Lohse Keith R, Miller Allison E, Bland Marghuretta D, Lee Jin-Moo, Lang Catherine E
Program in Physical Therapy (K.R.L., A.E.M., M.D.B., C.E.L.), Washington University School of Medicine, St Louis, MO.
Department of Neurology (K.R.L., M.D.B., J.-M.L., C.E.L.), Washington University School of Medicine, St Louis, MO.
Stroke. 2025 Aug;56(8):2079-2090. doi: 10.1161/STROKEAHA.124.050229. Epub 2025 Apr 23.
Stroke is a leading cause of long-term disability, but advances for rehabilitation have lagged those for acute treatment. Large biological studies (eg, omics) may offer mechanistic insights for recovery but require collecting detailed recovery phenotypes at scale, for example, in thousands of people with minimal burden for participants and researchers. This study investigates the concurrent validity between remotely collected wearable sensor data and in-clinic assessments of motor recovery poststroke.
Utilizing a large, harmonized multisite dataset of adults at various stages of recovery poststroke, we analyzed cross-sectional (N=198; from 0 to >52 weeks) and longitudinal (N=98; from 0 to 26 weeks) changes in the use ratio, the Action Research Arm Test, and the Fugl-Meyer Assessment upper extremity subscale. The use ratio is the ratio of the time the paretic arm is active divided by the time the nonparetic arm is active.
Our findings indicate strong concurrent validity of the use ratio, the Action Research Arm Test, and the Fugl-Meyer Assessment upper extremity subscale both cross-sectionally (differences between people) and longitudinally (changes within a person), for example, =0.87 (95% CI, 0.80-0.91) at 0 to 6 weeks, declining to =0.58 (95% CI, 0.39-0.72) at ≥52 weeks for correlations between use ratio and Action Research Arm Test.
Although the use ratio strongly correlated with the Fugl-Meyer Assessment upper extremity subscale and Action Research Arm Test early after stroke, these correlations reduced with longer elapsed time poststroke. This decreasing correlation might be explained by the increasing influence that personal and environmental factors play as recovery progresses.
中风是导致长期残疾的主要原因，但康复方面的进展落后于急性治疗。大型生物学研究（如组学）可能为恢复提供机制性见解，但需要大规模收集详细的恢复表型，例如，在数千人中进行，对参与者和研究人员的负担最小。本研究调查了远程收集的可穿戴传感器数据与中风后运动恢复的临床评估之间的同时效度。
利用一个大型的、统一的多地点数据集，该数据集包含处于中风后不同恢复阶段的成年人，我们分析了使用比例、动作研究臂试验和Fugl-Meyer评估上肢子量表在横断面（N = 198；从0到>52周）和纵向（N = 98；从0到26周）的变化。使用比例是患侧手臂活动时间与健侧手臂活动时间的比值。
我们的研究结果表明，使用比例、动作研究臂试验和Fugl-Meyer评估上肢子量表在横断面（人与人之间的差异）和纵向（一个人内部的变化）都具有很强的同时效度，例如，在0至6周时，使用比例与动作研究臂试验之间的相关性为r = 0.87（95%CI，0.80 - 0.91），在≥52周时降至r = 0.58（95%CI，0.39 - 0.72）。
尽管在中风后早期，使用比例与Fugl-Meyer评估上肢子量表和动作研究臂试验密切相关，但随着中风后时间的延长，这些相关性降低。这种相关性的降低可能是由于随着恢复的进展，个人和环境因素的影响越来越大。
