National surveillance using a clinical quality indicator for prolonged antipsychotic use among older Australians with dementia who access aged care services.

OBJECTIVES: Dementia guidelines recommend antipsychotics are only used for behavioral and psychological symptoms when non-drug interventions fail, and to regularly review use. Population-level clinical quality indicators (CQIs) for dementia care in permanent residential aged care (PRAC) typically monitor prevalence of antipsychotic use but not prolonged use. This study aimed to develop a CQI for antipsychotic use >90 days and examine trends, associated factors, and variation in CQI incidence; and examine duration of the first episode of use among individuals with dementia accessing home care packages (HCPs) or PRAC. METHODS: Retrospective cohort study, including older individuals with dementia who accessed HCPs (n = 50,257) or PRAC (n = 250,196). Trends in annual CQI incidence (2011-12 to 2015-16) and associated factors were determined using Poisson regression. Funnel plots examined geographical and facility variation. Time to antipsychotic discontinuation was estimated among new antipsychotic users accessing HCP (n = 2367) and PRAC (n = 15,597) using the cumulative incidence function. RESULTS: Between 2011-12 and 2015-16, antipsychotic use for >90 days decreased in HCP recipients from 10.7% (95% CI 10.2-11.1) to 10.1% (95% CI 9.6-10.5, adjusted incidence rate ratio (aIRR) 0.97 (95% CI 0.95-0.98)), and in PRAC residents from 24.5% (95% CI 24.2-24.7) to 21.8% (95% CI 21.5-22.0, aIRR 0.97 (95% CI 0.96-0.98)). Prior antipsychotic use (both cohorts) and being male and greater socioeconomic disadvantage (PRAC cohort) were associated with higher CQI incidence. Little geographical/facility variation was observed. Median treatment duration in HCP and PRAC was 334 (interquartile range [IQR] 108-958) and 555 (IQR 197-1239) days, respectively. CONCLUSIONS: While small decreases in antipsychotic use >90 days were observed between 2011-12 and 2015-16, findings suggest antipsychotic use among aged care recipients with dementia can be further minimized.

Quantifying the effects of sleep on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment.

BACKGROUND: Despite the promise of wearable sensors for both rehabilitation research and clinical care, these technologies pose significant burden on data collectors and analysts. Investigations of factors that may influence the wearable sensor data processing pipeline are needed to support continued use of these technologies in rehabilitation research and integration into clinical care settings. The purpose of this study was to investigate the effect of one such factor, sleep, on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment and across a two-day wearing period. METHODS: This was a secondary analysis of data collected during a prospective, longitudinal cohort study (n = 127 individuals, 62 with upper limb impairment and 65 without). Participants wore a wearable sensor on each wrist for 48 h. Five upper limb sensor variables were calculated over the full wear period (sleep included) and with sleep time removed (sleep excluded): preferred time, non-preferred time, use ratio, non-preferred magnitude and its standard deviation. Linear mixed effects regression was used to quantify the effect of sleep on each sensor variable and determine if the effect differed between people with and without upper limb impairment and across a two-day wearing period. RESULTS: There were significant differences between sleep included and excluded for the variables preferred time (p < 0.001), non-preferred time (p < 0.001), and non-preferred magnitude standard deviation (p = 0.001). The effect of sleep was significantly different between people with and without upper limb impairment for one variable, non-preferred magnitude (p = 0.02). The effect of sleep was not substantially different across wearing days for any of the variables. CONCLUSIONS: Overall, the effects of sleep on sensor-derived variables of upper limb accelerometry are small, similar between people with and without upper limb impairment and across a two-day wearing period, and can likely be ignored in most contexts. Ignoring the effect of sleep would simplify the data processing pipeline, facilitating the use of wearable sensors in both research and clinical practice.

Predicting later categories of upper limb activity from earlier clinical assessments following stroke: an exploratory analysis.

BACKGROUND: Accelerometers allow for direct measurement of upper limb (UL) activity. Recently, multi-dimensional categories of UL performance have been formed to provide a more complete measure of UL use in daily life. Prediction of motor outcomes after stroke have tremendous clinical utility and a next step is to explore what factors might predict someone's subsequent UL performance category. PURPOSE: To explore how different machine learning techniques can be used to understand how clinical measures and participant demographics captured early after stroke are associated with the subsequent UL performance categories. METHODS: This study analyzed data from two time points from a previous cohort (n = 54). Data used was participant characteristics and clinical measures from early after stroke and a previously established category of UL performance at a later post stroke time point. Different machine learning techniques (a single decision tree, bagged trees, and random forests) were used to build predictive models with different input variables. Model performance was quantified with the explanatory power (in-sample accuracy), predictive power (out-of-bag estimate of error), and variable importance. RESULTS: A total of seven models were built, including one single decision tree, three bagged trees, and three random forests. Measures of UL impairment and capacity were the most important predictors of the subsequent UL performance category, regardless of the machine learning algorithm used. Other non-motor clinical measures emerged as key predictors, while participant demographics predictors (with the exception of age) were generally less important across the models. Models built with the bagging algorithms outperformed the single decision tree for in-sample accuracy (26-30% better classification) but had only modest cross-validation accuracy (48-55% out of bag classification). CONCLUSIONS: UL clinical measures were the most important predictors of the subsequent UL performance category in this exploratory analysis regardless of the machine learning algorithm used. Interestingly, cognitive and affective measures emerged as important predictors when the number of input variables was expanded. These results reinforce that UL performance, in vivo, is not a simple product of body functions nor the capacity for movement, instead being a complex phenomenon dependent on many physiological and psychological factors. Utilizing machine learning, this exploratory analysis is a productive step toward the prediction of UL performance. Trial registration NA.

The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke.

The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.

Accuracy of an Algorithm in Predicting Upper Limb Functional Capacity in a United States Population.

OBJECTIVE: To determine the accuracy of an algorithm, using clinical measures only, on a sample of persons with first-ever stroke in the United States (US). It was hypothesized that algorithm accuracy would fall in a range of 70%-80%. DESIGN: Secondary analysis of prospective, observational, longitudinal cohort; 2 assessments were done: (1) within 48 hours to 1 week poststroke and (2) at 12 weeks poststroke. SETTING: Recruited from a large acute care hospital and followed over the first 6 months after stroke. PARTICIPANTS: Adults with first-ever stroke (N=49) with paresis of the upper limb (UL) at ≤48 hours who could follow 2-step commands and were expected to return to independent living at 6 months. INTERVENTION: Not applicable. MAIN OUTCOME MEASURES: The overall accuracy of the algorithm with clinical measures was quantified by comparing predicted (expected) and actual (observed) categories using a correct classification rate. RESULTS: The overall accuracy (61%) and weighted κ (62%) were significant. Sensitivity was high for the Excellent (95%) and Poor (81%) algorithm categories. Specificity was high for the Good (82%), Limited (98%), and Poor (95%) categories. Positive predictive value (PPV) was high for Poor (82%) and negative predictive value (NPV) was high for all categories. No differences in participant characteristics were found between those with accurate or inaccurate predictions. CONCLUSIONS: The results of the present study found that use of an algorithm with clinical measures only is better than chance alone (chance=25% for each of the 4 categories) at predicting a category of UL capacity at 3 months post troke. The moderate to high values of sensitivity, specificity, PPV, and NPV demonstrates some clinical utility of the algorithm within health care settings in the US.

Clinical Performance Measures for Stroke Rehabilitation: Performance Measures From the American Heart Association/American Stroke Association.

The American Heart Association/American Stroke Association released the adult stroke rehabilitation and recovery guidelines in 2016. A working group of stroke rehabilitation experts reviewed these guidelines and identified a subset of recommendations that were deemed suitable for creating performance measures. These 13 performance measures are reported here and contain inclusion and exclusion criteria to allow calculation of rates of compliance in a variety of settings ranging from acute hospital care to postacute care and care in the home and outpatient setting.

Day-to-Day Variability of Walking Performance Measures in Individuals Poststroke and Individuals With Parkinson Disease.

BACKGROUND AND PURPOSE: Improvement of walking performance is a primary goal for individuals poststroke or with Parkinson disease (PD) who receive physical therapy. More data about day-to-day variability of walking performance are critical for determining if changes in performance have occurred. METHODS: Baseline assessments were utilized from an ongoing, observational, prospective cohort study including 84 individuals poststroke (n = 37) or with PD (n = 47) receiving outpatient physical therapy services to improve mobility. Participants wore step activity monitors for up to 7 days to measure walking performance (steps per day, walking duration, maximum 30-minute output, and peak activity index) in daily life. Correlation analyses evaluated relationships between both capacity and performance measures as well as the relationships between mean performance variables and day-to-day variability. Regression analyses explored factors that contribute to variability in day-to-day performance variables. RESULTS: Mean steps per day for participants poststroke (5376 ± 2804) and with PD (8149 ± 4490) were consistent with previously reported cohorts. Greater amounts of walking were related to more day-to-day variability, with moderate correlations found between the mean and day-to-day variability of each performance measure, regardless of medical diagnosis or walking speed. Day-to-day variability is large (upwards of 50% of the mean), with the amount of walking performance serving as the primary predictor of day-to-day variability in walking performance. DISCUSSION AND CONCLUSIONS: The results of this study elucidate the factors that are related to and predict day-to-day variability of performance. Walking performance metrics should be evaluated over multiple days and greater variability should be anticipated with greater amounts of performance.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A319).

The prevalence, trends and determinants of mental health disorders in older Australians living in permanent residential aged care: Implications for policy and quality of aged care services.

OBJECTIVE: Mental health disorders are a major health concern in older people and are associated with a higher risk of disability, frailty and early mortality. This study aimed to conduct a contemporary population-based assessment of the prevalence, trends and factors associated with mental health disorders in individuals who are living in permanent residential aged care (PRAC) in Australia. METHODS: A retrospective cross-sectional study was conducted using national data from the Registry of Senior Australians, a national cohort of older Australians who had aged care eligibility assessment and entered PRAC between 2008 and 2016. Stepwise multivariate logistic regression modeling was applied to identify factors associated with mental health disorders. RESULTS: Of 430,862 individuals included in this study, 57.8% had at least one mental health disorder. The prevalence of depression, phobia/anxiety and psychosis were as follows: 46.2% (95% confidence interval = [46.0%, 46.3%]), 14.9% (95% confidence interval = [14.8%, 15.0%]) and 9.7% (95% confidence interval = [9.6%, 9.8%]), respectively. The likelihood of having a mental health disorder was higher for those who were (adjusted odds ratio [95% confidence interval]) relatively younger, specifically for every 10-year increment in age, the odds of having mental health disorders was 44.0% lower (0.56, [0.55, 0.56]); female (1.33 [1.32, 1.35]); having increasing numbers of physical health comorbidities, 6-10 (1.26 [1.24, 1.29]) or 11-15 (1.48 [1.45, 1.51]) or more than 15 (1.64 [1.58, 1.71]) compared to people having less than five comorbidities; having limitations related to health care tasks (1.05 [1.04, 1.07]), meals (1.04 [1.02, 1.05]) or social and community participation (1.10 [1.08, 1.12]). CONCLUSION: The burden of mental health disorders in older Australians living in PRAC was high and individuals with these conditions tend to be younger, with several physical comorbidities and/or functional limitations. Understanding the profile of individuals with mental health disorders at entry into PRAC can be used as evidence for baseline resource allocation for this population and evaluation of future needs of mental health services.

Relationships between accelerometry and general compensatory movements of the upper limb after stroke.

BACKGROUND: Standardized assessments are used in rehabilitation clinics after stroke to measure restoration versus compensatory movements of the upper limb. Accelerometry is an emerging tool that can bridge the gap between in- and out-of-clinic assessments of the upper limb, but is limited in that it currently does not capture the quality of a person's movement, an important concept to assess compensation versus restoration. The purpose of this analysis was to characterize how accelerometer variables may reflect upper limb compensatory movement patterns after stroke. METHODS: This study was a secondary analysis of an existing data set from a Phase II, single-blind, randomized, parallel dose-response trial (NCT0114369). Sources of data utilized were: (1) a compensatory movement score derived from video analysis of the Action Research Arm Test (ARAT), and (2) calculated accelerometer variables quantifying time, magnitude and variability of upper limb movement from the same time point during study participation for both in-clinic and out-of-clinic recording periods. RESULTS: Participants had chronic upper limb paresis of mild to moderate severity. Compensatory movement scores varied across the sample, with a mean of 73.7 ± 33.6 and range from 11.5 to 188. Moderate correlations were observed between the compensatory movement score and each accelerometer variable. Accelerometer variables measured out-of-clinic had stronger relationships with compensatory movements, compared with accelerometer variables in-clinic. Variables quantifying time, magnitude, and variability of upper limb movement out-of-clinic had relationships to the compensatory movement score. CONCLUSIONS: Accelerometry is a tool that, while measuring movement quantity, can also reflect the use of general compensatory movement patterns of the upper limb in persons with chronic stroke. Individuals who move their limbs more in daily life with respect to time and variability tend to move with less movement compensations and more typical movement patterns. Likewise, individuals who move their paretic limbs less and their non-paretic limb more in daily life tend to move with more movement compensations at all joints in the paretic limb and less typical movement patterns.

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field.

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples' homes and communities.

Dose of remote limb ischemic conditioning for enhancing learning in healthy young adults.

Remote limb ischemic conditioning (RLIC) is a technique in which tissues distant from the target organ are exposed to brief, sub-lethal bouts of ischemia. The effects of remotely applied ischemic conditioning are systemically transferred to the target organ, and typically manifested as protection from subsequent ischemic injury. Previous studies in our lab have found and confirmed that RLIC enhances learning and retention during motor training on a balance task. The current study tested the effect of RLIC dose (number of cycles) on learning enhancement in young, healthy adults. Forty healthy participants age 18-40 years were randomized to receive 5 cycles of sham conditioning (n = 9), 3 cycles of RLIC (n = 11), 4 cycles of RLIC (n = 10), or 5 cycles of RLIC (n = 10) using a blood pressure cuff around the upper arm once a day for 7 consecutive weekdays (Days 1-7). Participants concurrently trained on a balance task, bimanual cup stacking task, and a discrete sequence production task on Days 3-7. Change in performance on each of the three tasks was compared across groups. Participants in all four groups improved their performance on each of the three tasks over time. However, RLIC at any dose did not enhance learning on any of the three tasks. While RLIC is safe, inexpensive, and clinically feasible, reproducibility may be challenged by unidentified factors, raising critical challenges to the straightforward translation of RLIC for improving rehabilitation outcomes in individuals recovering from neurological injury.

Belief, Confidence, and Motivation to Use the Paretic Upper Limb in Daily Life Over the First 24 Weeks After Stroke.

BACKGROUND AND PURPOSE: The recovery patterns of upper limb (UL) impairment after stroke are established. Psychosocial factors such as belief that paretic UL recovery is possible, confidence, and motivation to use the paretic UL in everyday tasks are unexplored early after stroke. The purpose of this exploratory study was to characterize belief, confidence, and motivation to use the paretic UL in daily life, and self-perceived barriers to UL recovery over the first 24 weeks after stroke. METHODS: This was a longitudinal cohort study (N = 30) with 8 assessment sessions over the first 24 weeks after stroke. Belief, confidence, and motivation to use the paretic UL and self-perceived barriers were quantified via survey and analyzed using descriptive statistics. Change in the number of self-perceived barriers between weeks 2 and 24 was tested using a paired-samples t test. The relationship between UL capacity, depressive symptomatology, cognition, and each psychosocial factor was examined using Spearman rank-order correlation analyses. RESULTS: Twenty-two participants completed all study assessments. Belief, confidence, and motivation were high across the 24 weeks, with little variation. There was no difference between the average number of barriers from weeks 2 to 24. There was no relationship between the clinical measures and psychosocial factors at week 2, 12, or 24. DISCUSSION AND CONCLUSIONS: High levels of belief, confidence, and motivation appear consistent over the first 6 months after stroke. The lack of correlations between psychosocial factors and clinical measures suggests belief, confidence, and motivation may not be vulnerable to functional status early after stroke.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A283).

Sensor Measures of Symmetry Quantify Upper Limb Movement in the Natural Environment Across the Lifespan.

Knowledge of upper limb activity in the natural environment is critical for evaluating the effectiveness of rehabilitation services. Wearable sensors allow efficient collection of these data and have the potential to be less burdensome than self-report measures of activity. Sensors can capture many different variables of activity and daily performance, many of which could be useful in identifying deviation from typical movement behavior or measuring outcomes from rehabilitation interventions. Although it has potential, sensor measurement is just emerging, and there is a lack of consensus regarding which variables of daily performance are valid, sensitive, specific, and useful. We propose that symmetry of full-day upper limb movement is a key variable. We describe here that symmetry is valid, robustly observed within a narrow range across the lifespan in typical development, and shows evidence of being different in populations with neuromotor impairment. Key next steps include the determination of sensitivity, specificity, minimal detectable change, and minimal clinically important change/difference. This information is needed to determine whether an individual belongs to the typical or atypical group, whether change has occurred, and whether that change is beneficial.

Comparison of Self-Report Versus Sensor-Based Methods for Measuring the Amount of Upper Limb Activity Outside the Clinic.

OBJECTIVE: To compare self-reported with sensor-measured upper limb (UL) performance in daily life for individuals with chronic (≥6mo) UL paresis poststroke. DESIGN: Secondary analysis of participants enrolled in a phase II randomized, parallel, dose-response UL movement trial. This analysis compared the accuracy and consistency between self-reported UL performance and sensor-measured UL performance at baseline and immediately post an 8-week intensive UL task-specific intervention. SETTING: Outpatient rehabilitation. PARTICIPANTS: Community-dwelling individuals with chronic (≥6mo) UL paresis poststroke (N=64). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Motor Activity Log amount of use scale and the sensor-derived use ratio from wrist-worn accelerometers. RESULTS: There was a high degree of variability between self-reported UL performance and the sensor-derived use ratio. Using sensor-based values as a reference, 3 distinct categories were identified: accurate reporters (reporting difference ±0.1), overreporters (difference >0.1), and underreporters (difference <-0.1). Five of 64 participants accurately self-reported UL performance at baseline and postintervention. Over half of participants (52%) switched categories from pre-to postintervention (eg, moved from underreporting preintervention to overreporting postintervention). For the consistent reporters, no participant characteristics were found to influence whether someone over- or underreported performance compared with sensor-based assessment. CONCLUSIONS: Participants did not consistently or accurately self-report UL performance when compared with the sensor-derived use ratio. Although self-report and sensor-based assessments are moderately associated and appear similar conceptually, these results suggest self-reported UL performance is often not consistent with sensor-measured performance and the measures cannot be used interchangeably.

On the Reporting of Experimental and Control Therapies in Stroke Rehabilitation Trials: A Systematic Review.

OBJECTIVE: To use the Centralized Open-Access Rehabilitation database for Stroke to explore reporting of both experimental and control interventions in randomized controlled trials for stroke rehabilitation (including upper and lower extremity therapies). DATA SOURCES: The Centralized Open-Access Rehabilitation database for Stroke was created from a search of MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Cumulative Index of Nursing and Allied Health from the earliest available date to May 31, 2014. STUDY SELECTION: A total of 2892 titles were reduced to 514 that were screened by full text. This screening left 215 randomized controlled trials in the database (489 independent groups representing 12,847 patients). DATA EXTRACTION: Using a mixture of qualitative and quantitative methods, we performed a text-based analysis of how the procedures of experimental and control therapies were described. Experimental and control groups were rated by 2 independent coders according to the Template for Intervention Description and Replication criteria. DATA SYNTHESIS: Linear mixed-effects regression with a random effect of study (groups nested within studies) showed that experimental groups had statistically more words in their procedures (mean, 271.8 words) than did control groups (mean, 154.8 words) (P<.001). Experimental groups had statistically more references in their procedures (mean, 1.60 references) than did control groups (mean, .82 references) (P<.001). Experimental groups also scored significantly higher on the total Template for Intervention Description and Replication checklist (mean score, 7.43 points) than did control groups (mean score, 5.23 points) (P<.001). CONCLUSIONS: Control treatments in stroke motor rehabilitation trials are underdescribed relative to experimental treatments. These poor descriptions are especially problematic for "conventional" therapy control groups. Poor reporting is a threat to the internal validity and generalizability of clinical trial results. We recommend authors use preregistered protocols and established reporting criteria to improve transparency.

Medical Rehabilitation: Guidelines to Advance the Field With High-Impact Clinical Trials.

The purpose of this Special Communication is to summarize guidelines and recommendations stemming from an expert panel convened by the National Institutes of Health, National Center for Medical Rehabilitation Research (NCMRR) for a workshop entitled The Future of Medical Rehabilitation Clinical Trials, held September 29-30, 2016, at the NCMRR offices in Bethesda, Maryland. The ultimate goal of both the workshop and this summary is to offer guidance on clinical trials design and operations to the medical rehabilitation research community, with the intent of maximizing the effect of future trials.

A feasibility study of a novel, task-specific movement training intervention for women with patellofemoral pain.

OBJECTIVE: To investigate whether a novel, task-specific training intervention that focused on correcting pain-producing movement patterns was feasible and whether it would improve hip and knee kinematics, pain, and function in women with patellofemoral pain. DESIGN: Prospective, non-randomized, within-group, double baseline, feasibility intervention study. SUBJECTS: A total of 25 women with patellofemoral pain were enrolled. INTERVENTION: The intervention, delivered 2×/week for six weeks, consisted of supervised, high-repetition practice of daily weight-bearing and recreational activities. Activities were selected and progressed based on participants' interest and ability to maintain optimal alignment without increasing pain. MAIN MEASURES: Primary feasibility outcomes were recruitment, retention, adherence, and treatment credibility (Credibility/Expectancy Questionnaire). Secondary outcomes assessing intervention effects were hip and knee kinematics, pain (visual analog scale: current, average in past week, maximum in past week), and function (Patient-Specific Functional Scale). RESULTS: A total of 25 participants were recruited and 23 were retained (92% retention). Self-reported average daily adherence was 79% and participants were able to perform their prescribed home program correctly (reduced hip and knee frontal plane angles) by the second intervention visit. On average, treatment credibility was rated 25 (out of 27) and expectancy was rated 22 (out of 27). Hip and knee kinematics, pain, and function improved following the intervention when compared to the control phase. CONCLUSION: Based on the feasibility outcomes and preliminary intervention effects, this task-specific training intervention warrants further investigation and should be evaluated in a larger, randomized clinical trial.

Dose response of task-specific upper limb training in people at least 6 months poststroke: A phase II, single-blind, randomized, controlled trial.

OBJECTIVE: The objectives of this work were to (1) determine whether higher doses of motor therapy in chronic poststroke hemiparesis result in better outcomes, compared to lower doses, and (2) evaluate potential modifiers of the dose-response relationship. METHODS: Eighty-five adults with upper extremity paresis ≥6 months poststroke were randomized to one of four dose groups in this single-blind, parallel, randomized, control trial. The dosing parameter manipulated was amount of task-specific training, as indexed by the number of task repetitions. Groups received 3,200, 6,400, 9,600, or individualized maximum (IM) repetitions, during 1-hour sessions, 4 days/week for 8 weeks. The intervention was an individualized, progressive, task-specific upper-limb training program designed to improve upper-limb functional motor capacity. The primary outcome was the slope of the Action Research Arm Test (ARAT) during the intervention. Effects of dose and potential modifiers of the dose-response relationship were evaluated with hierarchical linear models. RESULTS: ARAT scores for the 3,200, 9,600, and IM groups improved over time as indicated by slopes (ΔARAT/week, mean ± standard errors) of 0.40 ± 0.15, 0.31 ± 0.16, and 0.66 ± 0.14, respectively (p < 0.05). The slope of the 6,400 group was smaller (-0.05 ± 0.15) and significantly different from the 3,200 and IM groups (p < 0.001). Initial motor capacity, neglect, and other tested characteristics did not modify the dose-response relationship. INTERPRETATION: Overall, treatment effects were small. There was no evidence of a dose-response effect of task-specific training on functional capacity in people with long-standing upper-limb paresis poststroke. Ann Neurol 2016;80:342-354.

Consideration of Dose and Timing When Applying Interventions After Stroke and Spinal Cord Injury.

BACKGROUND AND PURPOSE: Nearly 4 decades of investigation into the plasticity of the nervous system suggest that both timing and dose could matter. This article provides a synopsis of our lectures at the IV STEP meeting, which presented a perspective of current data on the issues of timing and dose for adult stroke and spinal cord injury motor rehabilitation. SUMMARY OF KEY POINTS: For stroke, the prevailing evidence suggests that greater amounts of therapy do not result in better outcomes for upper extremity interventions, regardless of timing. Whether or not greater amounts of therapy result in better outcomes for lower extremity and mobility interventions needs to be explicitly tested. For spinal cord injury, there is a complex interaction of timing postinjury, task-specificity, and the microenvironment of the spinal cord. Inflammation appears to be a key determinant of whether or not an intervention will be beneficial or maladaptive, and specific retraining of eccentric control during gait may be necessary. RECOMMENDATIONS FOR CLINICAL PRACTICE: To move beyond the limitations of our current interventions and to effectively reach nonresponders, greater precision in task-specific interventions that are well-timed to the cellular environment may hold the key. Neurorehabilitation that ameliorates persistent deficits, attains greater recovery, and reclaims nonresponders will decrease institutionalization, improve quality of life, and prevent multiple secondary complications common after stroke and spinal cord injury.