Factors associated with clinical meaningful recovery after upper limb task-oriented training in people with stroke: a cohort study

Introduction:This study investigated upper extremity (UE) recovery predictors in post-stroke patients undergoing task-oriented training (TOT) rehabilitation. The data were collected at the Don Gnocchi Foundation hospitals in Italy between 2011 and 2015. Ethical approval was obtained, and all participants provided informed consent.Methods:Participants: 64 participants were recruited.Intervention: Participants received 25 sessions of TOT (45 minutes each, five days/week) as an adjunct to standard therapy. TOT focused on functional tasks with real-life objects and was progressively adapted to individual needs.Outcome Measures:Fugl-Meyer Assessment - Upper Extremity (FMA-UE): To assess impairment (ICF body function domain).15-item Action Research Arm Test (ARAT-15): To assess activity/performance (ICF activity domain).Quick version of the Disability of the Arm, Shoulder, and Hand questionnaire - 9 items (Q-DASH-9): To assess participation restrictions (ICF participation domain).Predictor Variables: Age, sex (i.e., male, female), dominance of the affected side (affected bodyside; i.e., dominant; non-dominant), chronicity (i.e., chronic; subacute), injury typology (i.e., ischemic; hemorrhagic), injury localization (i.e., cortical; sub-cortical), and baseline scores on the FMA-UE, ARAT-15, and Q-DASH-9.Data Analysis:Descriptive statistics were used to summarize data.Wilcoxon signed-rank test was used to compare pre- and post-intervention scores.Effect sizes were calculated using matched-pairs rank-biserial correlation.Participants were classified as "Responders" or "Non-responders" based on achieving minimally clinically important differences (MCID) in outcome measures.Stepwise binary logistic regression models were developed to identify predictors of responder status. A bidirectional approach was employed, starting with an empty model. Predictors were added (forward selection) or removed (backward elimination) one at a time based on whether their inclusion improved the Akaike information criterion (AIC).Model accuracy was assessed using McFadden’s pseudo-R2, Scaled Brier Score, Receiver Operating Characteristic curve (AUC), and Hosmer–Lemeshow test.Subgroup sensitivity analysis was performed to assess model robustness.引言：本研究探究了接受任务导向训练（TOT）康复治疗的脑卒中后患者的上肢（UE）功能恢复预测因素。数据收集于2011至2015年间，来自意大利多诺乔基基金会医院。本研究已获得伦理批准，所有受试者均签署了知情同意书。 方法 受试者：共招募64名受试者。 干预：受试者接受25次任务导向训练（TOT），每次时长45分钟，每周5次，作为标准治疗的辅助手段。TOT聚焦于使用真实物品的功能性任务，并会根据个体需求进行渐进式调整。 结局指标： Fugl-Meyer上肢功能评估量表（FMA-UE）：用于评估损伤情况（国际功能、残疾和健康分类（ICF）身体功能领域）。 15项动作研究上肢测试（ARAT-15）：用于评估活动/表现能力（ICF活动领域）。 手臂、肩与手残疾问卷9项简版（Q-DASH-9）：用于评估参与受限情况（ICF参与领域）。 预测变量：年龄、性别（男、女）、患侧优势性（患侧肢体，即优势侧、非优势侧）、病程（慢性、亚急性）、损伤类型（缺血性、出血性）、损伤定位（皮层、皮层下），以及FMA-UE、ARAT-15与Q-DASH-9的基线评分。 数据分析： 采用描述性统计对数据进行汇总。使用威尔科克森符号秩检验比较干预前后的评分。通过配对秩双列相关系数计算效应量。根据结局指标是否达到最小临床重要差异（MCID），将受试者分为“应答者”与“非应答者”。构建逐步二元逻辑回归模型以识别应答状态的预测因素，采用双向建模策略：从空模型出发，每次根据是否提升赤池信息准则（AIC）来逐一添加（向前选择）或移除（向后剔除）预测变量。模型准确性通过麦克法登伪R²、缩放布里尔分数、受试者工作特征曲线（AUC）以及霍斯默-莱梅肖检验进行评估。开展亚组敏感性分析以评估模型的稳健性。