Study Protocol: Sleep Effects on Poststroke Rehabilitation Study.

BACKGROUND: A range of sleep disturbances and disorders are problematic in people after stroke; they interfere with recovery of function during poststroke rehabilitation. However, studies to date have focused primarily on the effects of one sleep disorder-obstructive sleep apnea (OSA)-on stroke recovery. OBJECTIVES: The study protocol for the SLEep Effects on Poststroke Rehabilitation (SLEEPR) Study is presented with aims of characterizing proportion of non-OSA sleep disorders in the first 90 days after stroke, evaluating the effect of non-OSA sleep disorders on poststroke recovery, and exploring the complex relationships between stroke, sleep, and recovery in the community setting. METHODS: SLEEPR is a prospective cohort observational study across multiple study sites following individuals from inpatient rehabilitation through 90 days poststroke, with three measurement time points (inpatient rehabilitation; i.e., ~15 days poststroke, 60 days poststroke, and 90 days poststroke). Measures of sleep, function, activity, cognition, emotion, disability, and participation will be obtained for 200 people without OSA at the study's start through self-report, capacity assessments, and performance measures. Key measures of sleep include wrist actigraphy, sleep diaries, overnight oximetry, and several sleep disorders screening questionnaires (Insomnia Severity Index, Cambridge-Hopkins Restless Legs Questionnaire, Epworth Sleepiness Scale, and Sleep Disorders Screening Checklist). Key measures of function and capacity include the 10-meter walk test, Stroke Impact Scale, Barthel index, and modified Rankin scale. Key performance measures include leg accelerometry (e.g., steps/day, sedentary time, upright time, and sit-to-stand transitions) and community trips via GPS data and activity logs. DISCUSSION: The results of this study will contribute to understanding the complex interplay between non-OSA sleep disorders and poststroke rehabilitation; they provide insight regarding barriers to participation in the community and return to normal activities after stroke. Such results could lead to strategies for developing new stroke recovery interventions.

Minimal Clinically Important Difference of the 6-Minute Walk Test in People With Stroke.

BACKGROUND AND PURPOSE: The 6-minute walk test (6MWT) is commonly used in people with stroke. The purpose of this study was to estimate the minimal clinically important difference (MCID) of the 6MWT 2 months poststroke. METHODS: We performed a secondary analysis of data from a rehabilitation trial. Participants underwent physical therapy between 2 and 6 months poststroke and the 6MWT was measured before and after. Two anchors of important change were used: the modified Rankin Scale (mRS) and the Stroke Impact Scale (SIS). The MCID for the 6MWT was estimated using receiver operating characteristic curves for the entire sample and for 2 subgroups: initial gait speed (IGS) <0.40 m/s and ≥0.40 m/s. RESULTS: For the entire sample, the estimated MCID of the 6MWT was 71 m with the mRS as the anchor (area under the curve [AUC] = 0.66) and 65 m with the SIS as the anchor (AUC = 0.59). For participants with IGS <0.40 m/s, the estimated MCID was 44 m with the mRS as the anchor (AUC = 0.72) and 34 m with the SIS as the anchor (AUC = 0.62). For participants with IGS ≥0.40 m/s, the estimated MCID was 71 m with the mRS as the anchor (AUC = 0.59) and 130 m with the SIS as the anchor (AUC = 0.56). DISCUSSION AND CONCLUSIONS: Between 2 and 6 months poststroke, people whose IGS is <0.40 m/s and experience a 44-m improvement in the 6MWT may exhibit meaningful improvement in disability. However, we were not able to estimate an accurate MCID for the 6MWT in people whose IGS was ≥0.40 m/s. MCID values should be estimated across different levels of function and anchors of importance.Video Abstract available for more insights from the authors (see Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A232).

Predicting Home and Community Walking Activity Poststroke.

BACKGROUND AND PURPOSE: Walking ability poststroke is commonly assessed using gait speed categories developed by Perry et al. The purpose of this study was to reexamine factors that predict home and community ambulators determined from real-world walking activity data using activity monitors. METHODS: Secondary analyses of real-world walking activity from 2 stroke trials. Home (100-2499 steps/d), most limited community (2500-4499 steps/d), least limited community (5000-74 999), and full community (≥7500 steps/d) walking categories were developed based on normative data. Independent variables to predict walking categories were comfortable and fast gait speed, 6-minute walk test, Berg Balance Scale, Fugl Meyer, and Stroke Impact Scale. Data were analyzed using multivariate analyses to identify significant variables associated with walking categories, bootstrap method to select the most stable model and receiver-operating characteristic to identify cutoff values. RESULTS: Data from 441 individuals poststroke were analyzed. The 6-minute walk test, Fugl Meyer, and Berg Balance Scale combined were the strongest predictors of home versus community and limited versus unlimited community ambulators. The 6-minute walk test was the strongest individual variable in predicting home versus community (receiver-operating characteristic area under curve=0.82) and limited versus full community ambulators (receiver-operating characteristic area under curve=0.76). A comfortable gait speed of 0.49 m/s discriminated between home and community and a comfortable gait speed of 0.93 m/s discriminated between limited community and full community ambulators. CONCLUSIONS: The 6-minute walk test was better able to discriminate among home, limited community, and full community ambulators than comfortable gait speed. Gait speed values commonly used to distinguish between home and community walkers may overestimate walking activity.

Self-Selected Walking Speed is Predictive of Daily Ambulatory Activity in Older Adults.

Daily ambulatory activity is associated with health and functional status in older adults; however, assessment requires multiple days of activity monitoring. The objective of this study was to determine the relative capabilities of self-selected walking speed (SSWS), maximal walking speed (MWS), and walking speed reserve (WSR) to provide insight into daily ambulatory activity (steps per day) in community-dwelling older adults. Sixty-seven older adults completed testing and activity monitoring (age 80.39 [6.73] years). SSWS (R2 = .51), MWS (R2 = .35), and WSR calculated as a ratio (R2 = .06) were significant predictors of daily ambulatory activity in unadjusted linear regression. Cutpoints for participants achieving < 8,000 steps/day were identified for SSWS (≤ 0.97 m/s, 44.2% sensitivity, 95.7% specificity, 10.28 +LR, 0.58 -LR) and MWS (≤ 1.39 m/s, 60.5% sensitivity, 78.3% specificity, 2.79 +LR, 0.50 -LR). SSWS may be a feasible proxy for assessing and monitoring daily ambulatory activity in older adults.

Prevalence and Detection of Obstructive Sleep Apnea Early after Stroke.

Background: Obstructive sleep apnea (OSA) negatively impacts post-stroke recovery. This study's purpose: examine the prevalence of undiagnosed OSA and describe a simple tool to identify those at-risk for OSA in the early phase of stroke recovery. Methods: This was a cross-sectional descriptive study of people ∼15 days post-stroke. Adults with stroke diagnosis admitted to inpatient rehabilitation over a 3-year period were included if they were alert/arousable, able to consent/assent to participation, and excluded if they had a pre-existing OSA diagnosis, other neurologic health conditions, recent craniectomy, global aphasia, inability to ambulate 150 feet independently pre-stroke, pregnant, or inability to understand English. OSA was deemed present if oxygen desaturation index (ODI) of >=15 resulted from overnight oximetry measures. Prevalence of OSA was determined accordingly. Four participant characteristics comprised the "BASH" tool (body mass index >=35, age>=50, sex=male, hypertension=yes). A receiver operator characteristics (ROC) curve analysis was performed with BASH as test variable and OSA presence as state variable. Results: Participants (n=123) were 50.4% male, averaged 64.12 years old (sd 14.08), and self-identified race as 75.6% White, 20.3% Black/African American, 2.4%>1 race, and 1.6% other; 22% had OSA. ROC analysis indicated BASH score >=3 predicts presence of OSA (sensitivity=0.778, specificity=0.656, area under the curve =0.746, p<0.001). Conclusions: Prevalence of undiagnosed OSA in the early stroke recovery phase is high. With detection of OSA post-stroke, it may be possible to offset untreated OSA's deleterious impact on post-stroke recovery of function. The BASH tool is an effective OSA screener for this application.

Research from Low-Income and Middle-Income Countries will Benefit Global Health and the Physiotherapy Profession, but it Requires Support.

Disparities in research publications are common in the physiotherapy and rehabilitation fields.1 A small proportion of published research arises from low-income and middle-income countries (LMICs),1,2 home to 85% of the world's population. Systems-level, institutional-level, and individual-level factors contribute to these disparities. With urgent and unified actions, global health and the standard of physiotherapy research in LMICs can be improved and strengthened. In this editorial, we will discuss the challenges encountered by researchers from LMICs in conducting and publishing high-quality research and propose potential strategies to address these challenges.

Identifying activity levels and steps of people with stroke using a novel shoe-based sensor.

BACKGROUND/PURPOSE: Advances in sensor technologies provide a method to accurately assess activity levels of people with stroke in their community. This information could be used to determine the effectiveness of rehabilitation interventions as well as provide behavior-enhancing feedback. The purpose of this study was to assess the accuracy of a novel shoe-based sensor system (SmartShoe) to identify different functional postures and steps in people with stroke. The SmartShoe system consists of five force-sensitive resistors built into a flexible insole and an accelerometer on the back of the shoe. Pressure and acceleration data are sent via Bluetooth to a smart phone. METHODS: Participants with stroke wore the SmartShoe while they performed activities of daily living (ADLs) in sitting, standing, and walking positions. Data from four participants were used to develop a multilayer perceptron artificial neural network (ANN) to identify sitting, standing, and walking. A signal-processing algorithm used data from the pressure sensors to estimate the number of steps taken while walking. The accuracy, precision, and recall of the ANN for identifying the three functional postures were calculated with data from a different set of participants. Agreement between steps identified by SmartShoe and actual steps taken was analyzed by the Bland Altman method. RESULTS: The SmartShoe was able to accurately identify sitting, standing, and walking. Accuracy, precision, and recall were all greater than 95%. The mean difference between steps identified by SmartShoe and actual steps was less than one step. DISCUSSION: The SmartShoe was able to accurately identify different functional postures, using a unique combination of pressure and acceleration data, of people with stroke as they performed different ADLs. There was a strong level of agreement between actual steps taken and steps identified by the SmartShoe. Further study is needed to determine whether the SmartShoe could be used to provide valid information on activity levels of people with stroke while they go about their daily lives in their home and community.

Outcome measures in neurological physical therapy practice: part I. Making sound decisions.

Standardized outcome measures (OMs) are a vital part of evidence-based practice. Despite the recognition of the importance of OMs, recent evidence suggests that the use of OMs in clinical practice is limited. Selecting the most appropriate OM enhances clinical practice by (1) identifying and quantifying body function and structure limitations; (2) formulating the evaluation, diagnosis, and prognosis; (3) informing the plan of care; and (4) helping to evaluate the success of physical therapy interventions. This article (Part I) is the first of a 2-part series on the process of selecting OMs in neurological clinical practice. We introduce a decision-making framework to guide the selection of OMs and discuss 6 main factors-what to measure, the purpose of the measure, the type of measure, patient and clinic factors, psychometric factors, and feasibility-that should be considered when selecting OMs for clinical use. The framework will then be applied to a patient case in Part II of the series (see the article "Outcome Measures in Neurological Physical Therapy Practice: Part II. A Patient-Centered Process" in this issue).

Estimating clinically important change in gait speed in people with stroke undergoing outpatient rehabilitation.

BACKGROUND AND PURPOSE: Gait speed is commonly used to assess walking ability in people with stroke. It is not clear how much change in gait speed reflects an important change in walking ability. The purpose of this study was to estimate clinically important changes in gait speed by using 2 different anchors for what is considered "important": stroke survivors and physical therapists perceptions of change in walking ability. METHODS: Participants underwent outpatient physical therapy (mean 56 days post-stroke) after a first-time stroke. Self-selected gait speed was measured at admission and discharge. At discharge, participants and their physical therapists rated their perceived change in walking ability on a 15-point ordinal Global Rating of Change (GROC) scale. Estimated important change values for gait speed were calculated by using receiver operating characteristics curves, with the participants and physical therapists GROC as the anchors. RESULTS: The mean (SD) initial gait speed of all participants was 0.56 (0.22) m/s. The estimated important change in gait speed ranged from 0.175 m/s (participants perceived change in walking ability) to 0.190 m/s (physical therapists perceived change in walking ability), depending on the anchor. DISCUSSION AND CONCLUSIONS: During the subacute stage of recovery, individuals poststroke who experience improvements in gait speed of 0.175 m/s or greater are likely to exhibit a meaningful improvement in walking ability. The estimated clinically important change value of 0.175 m/s can be used by clinicians to set goals and interpret change in individual patients and by researchers to compare important change between groups.

Using sensors to measure activity in people with stroke.

PURPOSE: The purpose of this study was to determine the ability of a novel shoe-based sensor that uses accelerometers, pressure sensors, and pattern recognition with a support vector machine (SVM) to accurately identify sitting, standing, and walking postures in people with stroke. METHODS: Subjects with stroke wore the shoe-based sensor while randomly assuming 3 main postures: sitting, standing, and walking. A SVM classifier was used to train and validate the data to develop individual and group models, which were tested for accuracy, recall, and precision. RESULTS: Eight subjects participated. Both individual and group models were able to accurately identify the different postures (99.1% to 100% individual models and 76.9% to 100% group models). Recall and precision were also high for both individual (0.99 to 1.00) and group (0.82 to 0.99) models. CONCLUSIONS: The unique combination of accelerometer and pressure sensors built into the shoe was able to accurately identify postures. This shoe sensor could be used to provide accurate information on community performance of activities in people with stroke as well as provide behavioral enhancing feedback as part of a telerehabilitation intervention.

Predicting home and community walking activity in people with stroke.

OBJECTIVE: To determine the ability of the 6-minute walk test (6MWT) and other commonly used clinical outcome measures to predict home and community walking activity in high-functioning people with stroke. DESIGN: Cross-sectional. SETTING: Outpatient physical therapy clinic. PARTICIPANTS: Participants (N=32) with chronic stroke (n=19; >6mo poststroke) with self-selected gait speed (GS) faster than .40m/s and age-matched healthy participants (n=13). INTERVENTIONS: Not applicable. INDEPENDENT VARIABLES: 6MWT, self-selected GS, Berg Balance Scale (BBS), lower extremity motor section of the Fugl-Meyer Assessment, and Stroke Impact Scale. Dependent variable: average steps taken per day during a 7-day period, measured using an accelerometer. RESULTS: 6MWT, self-selected GS, and BBS were moderately related to home and community walking activity. The 6MWT was the only predictor of average steps taken per day; it explained 46% of the variance in steps per day. CONCLUSIONS: The 6MWT is a useful outcome measure in higher functioning people with stroke to guide intervention and assess community walking activity.

The effects of diabetes and/or peripheral neuropathy in detecting short postural perturbations in mature adults.

BACKGROUND: This study explored the effects of diabetes mellitus (DM) and peripheral neuropathy (PN) on the ability to detect near-threshold postural perturbations. METHODS: 83 subjects participated; 32 with type II DM (25 with PN and 7 without PN), 19 with PN without DM, and 32 without DM or PN. Peak acceleration thresholds for detecting anterior platform translations of 1 mm, 4 mm, and 16 mm displacements were determined. A 2(DM) × 2(PN) factorial MANCOVA with weight as a covariate was calculated to compare acceleration detection thresholds among subjects who had DM or did not and who had PN or did not. RESULTS: There was a main effect for DM but not for PN. Post hoc analysis revealed that subjects with DM required higher accelerations to detect a 1 mm and 4 mm displacement. CONCLUSION: Our findings suggest that PN may not be the only cause of impaired balance in people with DM. Clinicians should be aware that diabetes itself might negatively impact the postural control system.

How much change in the stroke impact scale-16 is important to people who have experienced a stroke?

BACKGROUND: The Stroke Impact Scale-16 (SIS-16) is used clinically and in research to measure quality of life after stroke. There are no studies that have estimated how much change on the SIS-16 is an important amount of change. The aim of this study was to estimate the minimal clinically important difference (MCID) of the SIS-16. METHOD: SIS-16 scores of participants receiving services at 2 outpatient physical therapy clinics who met inclusion and exclusion criteria (n = 36) were taken at baseline and discharge. At discharge, participants and their physical therapists rated their perceived amount of recovery on a Global Rating of Change (GROC) scale. Estimated MCID values were calculated for the SIS-16 using receiver operating characteristics curves with the GROC as anchors. RESULTS: There was no difference in baseline characteristics between participants who reported important improvement and those who did not. There was a fair relationship between change in SIS-16 scores and participants' (0.41) and physical therapists' (0.38) GROC scores. Change in SIS-16 scores was significantly greater in participants who reported an important amount of change on the GROC scale and those who did not. Estimated MCID of the SIS-16 ranged from 9.4 to 14.1 depending on the anchor. CONCLUSION: The estimated MCID values presented in this study provide a way for clinicians to evaluate meaningful change in individual patients and for researchers to evaluate meaningful change between groups.

The Impact of Sleep Disorders on Functional Recovery and Participation Following Stroke: A Systematic Review and Meta-Analysis.

BACKGROUND: Adequate sleep is vital for health and quality of life. People with stroke and a concomitant sleep disorder may have poorer outcomes than those without a sleep disorder. OBJECTIVE: To systematically evaluate the published literature to determine the impact of sleep disorders on physical, functional recovery at the activity and participation level after stroke. METHODS: A systematic review was conducted using PubMed, CINAHL, Scopus, and PsycINFO. Studies were selected that reported outcomes on physical, functional recovery at the activity and participation levels in participants with stroke and a diagnosed sleep disorder. A meta-analysis was performed on included studies that reported Barthel Index (BI) and modified Rankin Scale (mRS) scores. Results: A total of 33 studies were included in the systematic review with 9 of them in the meta-analysis. The mean mRS score was 0.51 points higher in participants with stroke and sleep disorders versus participants with stroke without sleep disorder [95% CI: 0.23-0.78]. The mean BI score was 10.2 points lower in participants with stroke and sleep disorders versus participants with stroke without sleep disorder [95% CI: -17.9 to -2.6]. CONCLUSIONS: People with stroke and a sleep disorder have greater functional limitations and disability than those without a sleep disorder. Rehabilitation professionals should screen their patients with stroke for potential sleep disorders and further research is needed to develop sleep and rehabilitation interventions that can be delivered in combination. PROSPERO registration number: CRD42019125562.