A How-to Manual, Third Edition, features: • Determining and describing meaningful change Order rder No. C-12 Regular price: $84.95 • Dealing with likelihood ratios Member price: $49.95 • Using International Student Member price: $42.95 Classification of Functioning, Disability and Health (ICF) language • Checklists customized for different types of case reports • Online-only supplements with regularly updated examples

Version 1.1 of the Interactive Guide to Physical Therapist Practice, With Catalog of Tests and Measures A comprehensive, one-stop, easy-to-use hyperlinked list of almost 500 specific tests and measures! It’s the CD version of APTA’s Guide to Physical Therapist Practice, Revised Second Edition—and much, much more: • More than 1,500 references for articles on reliability and validity, hyperlinked to abstracts on MEDLINE’s PubMed. • More than 1,000 screens of information about tests and measures, diagnostic classifications, and intervention categories. • Robust search capability includes searching by keyword and ICD-9-CM codes and the ability to search using multiple terms. • Downloadable PDF examination and evaluation, and patient satisfaction forms. Single User Order No. P-170 Regular price: $199

APTA Member price: $99.00 Student Member price: $89.00 Multi-User Order No. P-170B Regular price: $550.00

Edited by Irene McEwen, PT, PhD, FAPTA, PTJ’s former editor for case reports, with contributions from PTJ’s Editorial Board and other top researchers and practitioners, this manual helps you select a case, successfully address each component of a case report, write clearly and effectively about your decision making, survive the peer-review process, and more! (ISBN 978-1-931369-62-6, 2009)

APTA Member price: $225.00

Atlas of Human Anatomy, 4th Edition (paperback) AMA Manual of Style, 10th edition If you're submitting a manuscript to Physical Therapy, you'll want to refer to the 10th edition of the AMA Manual of Style for acceptable format and reference style. The AMA Manual offers a style widely accepted by health care and medical publishers. The manual includes tips on language usage, grammar, g and punctuation and offers a host of other oth handy sections, including pointers on medical m abbreviations and terminology. APTA APT is a distributor of the manual, so you can order directly from us! (ISBN (I 978-0-19-517633-9, 1,010 1 pages, 2007)

Order No. ILC-1-07 Regular price: $89.00

APTA Member price: $67.95

Updated in 2006 with new and revised surface, anatomical, and radiographic images, the ultimate anatomy atlas for clinical reference and patient education offers more than 540 of Frank Netter’s own accurate and beautifully rendered full-color illustrations of key anatomical structures and relationships in the human body. (ISBN 978-1-416033-85-1, 640 pages, 2006)

Order No: AMA-1-08 Regular price: $62.00

APTA Member price: $44.95

To order, call APTA’s Service Center at 800/999-APTA (2782), ext 3395, Mon-Fri, 8:30 am-6:00 pm, Eastern time, or order online at www.apta.org.

Product News Support Belt

Shoulder Pulley

Exercise Ball

OPTP

PrePak Products

Hygenic Corp

The Si-Loc belt features wide, medical-grade, non-slip pads to help it stay in place. This tapered, lightweight belt is wider at the innominate bones for even pressure distribution and has a nonbulky, breathable fabric for patient comfort. Other features are the dual hook-and-loop closures for adjustability and the anti-slip buckle.

Developed by a practicing physical therapist in 1985, the Home Ranger Shoulder Pulley was the first webbing-strap, over-the-door pulley. The device is designed to help increase and maintain range of motion in all planes of shoulder motion. It can be used in the clinic or in the patient’s home and comes with several accessories.

www.optp.com

www.prepakproducts.com

Hygenic offers the Thera-Band 9-inch Mini Ball designed for core muscle strengthening. Tactile, stretchable PVC makes the Mini Ball responsive to the touch and non-slip when placed against a hard surface. This product is intended for use in the clinic or at home by people of all ages. It has applications in rehabilitation and in wellness programs such as yoga and Pilates. An exercise poster is included. www.theraband.com

Bed

Brace

Tempur-Pedic Medical

Cascade Dafo Inc

Cold and Heat Therapy Tri W-G

The Pro-HealthCore Bed is specifically designed for health care professionals to provide relief from chronic pain. The bed has 3 Body-Zones that vary to provide support where the patient needs it most. Available through the company’s professional partners. www.tempurpedic.com

The DAFO Floor Reaction is a new brace for patients with excessive dorsiflexion, replacing the DAFO 1. The Floor Reaction was designed to improve crouching by blocking dorsiflexion and encouraging hip and knee extension. The brace includes a full-wrap inner liner made from soft, thin polyethylene for comfortable control of the heel, midfoot, and forefoot.

The Ultimate Coldn’Hot Pack is designed to provide a solution for patients who need pain relief without drugs. When frozen, the pack stays therapeutically flexible. The packs are sold directly to health care professionals only and are available in 2 new sizes: 7 in × 25 in and 9 in × 12 in. www.triwg.com

www.cascadedafo.com

July 2009

Volume 89 Number 7 Physical Therapy 719

Product News

Pediatric Stander

Orthotic Insoles

Topical Skin Refrigerant

Altimate Medical

KLM Labs

Gebauer Co

KLM Labs offers SUPERSTEP orthotic insoles based on its System Rx Technology. The insoles feature a poly shell and a comfortable, shock-absorbing top and bottom cover. They come in 3 levels of flexibility and pronation control: Max, a semirigid shell for firm arch support; Medium, a semi-flexible shell for intermediate arch control; and Mild, a forgiving shell for flexible arch support.

Gebauer’s Spray and Stretch topical anesthetic skin refrigerant replaces Fluori-Methane, which has been discontinued. This fine stream spray can be used in conjunction with the spray and stretch technique to effectively manage myofascial pain, restricted motion, trigger points, muscle spasms, and minor sports injuries.

Altimate introduces the EasyStand Bantam, a pediatric stander that has a supine option, giving the child even more positioning options. The Bantam is available in 2 different seating systems and 2 sizes and can include an optional Shadow Tray and a hand-operated hydraulic pump.

www.gebauerco.com/

www.klmlabs.com

www.easystand.com

Ad Index HPSO............................................................ Cover 2 Tempur-Pedic ..................................................... 621

APTA Products and Services

Hooked on Evidence ..................................... Cover 4 How Current Is Your Reference Library? .................. 718 Membership ................................................. Cover 3 Writing Case Reports, 3rd Edition .......................... 717

www.apta.org/adinfo For more information about these companies and their products

Index to General Information Found at: www.apta.org

Physical Therapy (PTJ)

Accredited Education Programs—Changes ....................................... Education Accredited Education Programs—Full Listings ................................... Education Awards ................................................... Member Services Bylaws ................................................. APTA Communities Call for Nominations ........................... APTA Communities Code of Ethics ....................................... APTA Communities

Abstracts of Papers Accepted for Presentation at Annual Conference (added every May) .......................... www.ptjournal.org/ misc/annualcon.dtl Submission Guidelines ......................... www.ptjournal.org/ misc/ifora.dtl In Memoriam ...........................................................March Index (Author/Subject) .......................................December Mary McMillan Lecture ..................................... November Membership Statistics .................................................June Presidential Address ........................................... November Statement of Ownership ....................................December

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July 2009