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Stroke Research and Treatment Poststroke Outcomes Guest Editors: Bruce Ovbiagele, Steve Kautz, Wayne Feng, and DeAnna L. Adkins

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  • Stroke Research and Treatment

    Poststroke Outcomes

    Guest Editors: Bruce Ovbiagele, Steve Kautz, Wayne Feng, and DeAnna L. Adkins

  • Poststroke Outcomes

  • Stroke Research and Treatment

    Poststroke Outcomes

    Guest Editors: Bruce Ovbiagele, Steve Kautz, Wayne Feng,and DeAnna L. Adkins

  • Copyright © 2014 Hindawi Publishing Corporation. All rights reserved.

    This is a special issue published in “Stroke Research and Treatment.” All articles are open access articles distributed under the CreativeCommons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the originalwork is properly cited.

  • Editorial Board

    Alison E. Baird, USADaniel Bereczki, HungaryRaymond T. Cheung, Hong KongGeoffrey A. Donnan, AustraliaValery Feigin, New ZealandMasayuki Fujioka, JapanAlexander Geurts, The NetherlandsGraeme Hankey, Australia

    Cathy Helgason, USATauheed Ishrat, USAScott Kasner, USAChelsea Kidwell, USADavid S. Liebeskind, USAChristopher S. Ogilvy, USABruce Ovbiagele, USADavid Reutens, Australia

    David Russell, NorwayStefan Schwab, GermanyShani Shenhar-Tsarfaty, IsraelVeronika Skvortsova, RussiaHelmuth Steinmetz, GermanyWai-Kwong Tang, Hong KongDavid Vaudry, FranceOsama O. Zaidat, USA

  • Contents

    Poststroke Outcomes, Bruce Ovbiagele, Steve Kautz, Wayne Feng, and DeAnna L. AdkinsVolume 2014, Article ID 828435, 2 pages

    Sex, Diastolic Blood Pressure, and Outcome afterThrombolysis for Ischemic Stroke, David Nathanson,Cesare Patrone, Thomas Nyström, and Mia von EulerVolume 2014, Article ID 747458, 7 pages

    Walking Adaptability after a Stroke and Its Assessment in Clinical Settings,Chitralakshmi K. Balasubramanian, David J. Clark, and Emily J. FoxVolume 2014, Article ID 591013, 21 pages

    Does Inhibitory Repetitive Transcranial Magnetic Stimulation Augment Functional Task Practice toImprove Arm Recovery in Chronic Stroke?, Dorian K. Rose, Carolynn Patten, Theresa E. McGuirk,Xiaomin Lu, and William J. TriggsVolume 2014, Article ID 305236, 10 pages

    Rasch Analysis of a New Hierarchical Scoring System for Evaluating Hand Function on the MotorAssessment Scale for Stroke, Joyce S. Sabari, Michelle Woodbury, and Craig A. VelozoVolume 2014, Article ID 730298, 10 pages

    TheAdverse Effect of Spasticity on 3-Month Poststroke Outcome Using a Population-Based Model,S. R. Belagaje, C. Lindsell, C. J. Moomaw, K. Alwell, M. L. Flaherty, D. Woo, K. Dunning, P. Khatri,O. Adeoye, D. Kleindorfer, J. Broderick, and B. KisselaVolume 2014, Article ID 696089, 5 pages

    Differences in Plantar Flexor Fascicle Length and Pennation Angle between Healthy and PoststrokeIndividuals and Implications for Poststroke Plantar Flexor Force Contributions, John W. Ramsay,Thomas S. Buchanan, and Jill S. HigginsonVolume 2014, Article ID 919486, 6 pages

    Poststroke Muscle Architectural Parameters of the Tibialis Anterior and the Potential Implications forRehabilitation of Foot Drop, John W. Ramsay, Molly A. Wessel, Thomas S. Buchanan, and Jill S. HigginsonVolume 2014, Article ID 948475, 5 pages

    Do Improvements in Balance Relate to Improvements in Long-DistanceWalking Function after Stroke?,Louis N. Awad, Darcy S. Reisman, and Stuart A. Binder-MacleodVolume 2014, Article ID 646230, 6 pages

    Autologous Bone MarrowMononuclear Cells Intrathecal Transplantation in Chronic Stroke,Alok Sharma, Hemangi Sane, Nandini Gokulchandran, Dipti Khopkar, Amruta Paranjape, Jyothi Sundaram,Sushant Gandhi, and Prerna BadheVolume 2014, Article ID 234095, 9 pages

    Functional Brain Correlates of Upper Limb Spasticity and Its Mitigation following Rehabilitation inChronic Stroke Survivors, Svetlana Pundik, Adam D. Falchook, Jessica McCabe, Krisanne Litinas,and Janis J. DalyVolume 2014, Article ID 306325, 8 pages

  • Changes in Predicted Muscle Coordination with Subject-Specific Muscle Parameters for Individualsafter Stroke, Brian A. Knarr, Darcy S. Reisman, Stuart A. Binder-Macleod, and Jill S. HigginsonVolume 2014, Article ID 321747, 7 pages

    Racial/Ethnic Differences in Poststroke Rehabilitation Outcomes, Charles Ellis, Hyacinth I. Hyacinth,Jamie Beckett, Wuwei Feng, Marc Chimowitz, Bruce Ovbiagele, Dan Lackland, and Robert AdamsVolume 2014, Article ID 950746, 12 pages

    Surface Electrical Stimulation for Treating Swallowing Disorders after Stroke: A Review of theStimulation Intensity Levels and the Electrode Placements, Marziyeh Poorjavad,Saeed Talebian Moghadam, Noureddin Nakhostin Ansari, and Mostafa DaemiVolume 2014, Article ID 918057, 7 pages

    Stroke Survivors Scoring Zero on the NIH Stroke Scale Score Still Exhibit Significant MotorImpairment and Functional Limitation, Brittany Hand, Stephen J. Page, and Susan WhiteVolume 2014, Article ID 462681, 6 pages

  • EditorialPoststroke Outcomes

    Bruce Ovbiagele,1 Steve Kautz,2,3 Wayne Feng,1,2 and DeAnna L. Adkins2,4

    1 Department of Neurology and Neurosurgery, College of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA2Department of Health Science & Research, College of Health Professions, Medical University of South Carolina,Charleston, SC 29425, USA

    3 Ralph H. Johnson VA Medical Center, Charleston, SC 29425, USA4Department of Neuroscience, College of Medicine, Medical University of South Carolina, Charleston, SC 29425, USA

    Correspondence should be addressed to Wayne Feng; [email protected]

    Received 18 September 2014; Accepted 18 September 2014; Published 14 October 2014

    Copyright © 2014 Bruce Ovbiagele et al.This is an open access article distributed under theCreativeCommonsAttributionLicense,which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

    Stroke is a leading cause of death and disability [1, 2]. Whilestrokemortality rates are decreasing due to improvedmedicaltreatment of the complications caused by acute stroke, thenumber of individuals living with the residual effects ofstroke is rising [3]. Currently, over 75% of patients survivea first stroke, and, of these individuals, 25% are left witha minor disability and 40% experience moderate-to-severedisabilities [4]. Furthermore, stroke patients are at high riskfor future vascular events, including recurrent stroke, puttingthem at a greater risk of death and further disability [5].With growing numbers of stroke survivors, there is an urgentneed to improve our understanding of the short- to long-term recovery process after stroke and to identify avenues fordeveloping efficacious therapeutic strategies to enhance post-stroke outcomes [6]. Government research funding agencies,like the National Institute of Neurological Diseases andStroke (NINDS), and nongovernmental research fundingorganizations, like the American Heart Association (AHA),have recognized the need for prioritizing poststroke out-comes research by developing strategic plans to explore waysin which the brain affected by stroke or endangered byrisk factors can preserve, protect, or recover function andsupporting consortia of multidisciplinary investigators andfacilities conducting collaborative investigation into strokeregeneration, resilience, and secondary prevention [7, 8].

    This special issue was developed to shed light on thevarious factors affecting the central and peripheral nervoussystem, which influence prognoses following a stroke, as wellas to portray promising new poststroke treatmentmodalities.

    In the systematic qualitative review conducted by C. Ellis andcolleagues, they found evidence of a racial disparity in post-stroke functional outcomes, with people of Black race, whohave the highest risk for stroke incidence and mortality [9],having poor outcomes after a stroke compared to their non-Hispanic White counterparts. Among 355 ischemic strokepatients who received thrombolytic therapy, D. Nathansonet al. observed that women experienced better recoveryoutcomes at 3 months after stroke than men and that lowerdiastolic blood pressures in women may contribute to thisgender difference. Findings from both studies highlight aneed to properly establish the contributors to demographicdisparities in stroke outcomes and implement interventionsto equitably enhance favorable sequela after stroke.

    M. Poorjavad et al. performed a systematic review onthe use of surface electric stimulation intensity and electrodeplacements to treat swallowing disorders after stroke, rec-ommending that additional research should focus on betterdiscrimination of the underlying neurophysiologic effects ofthese therapeuticmethods on swallowing function. In a phaseI study, A. Sharma and team evaluated the feasibility andpotential effects ofautologous bone marrow mononuclear-cell intrathecal transplantation in chronic stroke patients,noting that relatively younger patients, those who underwenttherapy within 2 years of stroke, and those with ischemicversus hemorrhagic strokes showed better recovery. On theother hand, D. K. Rose and colleagues found that low-frequency rTMS stimulating contralesional hemisphere didnot augment upper extremity motor ability in a population

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  • 2 Stroke Research and Treatment

    of individuals with chronic stroke. They suggest that thechronicity of their cohort (on average ≥5 years from strokeonset) and degree of upper motor impairment may have ledto an inability of rTMS to provide robust effects.

    Regaining the ability to locomote after a stroke is acomplex process. In particular, several factors directly orindirectly influence an individual’s capacity to walk afterstroke, including ankle muscle weakness, balance issues,and other factors. Five distinct articles investigate poststrokewalking from different perspectives. C. K. Balasubrama-nian and her group examined conceptual challenges forclinical measurement of walking adaptability and summa-rized the current state of clinical assessment for walkingadaptability in a systematic review, calling for developmentof a comprehensive well-tested clinical assessment tool formeasuring walking adaptability. While many people thinkimprovement in balance should lead to better long-distancewalking function after stroke, in their paper, L. N. Awadand colleagues challenge this premise, finding that improvingbalance may not necessarily be sufficient to improve long-distance walking function. J. W. Ramsay et al. contributedtwo papers to this journal issue, by carefully analyzing themuscular morphology and architecture in both dorsiflexorsand plantar flexors using combined imagingmodalities (MRIand ultrasound). In both papers, his team found no majordifferences between the affected and unaffected sides, orcompared to healthy controls, concluding that ankle muscleweakness is mainly neural in origin and is possibly secondaryto muscle activation failure. The same research group alsohas another article (led by Knarr) in which musculoskeletalsimulations of individuals after stroke with subject-specificmuscle force and activation data were created. This studyindicated that after a stroke, subject-specificmuscle force andactivation data may improve the ability of musculoskeletalsimulations to precisely predict muscle coordination.

    Spasticity hinders stroke motor recovery and affectsglobal outcomes [10]. This is quantitatively demonstrated inthe paper by S. R. Belagaje and colleagues in which presenceof spasticity was associated with a worsening of mRS by aver-age of 0.4 at 3 months after stroke. However, the pathologicalmechanisms of poststroke limb spasticity are not clear. S.Pundik et al. used fMRI and behavioral assessment to exam-ine stroke patients receiving motor learning and spasticitytherapy.They found that greater baseline spasticity correlatedwith higher fMRI activation in the ipsilesional thalamus,and, after therapy, greater mitigation of spasticity correlatedwith enhanced fMRI activation in the contralesional primarymotor, premotor, primary sensory, and associative sensoryregions, even when controlling changes in motor function.They concluded that the contralateral motor region may playa role in spasticity and represent a novel target for treatment.

    The widely used NIH stroke scale did not correlatewell with validated measures of upper extremity functionalimpairment, and so B. Hand and colleagues recommendthat its use should be restricted only to acute stroke studiesand clinical settings with the objective of reporting strokeseverity and not to studies of stroke recovery. By using Raschanalysis, J. S. Sabari et al. redesigned the two scales thatcomprise the hand function items on the motor assessment

    scale. The developed hand movements and hand activitiesitems each measure a unidimensional construct and canreliably measure stroke patients with different levels of handfunctional impairments.

    In conclusion, several opportunities exist to expand thescientific underpinnings and therapeutic options pertainingto poststroke outcomes. Periodic journal issues wholly ded-icated to covering the state of the science in this researcharea are crucial for identifying gaps, stimulating ideas, andplanning for future evidence-based treatments. That wasthe objective of this particular issue. Fortunately, improvingpoststroke outcomes is now clearly a priority item on theagenda of policy makers at various levels of medical researchfunding and healthcare delivery.We sincerely hope that theseongoing endeavors will lead tomajor breakthroughs in strokerecovery/rehabilitation and secondary prevention, therebyoptimizing our ability to further enhance outcomes afterstroke in the not-too-distant future.

    Bruce OvbiageleSteve KautzWayne Feng

    DeAnna L. Adkins

    References

    [1] D. T. Lackland, E. J. Roccella, A. F. Deutsch et al., “Factorsinfluencing the decline in stroke mortality a statement fromthe american heart association/american stroke association,”Stroke, vol. 45, no. 1, pp. 315–353, 2014.

    [2] “ Prevalence and most common causes of disability amongadults—United States, 2005,” Morbidity and Mortality WeeklyReport, vol. 58, pp. 421–426, 2009.

    [3] B. Ovbiagele, L. B. Goldstein, R. T. Higashida et al., “Forecastingthe future of stroke in the united states: a policy statementfrom the American heart association and American strokeassociation,” Stroke, vol. 44, no. 8, pp. 2361–2375, 2013.

    [4] A. S. Go,D.Mozaffarian, V. L. Roger et al., “Executive summary:heart disease and stroke statistics—2014 update: a report fromthe american heart association,” Circulation, vol. 129, no. 3, pp.399–410, 2014.

    [5] W. Feng, R. M. Hendry, and R. J. Adams, “Risk of recurrentstroke, myocardial infarction, or death in hospitalized strokepatients,” Neurology, vol. 74, no. 7, pp. 588–593, 2010.

    [6] S. C. Cramer, “Repairing the human brain after stroke: I.Mechanisms of spontaneous recovery,”Annals of Neurology, vol.63, no. 3, pp. 272–287, 2008.

    [7] National Institute of Neurological Disorders and Stroke,http://www.ninds.nih.gov/about ninds/groups/stroke prg/2012-stroke-prg-full-report.htm.

    [8] American Heart Association, 2014, http://my.americanheart.org/professional/research/fundingopportunities/supporting-information/asa-bugher-foundationcenters ucm 447128 article.

    [9] B. Kissela, A. Schneider, D. Kleindorfer et al., “Stroke in abiracial population: the excess burden of stroke among blacks,”Stroke, vol. 35, no. 2, pp. 426–431, 2004.

    [10] R. D. Zorowitz, P. J. Gillard, and M. Brainin, “Poststroke spas-ticity: sequelae and burden on stroke survivors and caregivers,”Neurology, vol. 80, no. 3, pp. S45–S52, 2013.

  • Clinical StudySex, Diastolic Blood Pressure, and Outcome afterThrombolysis for Ischemic Stroke

    David Nathanson,1,2,3 Cesare Patrone,1,2,3 Thomas Nyström,1,2,3 and Mia von Euler1,2,3,4

    1 Karolinska Institutet, Department of Clinical Science and Education, Södersjukhuset, Stockholm, Sweden2Department of Internal Medicine, Sjukhusbacken 10 Södersjukhuset, 118 83 Stockholm, Sweden3 Karolinska Institutet Stroke Research Network at Södersjukhuset, Stockholm, Sweden4Center for Gender Medicine, Karolinska Institutet, Stockholm, Sweden

    Correspondence should be addressed to David Nathanson; [email protected]

    Received 1 April 2014; Revised 24 July 2014; Accepted 2 September 2014; Published 15 September 2014

    Academic Editor: Wuwei Feng

    Copyright © 2014 David Nathanson et al. This is an open access article distributed under the Creative Commons AttributionLicense, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properlycited.

    Background. The goal of this study was to identify differences in risk factors and functional outcome between the two sexesin patients treated with thrombolysis for ischemic stroke. Methods. This cohort study audited data from patients treated withthrombolysis for ischemic stroke during a 3-year period at Södersjukhuset, Stockholm. Results. Of the 355 patients included inthe study, 162 (45%) were women and 193 (54%) were men. Women were older with a median age of 76 years; median age formen was 69 years (𝑃 < 0.0001). Diastolic blood pressure was lower for women compared to men (𝑃 = 0.001). At admission fewerwomen had a favorablemodified Rankin Scale score compared tomen (93.8% versus 99%,𝑃 = 0.008).Threemonths after dischargefunctional status did not differ significantly between the two sexes. Diastolic blood pressure was associated to functional outcomeonly in men when sex specific odds ratios were calculated (OR, 5.7; 95% CI, 1.7–20). Conclusion. The study indicates that femalesappear to gain a relatively greater benefit from thrombolytic therapy thanmen due to a better functional recovery. A higher diastolicblood pressure increases the risk for a worse prospective functional status in men.

    1. Introduction

    Stroke is the primary cause of severe acquired disability inadults with 500,000 new cases each year in Europe [1, 2].Administration of recombinant tissue plasminogen activator(rtPA), alteplase (Actilyse), within 4.5 h after onset of stroke,is an efficient treatment in patients where an intracerebralhemorrhage and other contraindications have been excluded[3–6]. Overall, women and men have a similar incidence forischemic cerebrovascular disease but women are more frequently hit by stroke later in life than men [7]. Several epidemio-logical studies have shown that women having more severestroke symptoms at admission, a worse prognosis, are lesslikely to return home and to live independently [8, 9] andhavean overall worse outcome after ischemic stroke than men [10,11]. However, some studies show a similar outcome for menand women after stroke [12, 13] and there is evidence thatwomen treated with tPA benefit at least as much as men [14–16]. Very recently a study from the prospective multinational

    Safe Implementation of Treatments in Stroke InternationalStrokeThrombolysis Register (SITS-ISTR) suggested a possi-ble larger beneficial effect of intravenous tPA in women com-pared with men [17]. Several recent studies have shown thesame risk of bleeding and positive treatment effects inpatients above 80 years old even though this age group has anoverall higher mortality than younger patients [4, 18–20]. Inthe studies that form the scientific base for rtPA treatment forischemic stroke, two thirds of the study populations weremen [6, 21, 22]. A recent published systematic review of theliterature did not find any major differences in the effect ofthrombolysis between men and women although there was atrend towards a lower risk of symptomatic intracranialhemorrhage in women [22].

    The primary aim of the present study was to investigatewhether there are any differences, independent of age, in thebasal risk factor profile between men and women withischemic stroke treated with thrombolysis. Furthermore, thestudy seeks to assess any associations between these risk

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  • 2 Stroke Research and Treatment

    factors, sex, and outcome after thrombolysis (e.g., functionalstatus and mortality after 3 months).

    2. Methods

    2.1. Participants. Since January 2008 all patients treated withrtPA for ischemic stroke at Södersjukhuset AB, a large teach-ing hospital in Stockholm, Sweden, have been consecutivelyregistered in a local registry and followed for 3 months. Thepresent study is a retrospective cohort study with prospec-tively collected data, including patients registered betweenJanuary 2008 and December 2010 (censor date December 31,2010) and discharged with a final diagnosis of transientischemic attack or stroke. The study was approved by theregional ethical review board of Stockholm, EPN: 2012/626-31/4. Informed consent was obtained from the study partici-pants.

    2.2. Data Collection. Patient age, sex, door-to-needle time,vascular risk factors, blood pressure at admittance, CT scanat admittance and 24 h after thrombolysis, National Instituteof Health Stroke Scale (NIHSS) score at admittance and atdischarge, and an estimated Modified Rankin Scale (mRS)score before strokewere recorded.NIHSS andmRS scores at 3months after strokewere obtained from the study participantsat a face-to-face visit 3-month after thrombolysis. We evalu-ated the differences between men and women according todemographic data and pre-existing risk factors for stroke.

    2.3. Clinical Assessment. Estimation of functional status wasmeasured by mRS, which was assessed according to the SafeImplementation ofThrombolysis in Stroke-Monitoring Study(SITS-MOST) protocol [20, 23]. All mRS scoring was per-formed by one mRS- and NIHSS-certified study nurse. mRSscore describing functional status for the patients before thestroke was collected within 48 hours after admission tohospital. A favourable mRS was defined as mRS ≤2.

    Blood pressure was measured according to clinical rou-tine in the left arm with the patient in a supine position.

    SICH was assessed by the National Institute of Neurolog-ical Disorders and Stroke (NINDS) definition (any deteriora-tion in NIHSS score or death within 7 days combined withintracerebral haemorrhage of any type on any posttreatmentimaging after the start of thrombolysis).

    2.4. Statistical Analyses. Means and standard deviations ormedians and interquartile ranges were used to describe thecharacteristics of the study participants. Normal distributionof the variables was tested with Shapiro-Wilk’s test. Theindependent samples 𝑡-test was used to compare means fornormally distributed continuous variables. Skewed dis-tributed variables were compared using Mann-Whitney test.Categorical variables were compared with 𝜒2 or Fisher’s exacttest. Logistic regression was used to investigate the associa-tions between sex and hypertension and the outcomes: (a)3-month favourable mRS and (b) 3-month mortality. First,univariable associations between outcomes, sex, and mortal-ity were estimated. The results for diastolic blood pressure

    that differed between sexes at baseline are presented.The cut-off level (diastolic blood pressure

  • Stroke Research and Treatment 3

    Table 1: Baseline characteristics.

    Total (𝑛 = 355) Men (𝑛 = 193) Women (𝑛 = 162) 𝑃 valueAge 71 (63–71) 69 (61–76) 76 (67–84)

  • 4 Stroke Research and Treatment

    Table 2: Modified Rankin Scale score before ischemic event and 3 months after rtPA.

    Men (𝑛 = 193) Women (𝑛 = 162) 𝑃 valueBASELINE mRS SCORE

    0 (no symptoms at all) 158 (82.7) 107 (66.5) 0.00041 (no significant disability despite symptoms) 20 (10.5) 35 (21.7) 0.0042 (slight disability) 11 (5.8) 9 (5.6) 0.93 (moderate disability) 1 (0.5) 8 (5.0) 0.0084 (moderate severe disability) 1 (0.5) 2 (1.2) 0.55 (severe disability) 0 (0) 0 (0) NS

    Favourable mRS score 189 (99.0) 151 (93.8) 0.0083-MONTHmRS SCORE

    0 (no symptoms at all) 56 (29.0) 42 (25.9) 0.21 (no significant disability despite symptoms) 38 (23.5) 33 (22.1) 0.82 (slight disability) 20 (12.3) 24 (16.1) 0.33 (moderate disability) 14 (7.3) 10 (6.7) 0.54 (moderate severe disability) 14 (8.6) 13 (8.7) 1.05 (severe disability) 5 (2.6) 4 (2.5) 0.86 (dead) 15 (9.3) 23 (15.4) 0.1

    Favourable mRS score 114 (70.4) 99 (66.4) 0.5Abbreviations: mRS: modified rankin scale.Data are described as 𝑛 (%); 𝑃 values were calculated and proportions were compared using the 𝜒2 test.

    calculated diastolic blood pressure

  • Stroke Research and Treatment 5

    Table 3: Interaction by gender and diastolic blood pressure and influence on (a) 3-month favorable mRS and (b) 3-month mortality.

    (a)

    𝑛 (% favourable mRS) Univariable Multivariablea Multivariableb Multivariablec

    OR 95% CI 𝑃 OR 95% CI 𝑃 OR 95% CI 𝑃 OR 95% CI 𝑃Sex1

    Men 162 (70.4) ReferenceWomen 149 (66.4) 0.8 0.5–1.3 0.5 0.9 0.5–1.8 0.9 1.7 0.7–3.9 0.2

    DBP2

    >90mmHg 68 (63.2) Reference90mmHg 46 (60.9) Reference90mmHg 22 (68.2) Reference90mmHg 46 (60.9) ReferenceFemale >90mmHg 22 (68.2) 5.3 0.9–32.0 0.07Male 90mmHg 23 (8.7) 0.05 0.01–2.0 0.4Male

  • 6 Stroke Research and Treatment

    did not. In this study the risk of death increased by 5% foreach 1mm increase of diastolic blood pressure [34]. A highdiastolic blood pressure might augment edema formation asthe major cause of cerebral edema is increased capillarypressure which in turn is dependent of mean arterial bloodpressure [34].

    Brain edema or recurrent stroke has not been assessed inthe current study, but it is likely that these complications canbe potential explanations for the association between higherdiastolic blood pressure and a worse functional outcome.

    We did not find any significant associations when theoutcome was 3-month mortality, although the sample mighthave been too small and with too few events to reveal anyassociations between sex, blood pressure, and mortality.

    In the present study, a larger proportion of the womenwere treated with antihypertensive agents, especially diuret-ics, prior to the stroke, which might have caused the lowerdiastolic blood pressure in women compared to men. Nev-ertheless, the associations between sex, blood pressure, andfunctional status remained significant when adjusted for anti-hypertensive treatment and acetyl salicylic acid treatment.

    Limitations of the present study are the relatively smallsample size and the observational study design that carriesa risk of residual and unmeasured confounding such asgeneral health prestroke and other socioeconomic factors[35]. Moreover, the population studied is a cohort with mildstroke symptoms which further limits the generalizability ofthe findings.However, in the Swedish national quality register(to which all hospitals treating stroke report) NIHSS was 7 in2013, which was the same as in the women, but slightly higherthan the NIHSS found in men in our cohort [36].

    The strength of the study is the internal validity as the datacollection and functional assessment weremade by onemRS-and NIHSS-certified study nurse.

    5. Conclusion

    In conclusion, this cohort study demonstrates differences inrisk factor profiles between men and women treated withthrombolytic therapy for ischemic stroke.

    The study indicates that females appear to gain a relativelygreater benefit from thrombolytic therapy than men due to abetter functional recovery. A higher diastolic blood pressureincreases the risk for a worse prospective functional status inmen but seems to be of less significance in women.

    Conflict of Interests

    The authors declare that there is no conflict of interestsregarding the publication of this paper.

    Acknowledgments

    The authors thank Linda Ekström, research nurse at theDepartment of Internal Medicine Södersjukhuset AB, whometiculously recruited all patients and performed all data col-lection. They thank H. Pettersson and Lina Benson (Karolin-ska Institutet, Department of Clinical Science and Education,

    Södersjukhuset, Stockholm) for their excellent statisticaladvice. Financial support was provided by the Depart-ment of Internal Medicine, Södersjukhuset AB. Dr. DavidNathansonhas received grants fromStiftelsen Sigurd andElsaGoljes minne. Dr. Cesare Patrone andThomas Nyström havereceived grants from the SwedishHeart and Lung foundation.Dr. Mia von Euler has received grants from Bliwa researchfoundation.

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    [2] T. Russo, G. Felzani, and C. Marini, “Stroke in the very old: asystematic review of studies on incidence, outcome, andresource use,” Journal of Aging Research, vol. 2011, Article ID108785, 6 pages, 2011.

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    [5] T. G. Kwiatkowski, R. B. Libman, M. Frankel et al., “Effects oftissue plasminogen activator for acute ischemic stroke at oneyear,”TheNew England Journal of Medicine, vol. 340, no. 23, pp.1781–1787, 1999.

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    [11] M. K. Kapral, H. Wang, P. C. Austin et al., “Sex differences incarotid endarterectomy outcomes: results from the OntarioCarotid Endarterectomy Registry,” Stroke, vol. 34, no. 5, pp.1120–1124, 2003.

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    [13] S. Pundik, L. McWilliams-Dunnigan, K. L. Blackham et al.,“Older age does not increase risk of hemorrhagic complicationsafter intravenous and/or intra-arterial thrombolysis for acutestroke,” Journal of Stroke and Cerebrovascular Diseases, vol. 17,no. 5, pp. 266–272, 2008.

  • Stroke Research and Treatment 7

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    [16] N. Shobha, P. N. Sylaja, M. K. Kapral, J. Fang, and M. D. Hill,“Differences in stroke outcome based on sex,”Neurology, vol. 74,no. 9, pp. 767–771, 2010.

    [17] S. Lorenzano, N. Ahmed, A. Falcou et al., “Does sex influencethe response to intravenous thrombolysis in ischemic stroke?:Answers from safe implementation of treatments in stroke-international stroke thrombolysis register,” Stroke, vol. 44, no.12, pp. 3401–3406, 2013.

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  • Review ArticleWalking Adaptability after a Stroke and Its Assessment inClinical Settings

    Chitralakshmi K. Balasubramanian,1 David J. Clark,2,3 and Emily J. Fox4,5

    1 Department of Clinical and Applied Movement Sciences, University of North Florida, 1 UNF Drive, Jacksonville, FL 32224, USA2 Brain Rehabilitation Research Center (151A), Malcom Randall VA Medical Center, 1601 SW Archer Roadd,Gainesville, FL 32608, USA

    3Department of Aging and Geriatric Research, University of Florida, Gainesville, FL 32603, USA4Department of Physical Therapy, University of Florida, P.O. Box 100154, Gainesville, FL 32610-0154, USA5 Brooks Rehabilitation, Jacksonville, FL 32216, USA

    Correspondence should be addressed to Chitralakshmi K. Balasubramanian; [email protected]

    Received 15 April 2014; Accepted 6 June 2014; Published 28 August 2014

    Academic Editor: Steve Kautz

    Copyright © 2014 Chitralakshmi K. Balasubramanian et al. This is an open access article distributed under the Creative CommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work isproperly cited.

    Control of walking has been described by a tripartite model consisting of stepping, equilibrium, and adaptability. This reviewfocuses on walking adaptability, which is defined as the ability to modify walking to meet task goals and environmental demands.Walking adaptability is crucial to safe ambulation in the home and community environments and is often severely compromisedafter a stroke. Yet quantification of walking adaptability after stroke has received relatively little attention in the clinical setting.Theobjectives of this reviewwere to examine the conceptual challenges for clinicalmeasurement of walking adaptability and summarizethe current state of clinical assessment for walking adaptability. We created nine domains of walking adaptability from dimensionsof communitymobility to address the conceptual challenges inmeasurement and reviewed performance-based clinical assessmentsof walking to determine if the assessments measure walking adaptability in these domains. Our literature review suggests the lackof a comprehensive well-tested clinical assessment tool for measuring walking adaptability. Accordingly, recommendations forthe development of a comprehensive clinical assessment of walking adaptability after stroke have been presented. Such a clinicalassessment will be essential for gauging recovery of walking adaptability with rehabilitation and for motivating novel strategies toenhance recovery of walking adaptability after stroke.

    1. Introduction

    Approximately, 600.000 individuals incur a stroke each yearand stroke is the leading cause of long term disability in theUnited States [1, 2]. Walking function in those who havesustained a stroke may range from complete dependence toindependent walking ability. During the first week after astroke, only a third of persons are able to walk unaided [3]but at 3 weeks or at hospital discharge 50–80% of survivorscan walk unaided [4, 5] and by 6 months approximately 85%of stroke survivors are able to walk independently withoutphysical assistance from another person [6]. Interestingly,while up to 85% of individuals with a stroke regain inde-pendent walking ability [6–8], only about 7% of persons

    discharged from inpatient rehabilitation could manage stepsand inclines and walk the speeds and distances required towalk competently in the community [8–10].

    Walking in everyday life necessitates walking adaptability,which is the ability tomodify walking tomeet behavioral taskgoals and demands of the environment [11–13]. The abilityto adapt walking is one component of a tripartite model oflocomotor control, along with the ability to generate steppingand maintain postural equilibrium [11, 14]. Individuals withlimited ability to appropriately adjust to changes in the taskand environment may either choose to avoid walking inthese contexts (a safety strategy) or experience a heightenedrisk of falls when required to walk under these challengingcircumstances [15]. Indeed, the rates of falling are reported

    Hindawi Publishing CorporationStroke Research and TreatmentVolume 2014, Article ID 591013, 21 pageshttp://dx.doi.org/10.1155/2014/591013

    http://dx.doi.org/10.1155/2014/591013

  • 2 Stroke Research and Treatment

    to be high, ranging between 23–34%, 40–73%, and 43–70%during a 3-4 month [7, 16], 6-month [17, 18], and 1-yearfollow-up [19, 20], respectively. Most falls are reported toresult from a trip, a slip, or a misplaced step while walking[17, 21–24] and walking is also the most frequently reportedactivity (39%–90%) at the time of a fall in stroke survivors[7, 17, 25, 26], suggesting the reduced ability of individualswith stroke to adjust walking to task and environmentaldemands.

    Despite the relevance of walking adaptability to everydaymobility and the reduced ability of individuals with stroke toadjust walking to task and environmental demands, assess-ment of walking adaptability has received relatively littleattention. Frequently used assessments of walking recoveryafter stroke involve walking short distances (such as the 10mwalking speed test, timed up, and go test) and examinationof isolated limb movements (e.g., Fugl-Meyer Assessment)to predict walking recovery [27–29]. Although valuable,these assessments do not account for the full repertoireof walking skills that are required to reengage in safeand independent ambulation in the home and community[29, 30]. Specific, comprehensive, and rigorous assessmentsfor walking adaptability are essential to design targetedinterventions to improve walking adaptability after stroke.Therefore, the purpose of this evidence-based review is toexamine the challenges to clinical measurement of walkingadaptability and to discuss the status of clinical measurementof walking adaptability after a stroke. Specifically, we aimedto identify existing performance-based clinical assessmentsof walking function that can measure adaptability and inturn inform rehabilitation strategies to improve recovery ofwalking adaptability after stroke. This review is organized infive sections. First, we present the neural control model ofwalking which identifies adaptability as a distinct require-ment for optimal walking function. Second, we discuss theconceptual challenges in measurement of walking adaptabil-ity and propose some solutions to these challenges. Third,we review the existing literature related to experimentalevidence quantifying limitations and capacity in walkingadaptability after stroke. Fourth, we review the content ofcurrent performance-based clinical assessments of walkingfunction to determine the extent to which they capture theconstruct of adaptability. Finally, we have proposed somestrategies for effectively measuring walking adaptability inclinical settings for individuals with a stroke.

    2. Neural Control Model of Walking

    Amajor rationale for the need to measure walking adaptabil-ity separately from steady-state walking is that adaptabilityhas some distinct neural control requirements. Among theearliest works identifying adaptability as an independentneural control construct is the framework proposed byForssberg [11] and Grillner and Wallen [14]. This frameworkidentifies the three primary requirements for the CNS togenerate purposeful or goal-directed locomotion: stepping,equilibrium, and adaptability (Figure 1). First, the CNS mustgenerate the basic stepping pattern of rhythmic reciprocal

    Stepping(basic rhythmic

    reciprocallimb movements)

    Equilibrium(posture and equilibriumcontrol during walking)

    Adaptability(adaptation to behavioral

    task goals andenvironmental demands)

    Figure 1: Neural control model of functional walking. Neuralcontrol of walking can be explained as a tripartite model consistingof stepping, equilibrium, and adaptability [11, 14]. All three arenecessary for optimal walking function. This review focuses onwalking adaptability, which is defined as the ability to adjust walkingto behavioral task goals and environmental circumstances.

    limb movements while supporting the body against gravityand propelling it forward. Second, the CNS must maintaincontrol of equilibrium to keep the center of mass over aconstantly moving base of support and maintain the bodyupright in space. Finally, the CNS must have some adaptivecapabilities for locomotor control so that the basic patterncan be adapted according to the environmental circumstanceor changes in the behavioral goal. Walking adaptabilityconceptualizes the third essential requirement for successfulwalking as earlier proposed (Figure 1).

    Accumulating evidence further supports a model ofwalking that distinguishes some of the neural control require-ments of walking adaptability from stepping and balance.Thebasic reciprocal pattern of stepping is primarily controlledby pattern generating circuits in the spinal cord [33, 34].For typical steady state walking, these circuits are activatedby an indirect locomotor pathway believed to include themotor cortex, basal ganglia, and brainstem locomotor centers[35, 36], as well as by signals from the cerebellum and theperiphery (e.g., sensorimotor reflexes) [37]. While typicalsteady state walking involves some direct control fromthe corticospinal pathway [38–41], the role of corticospinalcontrol is known to be much greater for tasks requiringadaptability [42–47]. For example, evidence from animalsshows that central motor lesions severely limit the capacityfor adaptability [44], while stepping is relatively preserved[48, 49]. Additional evidence from cat studies shows thatcorticospinal neurons increase their firing during ladderwalking, obstacle crossing, and obstacle avoidance [50–52].Analogous results have been shown in humans, as motorevoked potentials are increased in legmuscles duringwalkingtasks requiring accurate control [53, 54]. Based on this cumu-lative evidence, stroke would be expected to be particularlydetrimental to walking adaptability because a stroke often

  • Stroke Research and Treatment 3

    directly damages the supraspinal motor pathways (i.e., motorcortex, cerebral whitematter, and/or internal capsule) that arecritical for walking adaptability. Since walking adaptability isalso critical for the optimal functional recovery of walkingfunction, measurement of walking adaptability after strokewarrants attention.

    3. Conceptual Challenges for theMeasurement of Walking Adaptability

    Measurement of walking adaptability has received relativelylittle attention in clinical settings, as indicated in part bythe absence of a comprehensive, well-accepted assessment ofwalking adaptability. A number of factors may account forthe lack of progress in this area. First, there is no uniformterminology to define the construct of walking adaptability.Second, the construct of walking adaptability covers a broadspectrum of situations because adaptations of walking maybe required under varied task and environmental demands.Clinical assessments of walking adaptability must thereforereflect this multi-faceted and complex nature of adaptability.

    3.1. Lack of UniformTerminology. While walking adaptabilityhas been the subject of interest in several studies, there is alack of uniform terminology used to describe the construct.The most common task paradigms that refer to similar con-structs as walking adaptability are “gait adaptability,” “obstaclecrossing/clearance/negotiation,” and “locomotor adaptation.”Houdijk and colleagues define “gait adaptability” as “theability to adjust gait to environmental circumstances, suchas obstacles and targets” [55]. They have studied gait adapt-ability as the adjustments in foot placement in response tovisual or acoustic stimuli delivered during treadmill walking.However, walking adaptability may not necessarily requireovert changes to the walking pattern. Rather, it may requiremotor control adjustments that (in some cases) preservethe mechanics of walking such as when walking underdifferent ambient conditions or constraints posed by theterrain. “Obstacle crossing/negotiation/clearance” is anotherterm used in the literature to indicate walking adaptability[23, 56–64]. This term has been most frequently utilizedin the body of work investigating the mechanisms relatedto obstacle clearance. Avoiding obstacles is an importantand unique dimension of walking adaptability, but “obstacleavoidance” does not comprehensively capture the multi-faceted construct of walking adaptability. “Locomotor adap-tation,” another term selectively used in the work by Bastianand colleagues, refers to an error driven motor learningprocess that is used to alter the spatiotemporal elements ofwalking [65, 66]. Bastian and colleagues utilize a split-belttreadmill to study locomotor adaptation and their conceptu-alization of locomotor adaptation encompasses an importantaspect related to learning of walking adjustments over time[66, 67].

    Our conceptualization of walking adaptability is foundedon the previously mentioned tripartite locomotor controlmodel of stepping, equilibrium, and adaptability. Terminol-ogy based on this fundamental neural controlmodel provides

    a strong foundation and a broader context for the use of theterm, “walking adaptability.” Furthermore, since emergingrehabilitation paradigms have utilized and focused on thistripartite model [12, 13, 68], our approach is intended tosynchronize with these paradigms in order to provide auniform framework for both assessment and intervention ofwalking adaptability after stroke.

    3.2. Complex Nature of the Construct of Walking Adaptability.Walking adaptability is necessitated when the complexity ofthe task situation exceeds what can be accomplished withbasic stepping. For example, walking adaptability is crucialwhen walking on uneven or cluttered terrains (unpredictableenvironment), to ensure safe and appropriate foot placement[64, 69]. Similarly, walking adaptability is essential whenthe task requires walking and turning to negotiate a curvedpath. There can be numerous combinations of task goalsand environmental circumstances that need to be consideredto comprehensively capture walking adaptability (Figure 2).A starting point to capture the different situations andcontexts necessitating walking adaptability is the conceptualframework developed by Patla and Shumway-Cook [15].Patla and Shumway-Cook describe eight dimensions thatimpact a person’s ability to interact in the environmentand their framework includes time constraints, distance,ambient conditions, terrain characteristics, external physicalload, attentional demand, postural transitions, and trafficdensity [15, 70]. Although this framework was originallyintended to characterize the external demands of commu-nity ambulation, it also can be applied to characterize thespectrum of environmental situations that require walkingadaptability. Thus, our application of this framework to thetopic of “walking adaptability” is inclusive of all ambulationsettings, not just community ambulation. Based on Patla andShumway-Cook’s framework [15], we propose nine domainsof walking adaptability that are defined in Table 1.

    While we primarily conceptualized the domains of adapt-ability based on Patla and Shumway-Cook’s proposed dimen-sions of community mobility, there are some differencesin our approach. First, we conceptualize the “domains” ofwalking adaptability as the “capacity/ability” of an individual(an internal characteristic) as opposed to Patla and Shumway-Cook’s emphasis of the environmental context (an externalcharacteristic). Second, we incorporated seven of the eightdimensions of community mobility proposed by Patla andShumway-Cook, excluded one dimension, and modifiedtwo dimensions to create overall nine domains of walkingadaptability. Particularly, we modified the “traffic density”dimension of Patla and Shumway-Cook’s framework [15]and subcategorized this dimension into two domains of“obstacle negotiation” and “maneuvering in traffic.” Amassingliterature (discussed below) suggests unique limitations ofindividuals with stroke when negotiating obstacles warrant-ing an exclusive assessment of this domain of walking adapt-ability. “Maneuvering in traffic” refers to successfully avoidingcollision with obstacles by maneuvering the entire body andmay require discrete set of abilities (like processing the speedand direction of movement) when compared to stepping

  • 4 Stroke Research and Treatment

    ON TM CT TR AM PT MT PL TF ON TM CT TR AM PT MT PL TF ON TM CT TR AM PT MT PL TF

    Home TrailBusy city streets

    Street 1

    Street 2

    Street 3 Street 4

    Figure 2: Conceptual illustration of the domains of adaptability. This figure illustrates the relative demands that may be placed on the ninedomains of walking adaptability in different ambulatory environments. The nine domains of walking adaptability have been adapted fromearlier work by Patla and Shumway-Cook [15]. In a less complex and predictable environment such as the home, the requirements for walkingadaptability would be less demanding and encompass fewer domains relative to more challenging environments such as walking on a naturetrail or on a busy city street. Abbreviations: ON—obstacle negotiation; TM—temporal demands; CT—cognitive dual-tasking; TR—terraindemands; AM—ambient demands; PT—postural transitions demands; MT—motor dual-tasking; PL—physical load; TF—maneuveringtraffic.

    Table 1: Domains of walking adaptability.

    Domain∗ Definition∗

    Obstacle negotiation1 Negotiating obstacles in the environment to prevent a collision between the lower limb and the obstacle,such as stepping over an obstacle

    Temporal Time constraints imposed on walking, such as needing to walk fast to cross a street or slow in a crowdedmallCognitive dual-tasking2 Walking while attending to cognitive tasks, such as engaging in conversation while walking

    Terrain demands Walking on compliant or uneven surfaces that are not flat and firm, such as stairs, ramps, grass, and soforth

    Ambient demands Factors such as level of lighting, temperature, weather conditions, noise levels, and familiarity withsurroundings

    Postural transitions Varying posture during walking, such as turning, bending down to pick an object while walking, and soforth

    Motor dual-tasking2 Walking while attending to additional motor tasks, such as holding a glass of water while walking, pickingup an object from the floor, and so forth

    Physical Load Carrying or interacting with a weighted object while walking, such as carrying a loaded back-pack,walking to open a heavy door, and so forth

    Maneuvering in traffic1 Avoiding collision with static and dynamic objects by maneuvering the entire body, such as walkingaround other people, pets, vehicles, and so forth∗Modified from Patla and Shumway-Cook’s conceptual framework defining dimensions of mobility [15].1Originally categorized as “traffic density” in Patla and Shumway-Cook’s dimensions of mobility.2Originally categorized as “attentional demands” in Patla and Shumway-Cook’s dimensions of mobility.

  • Stroke Research and Treatment 5

    over an obstacle.Therefore, we propose that “maneuvering intraffic” should be assessed as a separate domain of walkingadaptability. We also modified the “attentional demands”dimension of Patla and Shumway-Cook’s framework [15]and subcategorized this dimension into two domains of“cognitive dual-tasking” and “motor dual-tasking.” Since theaddition of a cognitive or motor task to walking may demandunique and varying amounts of attention resources, wepropose that adjusting walking to cognitive and motor dual-tasks necessitates distinct measurement. We also excludedthe dimension of “distance” originally proposed by Patlaand Shumway-Cook since distance pertains to endurance ofwalking and does not necessitate adaptations.

    Each of these domains represents a demand (goal of thetask or an environmental constraint) that may necessitatewalking adaptability. Figure 2 is a conceptual illustration ofthe domains of walking adaptability in varying environments.In any given environment, the demand on a particulardomain and the number of domains included may vary(Figure 2). For instance, in a less complex and predictableenvironment, fewer domains may be represented and thosethat are represented may have lower demand. An example iswalking at home with uncluttered walking paths, walking atone’s own pace and with no traffic encountered. In contrast,a complex and unpredictable environment such as a busycity street will involve greater representation of more numberof domains for negotiating street curbs, ramps, walking tocross a street, conversingwith a friendwhile walking, walkingat dusk or when raining, holding to shopping bags whilewalking, and maneuvering around other people (Figure 2).An advantage of using these domains to define task goals andenvironmental demands that necessitate walking adaptabilityis that it is not specific to the environment in which walkingis being performed but, instead, is reflective of the demandsfor walking adaptability under varied situations (Figure 2).

    4. Evidence of Impairments in WalkingAdaptability in Individuals with Stroke

    The domains of walking adaptability most notably investi-gated and reported in the stroke literature include “obstaclenegotiation,” “temporal demands,” and “cognitive dual-taskdemands.” There is also emerging evidence pertaining to“terrain demands” and “ambient demands.” Other domainshave received some attention as components of clinicalassessments, but specific performance results for personsafter stroke are not readily available in the literature. Theseinclude the domains of “postural transitions,” “motor dual-task demands,” “physical load,” and “maneuvering in traffic.”Here, we review some of the most pertinent evidence high-lighting the impairments in walking adaptability after stroke.

    4.1. Obstacle Negotiation. The capability to negotiate obsta-cles in the environment is crucial for safety during walking.Obstacle negotiation involves modifying the typical gaitpattern to prevent a collision between the lower limb andthe obstacle. This often requires a well-timed coordinationbetween the visual and motor systems in order to produce

    an appropriate limb trajectory while maintaining dynamicbalance. Limitations in walking adaptability using obstacleclearance paradigms have been well studied in the strokepopulation. Individuals with a stroke have greater failuresrates when avoiding obstacles despite using a more cautiousstrategy of stepping over with a higher toe clearance with thelead limb [56]. Additionally, Said and colleagues reported thatalthough the lead limb clearance was high, the limb trajectorywas much more variable increasing the stability demands ofthe trail limb [99]. While the failure rate was lower when theunaffected limb crossed the obstacle first, individuals withstroke showed no preference in crossing with the affected orunaffected limb [56, 58]. Toe clearance of the trail limb wasalso shown to be reduced, increasing the risk of tripping [23].Individuals with stroke also demonstrate increased anterior-posterior separation of the COP and COMwhen negotiatingobstacles, suggesting greater instability during the task [57].Furthermore, individuals with stroke show inaccurate footplacement of the affected lead foot when clearing obstaclesand prefer using a step lengthening strategy [58, 59].

    The deficits in adjusting foot placement when clearingobstacles are shown to be even more prominent whenexecuted under time pressure as when individuals had toavoid obstacles that suddenly appeared before them [58, 100,101]. Furthermore, adding a cognitive task during obstaclecrossing deteriorated performance in individuals with strokeand increased their risk of obstacle-heel contact duringcrossing [61]. Individuals with stroke also seemed to utilizea “posture-first strategy” even when they were instructedto keep up their performance on both motor and cognitivetasks [59]. Moreover, van Swigchem and colleagues recentlyidentifiedmotor impairments associatedwith the difficulty inobstacle avoidance after stroke [64]. They reported that indi-viduals with stroke demonstrated a delay and reduction inmuscle responses and therefore suggested that rehabilitationinterventions that aim to improve obstacle avoidance shouldfocus on time-critical obstacle training.

    4.2. Temporal Demands. Walking tasks often require timeconstraints, such as needing to walk faster when crossing abusy intersection or whenwalking to answer a ringing phone.In some cases, temporal demands might also require slowerwalking such as when walking with a slow moving crowd. Anumber of studies demonstrate the compromised ability ofindividuals after stroke to increase walking speed over andabove their self-selected speed [102–104], which is expectedgiven that self-selected speeds are well below normal. Whilemost rehabilitation studies have focused on improving tem-poral walking performance (i.e., gait speed) as the primaryoutcome measure and walking speed has also shown toincrease with rehabilitation [102, 105, 106], walking speedsgenerally remain well below normal and do not transfer tosubstantial gains in home and community ambulation [9, 10].These findings argue for the need to broaden rehabilitationinterventions and assessments to account for other aspects ofwalking adaptability that may contribute to functional gains.

    4.3. Cognitive Dual-Tasking. Secondary task demandsinvolve combining walking with other attention-demanding

  • 6 Stroke Research and Treatment

    tasks such as engaging in conversation, reading a map, andso forth. This is commonly referred to as “dual-tasking,”and is known to degrade walking performance even inhealthy adults [107]. After a stroke, dual-tasking conditionsof walking and concurrently performing a cognitive taskhave shown to profoundly impact the walking performancecompared to age-matched healthy controls [108–111].Walking and concurrently performing a cognitive dual-taskreduces gait speed [108–110], stride duration [108, 111, 112],stride length [108, 109], double support time [110, 113], andcadence [108, 114].The results of cognitive-motor interferencein individuals with stroke are consistent across the use ofdifferent secondary cognitive tasks involving a range ofcognitive functions (such as working memory, executivefunction, visuospatial processing, and language) [107, 115].Moreover, the majority of the research demonstrating suchcognitive-motor interference reports that individuals withstroke prioritize the cognitive task, sacrificing walkingperformance [108, 109, 111, 112], suggesting the impairedability to adapt the walking pattern in the presence of acognitive task.

    4.4. Terrain Demands. Terrain refers to walking on surfacesthat are not flat and firm. This includes stairs, escalators,ramps, curbs, side slopes, grass, sand, trails with tree roots,and so forth. Relatively little work has been conducted toassess the capability of individuals after stroke to adaptwalking to challenging terrain conditions. Phan and col-leagues [116] showed that individuals with stroke reducedtheir walking speed and step length when walking downhillcompared to both level and uphill walking. Walking speedin healthy controls, however, remained unchanged acrossdifferent conditions. A number of studies have documenteddeficits in stair ascent/descent performance after stroke [117,118] and at least one study has developed a clinical assessmentof stair performance [119].

    4.5. Ambient Demands. Ambient conditions refer to factorssuch as lighting, temperature, weather conditions, noiselevels, familiarity with surroundings, and other such factorsthat may interact with walking. Although most of thesefactors have not been specifically examined, there is emergingevidence that the ambient environment, in general, caninfluence walking function. One recent study found thatfaster walking speeds were obtained when stroke participantswalked outdoors relative to walking indoors [120]. Otherstudies have also reported that walking speedwas lower whentested in a shopping mall compared to on a street [121] orin a clinic [122], suggesting that the ambient environmentcan influence walking function. Clinic-based walking speedassessment predicts community walking speeds for fasterwalking stroke survivors, but not for slower walking strokesurvivors [123].

    4.6. Less Investigated Domains ofWalking Adaptability. Thereis a need for research to examine poststroke deficits inthe domains of “postural transitions,” “motor dual-tasking,”

    “physical load,” and “maneuvering in traffic.” Postural transi-tioning refers to the capability of an individual to alter bodyorientation or head position in order to perform a task, suchas turning a corner, observing the surrounding environment(i.e., head turns), reaching during walking, bending duringwalking, or walking through a narrow space.Motor dual-taskincludes such tasks as carrying a tray of food and dialing aphone while walking. Like cognitive dual-task, this involvesa competition for attentional resources. However, manualdual-tasking may also involve a competition for resources(such as motor programs) that are detrimental to safe controlof walking. Physical load demands while walking includetasks such as opening a heavy door, walking while wearing aheavy backpack, or carrying a weighted package. Interactionwith a physical load during walking necessitates success-fully adapting to any changes to the walking pattern (e.g.,perturbations to the body mass) created by the additionalphysical load. Maneuvering in traffic can include factors suchas other people (i.e., when walking on a busy sidewalk), largeenvironmental objects (i.e., street signs, furniture), or petsin the home. In some cases, maneuvering may require someonline processing of information about speed and directionof movement, in order to predict where the object is likelyto move relative to oneself. Since maneuvering in traffic mayrequire discrete set of abilities (like processing the speedand direction of movement), we propose its assessment as aseparate domain of walking adaptability.

    It is important to consider that walking adaptability tasksin each of the proposed domains require the integration ofall three neural control requirements of walking: stepping,equilibrium, and adaptability.While the limitations in steady-state walking ability after a stroke due to compromisedstepping and equilibrium are well characterized [5], quan-tification of limitations in walking adaptability is not wellestablished and warrants further work. To date, the existinglimited experimental evidence highlights the limitations inadaptability in individuals with stroke, thereby supportingthe need for individualized assessment of these limitations.

    5. Existing Performance-BasedClinical Assessments of WalkingFunction and the Measurement ofWalking Adaptability Post-Stroke

    Since there is no gold-standard clinical assessment of walk-ing adaptability, performance-based clinical assessments ofwalking function were reviewed to determine the extent towhich they measure the construct of walking adaptability.Assessments included in this review contained at least asubset of walking activities requiring adaptability, had at leastone peer-reviewed study with detailed information about thecontent of the assessment, were developed for any adult pop-ulation (not limited to stroke), and were clinically feasible.While some of the clinical assessments included in our reviewmay lack recommendation for clinical use based on earlierpublished criteria [124], our purpose in reporting thesewas toprovide an in-depth review of the content of these tools andidentify the domains of walking adaptability that they may

  • Stroke Research and Treatment 7

    capture. We excluded four assessments (balance evaluationsystems test, timed up and go measure, Fullerton advancedbalance scale, and stops walking when talking) from ourreview since all items contained in these assessments wereredundant with clinical assessments included in this review.

    5.1. Dynamic Gait Index. The dynamic gait index (DGI) wasdeveloped to assess an individual’s ability to modify gait inresponse to changes in task demands [74]. The DGI wasoriginally developed for community-dwelling older adultsand consists of 8 walking tasks requiring persons to modifytheir gait to varying demands, such as walking at differentspeeds, walking while turning head, ambulating over andaround obstacles, stair negotiation, and making quick turns.The performance on the items of the DGI is measured ona 4-point ordinal scale (0–4), with higher scores indicatingbetter performance and a maximum score of 24 [74]. Thepsychometric properties of the DGI have been well testedwith several reports of reliability, validity, and sensitivityin varied clinical populations, including stroke [71–73, 75–79, 125], as presented in Table 2. Seven of the eight items onthe DGI assessment involve walking adaptability capturing5 domains of walking adaptability (obstacle negotiation,postural transitions, temporal demands, terrain demands,and maneuvering in traffic) (Table 3).

    5.2. Functional Gait Assessment. The functional gait assess-ment (FGA) is based on the DGI and was developed forpersons with vestibular disorders to reduce the ceiling effectof the DGI for this population [85]. The FGA is a 10-itemwalking test comprising of 7 of the 8 items from the originalDGI and 3 new items, including walking with a narrowsupport base, walking backwards, and walking with eyesclosed. Similar to the DGI, the performance on the itemsof the FGA is measured on a 4-point ordinal scale (0–4),with a maximum score of 30 [85]. The FGA like the DGIhas also been tested in several clinical populations, includingthe stroke population [71, 79–84]. Additionally, psychometricproperties of reliability, validity, and sensitivity have beentested (Table 2). The FGA also reduces the ceiling effect ofthe DGI in persons with stroke [71]. The items of the FGAcapture four domains of walking adaptability, to includeobstacle negotiation, postural transitions, temporal demands,and terrain demands. Two of the three new items of theFGA add measurement in the domain of postural transitions(Table 3).

    5.3. Modified Emory Functional Ambulation Profile. Themodified Emory functional ambulation profile (mEFAP) is amodification of the functional ambulation profile, is a timedmeasure of walking under five environmental challenges,and was developed for individuals with stroke [87]. ThemEFAP challenges a person to walk over a standardizedarray of terrains (floor, carpet, and stairs), step over obstaclesand walk with postural transitions (rise from a chair andwalk a distance). Each of the items on the mEFAP is timedand scored based on standardized criterion. Individuals’time to complete each subtask is recorded and this time is

    multiplied by a factor assigned based on the use and typeof an assistive device [87]. The total score is the summedtotal for each subtask. The mEFAP has been exclusivelytested in the stroke population and reliability and validityfor use in individuals with stroke has been reported [86,87], as shown in Table 2. Four of the five items of themEFAP measure walking adaptability but only a limitednumber of domains of walking adaptability (terrain, obstaclenegotiation, postural transitions, and maneuvering in traffic)are captured (Table 3).

    5.4. Spinal-Cord Injury Functional Ambulation Profile. Thespinal-cord injury functional ambulation profile (SCI-FAP)is modified from the mEFAP and is a timed measure of func-tional walking developed for individuals with an incompletespinal cord injury [89]. The SCI-FAP is a 7-item assessmentscale that comprises of 4 items similar to the mEFAP and 3new items (walking to step up on a small step and continuewalking, walking while carrying a shoulder bag and walkingto open a door and continue walking through). Scoringof the SCI-FAP is similar to that of the mEFAP but themaximum possible score is higher due to the addition of the3 items. While reliability and sensitivity of the SCI-FAP havebeen reported in individuals with incomplete SCI [88, 89],as shown in Table 2, validity of the SCI-FAP has not yetbeen established. While this assessment tool was originallydeveloped for individuals with SCIs, some of the additionalitems on the SCI-FAP capture additional domains of walkingadaptability. Specifically, the SCI-FAP captures the domainof adapting walking to interact with a physical load, oneof the domains that has been less frequently assessed. TheSCI-FAP adds measurement of one more domain of walkingadaptability (physical load) when compared to the mEFAP(Table 3).

    5.5. High-Level Mobility Assessment Test. The high-levelmobility assessment test (Hi-MAT) was developed for per-sons with traumatic brain injury (TBI) to assess high-levelmobility skills [90, 91]. The Hi-MAT consists of 13 items thatassess balance and mobility utilizing a wide-range of high-level activities such as walking, stair negotiation, running,hopping, skipping, and jumping.Majority of items (excludingbounding and stair items) are performed by the individualsat their fastest safe speed and the performance times anddistances (raw scores) are recorded. The raw scores areconverted to a score from 0 to 4 using a standardized scoringtable and the item scores are summed to produce a total score,with amaximum score of 54.TheHi-MAThas primarily beentested in persons with acquired and traumatic brain injuriesand reliability, validity, and sensitivity have been reportedfor this population (Table 2). Normative data of performancehave also been reported [126]. The Hi-MAT has not yet beentested in the stroke population. While the walking itemson the Hi-MAT are similar to other clinical assessments,these activities (except stair negotiation) are tested undertime constraints (maximal safe speed) and may provide asensitive method to unmask adaptability deficits in somehigher-functioning individuals. Recent evidence shows that

  • 8 Stroke Research and Treatment

    Table2:Psycho

    metric

    characteris

    ticso

    fthe

    perfo

    rmance-based

    clinicalassessm

    entsof

    walking

    functio

    n.

    Assessment

    Psycho

    metric

    prop

    ertie

    sSubjects

    Results

    DGI(Linetal.2010[71])

    Sensitivity,TrT,and

    C-valid

    ity45

    after

    stroke,48

    forT

    rTMDC=4po

    ints,

    TrTIC

    C=0.91–0

    .97,valid

    ityDGIw

    rt4-item

    DGI

    andFG

    A𝑟>0.91

    DGI(Jonsdo

    ttira

    ndCa

    ttaneo2007

    [72])

    TrT,InterRR,

    andC-

    valid

    ity25

    postc

    hron

    icstr

    oke

    TrTIC

    C=0.96,InterRR

    ICC=0.96,validity

    DGIw

    rtBB

    S𝑟=0.83,

    wrtABC𝑟=0.68

    DGI(Ro

    meroetal.2011[73])

    Sensitivity

    42commun

    ity-dwellingeld

    erly

    MDC=2.9po

    ints

    DGI(Shum

    way-C

    ooketal.1997[

    74])

    C-Va

    lidity

    44commun

    ity-dwellingeld

    erly

    DGIw

    rtBB

    S𝑟=0.67,w

    rtbalances

    elf-p

    erceptions

    test𝑟=0.76

    DGID

    anish

    version(Jøn

    sson

    etal.

    2011[75])

    InterRR,

    IntraR

    R24

    hospita

    lized

    adults

    26adultsin

    outpatient

    rehab

    Hospitalized

    InterRRIC

    C=0.92,IntraRR

    ICC=0.90;outpatie

    nts

    InterRRIC

    C=0.82,IntraRR

    ICC=0.89

    DGI(Huang

    2011)

    Sensitivity,TrT

    72adultswith

    PDMDC=2.9po

    ints,

    TrTIC

    C=0.84

    DGI(Ca

    kitetal.2007

    [76])

    C-valid

    ity31

    adultswith

    PDDGIw

    rtUPD

    RSmotor

    subscale𝑟=−0.57,w

    rthisto

    ryof

    falls

    𝑟=0.64

    DGI(Halland

    Herdm

    an2006

    [77])

    TrT

    16adultswith

    vestibu

    lar

    disorders

    TrTIC

    C=0.86

    DGI(Whitney

    etal.200

    0[78])

    C-valid

    ity30

    adultswith

    vestibu

    lar

    disorders

    DGIw

    rtBB

    S𝑟=0.71

    DGI(Marchettietal.2014JN

    PT[79])

    Sensitivity

    326adultswith

    balancea

    ndvestibular

    disorders

    MDC=4po

    ints

    FGA(Lin

    etal.2010[71])

    Sensitivity,TrT,C

    and-validity

    45aft

    erstr

    oke

    MDC=4.2po

    ints,

    TrTIC

    C=0.95,FGAwrt10MWT𝑟=−0.66,w

    rtPA

    SS𝑟=−0.83

    FGAGerman

    version(Th

    iemee

    tal.

    2009

    [80])

    InterRR,

    IntraR

    R,andC-

    valid

    ity28

    after

    stroke

    InterRRIC

    C=0.94,IntraRR

    ICC=0.97,FGAwrtFA

    C𝑟=0.83,w

    rtgaitspeed𝑟=0.82,w

    rtBB

    S𝑟=0.93,w

    rtRM

    I𝑟=0.85,w

    rtBa

    rthel

    index𝑟=0.71

    FGA(W

    alkere

    tal.2007

    [81])

    InterRR

    200healthyadults

    InterRRIC

    C=0.93

    FGA(Leddy

    etal.2011[82])

    TrT,InterRR

    24adultswith

    PD,15forInterRR

    TrTIC

    C=0.91,InterRR

    ICC=0.93

    FGA(W

    risleyandKu

    mar

    2010

    [83])

    C-valid

    ity35

    commun

    ity-dwellingeld

    erly

    FGAwrtBB

    S𝑟=0.84,w

    rtTU

    GT𝑟=0.84,w

    rtABC

    scale𝑟=0.53

    FGA(Ellise

    tal.2011[84])

    C-valid

    ity262adultswith

    PDFG

    AwrtBB

    S𝑟=0.77,w

    rtPD

    Q-39𝑟=−0.57,w

    rtfunctio

    nalreach

    𝑟=0.52

    FGA(W

    risleyetal.200

    4[85])

    InterRR,

    IntraR

    R,andC-

    valid

    ity6adultswith

    vestibu

    lard

    isorders

    InterRRIC

    C=0.84,IntraRR

    ICC=0.83,FGAwrtABC

    scale𝑟=0.64,

    wrtTU

    GT𝑟=−0.50,w

    rtDGI𝑟=0.80,w

    rtdizzinessh

    andicap

    inventory𝑟=−0.64,w

    rtperceptio

    ndizzinesssym

    ptom

    s𝑟=−0.70

    FGA(M

    archettietal.2014JN

    PT[79])

    Sensitivity

    326adultswith

    balancea

    ndvestibular

    disorders

    MDC=6po

    ints

    mEF

    AP(Liawetal.200

    6[86])

    TrT,C-

    valid

    ity20

    postc

    hron

    icstr

    okefor

    TrT

    40po

    stsub

    acutes

    troke

    for

    C-Va

    lidity

    TrTIC

    C=0.99,m

    EFAPwrtBa

    rthelInd

    ex𝑟=−0.52,w

    rtRiverm

    ead

    Index𝑟=−0.78

    mEF

    AP(Baera

    ndWolf2001[87])

    TrT,InterRR,

    andC-

    valid

    ity26

    after

    stroke

    TrTIC

    C=0.99,InterRR

    ICC=0.99,m

    EFAPwrtBB

    S𝑟=−0.70,w

    rtFu

    nctio

    nalassessm

    entm

    easure𝑟=−0.78

    SCI-FA

    P(M

    usselm

    anandYang

    2014

    [88])

    Sensitivity

    20adultswith

    incompleteS

    CIMDC=96

    points

  • Stroke Research and Treatment 9

    Table2:Con

    tinued.

    Assessment

    Psycho

    metric

    prop

    ertie

    sSubjects

    Results

    SCI-FA

    P(M

    usselm

    anetal.2011[89])

    TrT,InterRR

    22adultswith

    incompleteS

    CITrTIC

    C=0.98,InterRR

    ICC=1.0

    ,

    Hi-M

    AT(W

    illiamse

    tal.2006

    [90])

    Sensitivity,C

    -validity

    103adultswith

    BIMDC=+4

    points,−2po

    ints,

    Hi-M

    ATwrtmotor

    FIM𝑟=0.53,w

    rtgrossfun

    ctionriv

    ermeadmotor

    assessment𝑟=0.87

    Hi-M

    AT(W

    illiamse

    tal.in

    PTJ2

    006

    [91])

    TrT,InterRR

    103adultswith

    BI20

    adultswith

    BIforT

    rT17

    adultswith

    BIforInterRR

    TrTIC

    C=0.99,InterRR

    ICC=0.99

    CB&M

    (Balasub

    ramanian2014

    [92])

    InterRR,

    IntraR

    R,andC-

    valid

    ity40

    commun

    itydw

    ellin

    gelderly

    37forC

    -validity

    wrt6M

    WT

    36forC

    -validity

    wrtgaitspeed

    InterRRIC

    C=0.95,IntraRR

    ICC=0.96,C

    B&M

    wrtDGI𝑟=0.79,

    wrtBB

    S𝑟=0.87,w

    rtSP

    PB𝑟=0.75,w

    rt6M

    WT𝑟=0.71,w

    rtTU

    GT

    𝑟=−0.69,w

    rtgaitspeed𝑟=0.65,w

    rtABC𝑟=0.47,w

    rtfunctio

    nal

    reachtest𝑟=0.35

    CB&M

    (Innessetal.2011[93])

    C-valid

    ity35

    adultswith

    BICB

    &M

    wrtgaitvelocity𝑟>0.67,w

    rtABC𝑟=0.60

    CB&M

    (Wrig

    htetal.2010[94])

    Sensitivity,TrT,and

    InterRR

    32youths

    with

    BIMDC=13.5%po

    ints,

    TrTIC

    C=0.90,InterRR

    ICC=0.93

    CB&M

    (How

    eetal.2006

    [95])

    TrT,InterRR,

    andIntraR

    R32–36adultswith

    BITrTIC

    C=0.98,InterRR

    ICC=0.98,IntraRR

    ICC=0.98

    CB&M

    (Kno

    rretal.2010[96])

    C-valid

    ity44

    after

    stroke

    CB&M

    wrtCh

    edokeM

    cMasterstro

    keassessment𝑟=0.63(le

    g),𝑟=0.61(fo

    ot)

    WIT

    (Bandinelli

    etal.200

    6[97])

    TrT

    30commun

    ity-dwellingeld

    erly

    TrTIC

    C≥0.75

    for13of

    14items

    SWOC(Rub

    enste

    inetal.1997[31])

    TrT,InterRR,

    andC-

    valid

    ity58

    commun

    ity-dwellingeld

    erly

    men

    TrTIC

    C=0.93,InterRR

    ICC0.81–1.0,obstacle

    course-R

    wrtgait

    velocity𝑟=0.61,w

    rt6M

    WT𝑟=0.56,w

    rtPO

    MAGaitscore

    0.52,

    wrt,P

    OMAbalance𝑟=0.42

    Obstacle

    course

    (Means

    1996

    [32])

    C-valid

    ity237commun

    ity-dwellingeld

    erly

    Obstacle

    course-M

    wrtmedicalcond

    ition

    s𝑟=−0.41,w

    rtnu

    mbero

    fmedications𝑟=−0.29

    SOMAI(Tang

    etal.1998[98])

    C-valid

    ity27

    commun

    ity-dwellingeld

    erly

    SOMAIn

    ormalvisio

    ncond

    ition

    wrt6SO

    Tcond

    ition

    s𝑟=0.21–0

    .53,

    SOMAIfocalvisio

    nwrt6SO

    Tcond

    ition

    s𝑟=0.20–0

    .59

    MTT∗∗

    TrT,test-

    retestreliability;C-

    valid

    ity,criterionvalid

    ity;InterRR

    ,interteste

    rreliability;IntraR

    R,intratesterreliabilityDGI,dynamicgaitindex;FG

    A,fun

    ctionalgaitassessm

    ent;mEF

    AP,mod

    ified

    Emoryfunctio

    nal

    ambu

    lationprofi

    le;S

    CI-FAP,spinalcord

    injury

    functio

    nalambu

    lationprofi

    le;H

    i-MAT

    ,high-levelm

    obility

    assessmenttest;CB

    &M,com

    mun

    itybalanceandmob

    ility

    scale;SO

    MAI,sensory-oriented

    mob

    ility

    assessmentinstrum

    ent;WIT,w

    alking

    InCH

    IANTI

    toolkit;SW

    OC,

    standardized

    walking

    obstaclecoursedevelopedby

    Rubensteinandcolleagues;ob

    staclecourse,obstacle

    coursedevelopedby

    Means

    andcolleagues;

    MTT

    ,multip

    letask

    test;

    PD,Parkinson’sdisease;BI,brain

    injury;SCI

    ,spinalcordinjury;w

    rt,w

    ithrespectto;MDC,

    minim

    aldetectablechange;6MWT,6-minutew

    alktest;

    BBS,Be

    rgbalancescale;A

    BC,activities-

    specificb

    alance

    confi

    dences

    cale;U

    PDRS

    ,unifiedParkinson’s

    diseaser

    atingscale;PA

    SS,posture

    assessmentscaleforstro

    kepatie

    nts;TU

    GT,tim

    edup

    andgo

    test;

    RMI,Riverm

    eadmob

    ilityindex;PO

    MA,T

    inetti

    perfo

    rmance-orie

    nted

    mob

    ilityassessment;FIM,fun

    ctionalind

    exmeasure;SPP

    B,shortp

    hysic

    alperfo

    rmance

    batte

    ry.

    ∗∗Develo

    pedforp

    ersons

    with

    Parkinson’s

    disease.Quantitativ

    edataa

    ndstr

    ategiesfor

    person

    swith

    Parkinson’s

    diseasea

    rerepo

    rted.H

    owever,n

    ospecificp

    sychom

    etric

    characteris

    ticsh

    aveb

    eenrepo

    rted.

  • 10 Stroke Research and Treatment

    Table 3: Domains of walking adaptability captured by performance-based clinical assessments of walking function.

    Clinical assessment items Domains of walking adaptability∗

    ON TM CT TR AM PT MT PL TF

    DGI2 Change speed TM

    3 Horizontal head turns PT

    4 Vertical head turns PT

    5 Gait and pivot turn PT

    6 Step over obstacle ON

    7 Step around obstacle TF

    8 Stairs TR

    FGA2 Change speed TM

    3 Horizontalhead turns PT

    4 Verticalhead turns PT

    5 Gait andpivot turn PT

    6 Step over obstacle ON

    7 Narrow BOS PT

    9 Ambulate backwards PT

    10 Stairs TR

    mEFAP2 Carpet TR

    3 Up and go PT

    4 Step over and around obstacles ON TF

    5 Stairs TR

    SCI-FAP1 Carpet TR

    2 Up and go PT

    3 Obstacles ON

    4 Stairs TR

    5 Carry PL

    6 Step Up ON

    7 Door PT MT

    Hi-MAT2 Walk backwards TM PT

    3 Walk on toes TM PT

    4 Walk over obstacle ON TM

    10/12 Stairs/dependant TR

    11/13 Stairs/independent TR

    CB&M2 Tandem walk PT

    6 Crouch and walk PT MT

    8 Walk and look PT

  • Stroke Research and Treatment 11

    Table 3: Continued.

    Clinical assessment items Domains of walking adaptability∗

    ON TM CT TR AM PT MT PL TF

    10 Forward to Backward walk TM PT

    11 Walk, look, and carry PT MT

    12 Descending stairs TR

    SOMAI6/7 Cushion 1-NV TR

    8/9 Cushion 2-NV TR

    16/17 Cushion 1-FV TR AM

    18/19 Cushion 2-FV TR AM

    WIT2 4m walk fast TM

    3 4m BOS 25 cm TM PT

    4 4m BOS 15 cm TM PT

    5 7m walk fast TM

    6 7m walk long steps PT

    7 7m fast walk obstacles ON TM

    8 7m fast walk obstacles dim light ON TM AM

    9 7m usual walk carry package MT

    10 7m usual pace naming objects CT

    11 7m usual pace pick up 1/3 objects PT MT

    12 400m fast walk TM

    13 60m fast walk weighted jacket TM PL

    SWOC1 Tandem walk PT

    2 Balance ladder with foam ON TR

    3 Ramp and stairs TR

    4 Pick up empty box PT MT

    5 Miniblind PT

    6 Step over a block TR

    OC1 Door opening PT MT

    2 Turf TR

    3 Objects ON

    4 Carpet TR

    5 Low steps TR

    6 Pine Bark TR

    7 Cones TF

    8 Sand TR

    9 Chair PT

    10 Steep steps TR

    11 Upramp TR

    12 Downramp TR

  • 12 Stroke Research and Treatment

    Table 3: Continued.

    Clinical assessment items Domains of walking adaptability∗

    ON TM CT TR AM PT MT PL TF

    MTT1 Stand Up, walk, turn, and sit down PT

    2 Item 1 + answer questions CT PT

    3 Item 1 + avoid obstacles ON PT TF

    4 Item 1 + carry an empty tray PT MT

    5 Item 1 + carry tray of 2 eggs, 1 rolling egg PT MT

    6 Item 1 + slippery shoes TR PT

    7 Item 1 + tip the floor halfway PT

    8 Item 1 + wear sunglasses in dim light AM PTItems represented in bold are redundant across assess