远程康复
医学
冲程(发动机)
康复
痉挛
物理疗法
物理医学与康复
随机对照试验
方差分析
远程医疗
内科学
经济增长
机械工程
工程类
医疗保健
经济
作者
Sang Min Paik,Steven C. Cramer
标识
DOI:10.1177/1357633x211023353
摘要
Introduction Telerehabilitation (TR) may be useful for rehabilitation therapy after stroke. However, stroke is a heterogeneous condition, and not all patients can be expected to derive the same benefit from TR, underscoring the need to identify predictors of response to TR. Methods A prior trial provided patients with 6 weeks of intensive rehabilitation therapy targeting arm movement, randomly assigned to be provided in the home via TR (current focus) or in clinic. Eligible patients had moderate arm motor deficits and were in the subacute–chronic stage post stroke. Behavioral gains were measured as change in the arm motor Fugl-Meyer score from baseline to 30 days post therapy. To delineate predictors of TR response, multivariable linear regression was performed, advancing the most significant predictor from each of eight categories: patient demographics, stroke characteristics, medical history, rehabilitation therapy outside of study procedures, motivation, sensorimotor impairment, cognitive/affective deficits, and functional status. Results The primary focus was on patients starting TR >90 days post stroke onset ( n = 44), among whom female sex, less spasticity, and less visual field defects predicted greater motor gains. This model explained 39.3% of the variance in treatment-related gains. In secondary analysis that also included TR patients enrolled ≤90 days post stroke (total n = 59), only female sex was a predictor of treatment gains. A separate secondary analysis examined patients >90 days post stroke ( n = 34) randomized to in-clinic therapy, among whom starting therapy earlier post stroke and less ataxia predicted greater motor gains. Discussion Response to TR varies across patients, emphasizing the need to identify characteristics that predict treatment-related behavioral gain. The current study highlights factors that might be important to patient selection for home-based TR after stroke.
科研通智能强力驱动
Strongly Powered by AbleSci AI