Department of Occupational Therapy, School of Health and Human Services, College of Professional Studies, California State University, Dominguez Hills, CA, USA.
Neurorehabil Neural Repair. 2010 Jul-Aug;24(6):559-66. doi: 10.1177/1545968309358074. Epub 2010 May 3.
There are no reports of predictive models or predictors for quality of life (QoL) after constraint-induced therapy (CIT).
This investigation identified predictors of change in stroke-related QoL after distributed CIT using the Chi-squared Automatic Interaction Detector (CHAID) method.
A total of 58 patients with chronic stroke were treated with CIT for 2 hours daily for 3 weeks. The 7 potential predictors were age, gender, side of lesion, time since stroke, cognitive status, motor impairment of upper extremity, and activities of daily living (ADL). QoL was measured by the Stroke Impact Scale (SIS). CHAID analysis was used to examine for associations between the 7 predictors and each SIS domain. The validity of each model generated by the analysis was evaluated.
Daily functional performance as measured by the Functional Independence Measure (FIM) was found to determine SIS outcomes, including overall score (P = .006) and the ADL/instrumental ADL (IADL) domain (P = .004). None of the potential predictors emerged as significant predictors of the strength, memory, emotion, communication, mobility, hand function, and participation domains of SIS. The misclassification risk estimates were small, indicating good validity for the CHAID models.
The functional independence score of the FIM can predict the overall SIS score as well as the ADL/IADL domain of the SIS in chronic stroke patients who receive CIT, but larger databases are needed to confirm this. CHAID analysis was a useful approach for an exploratory study.
目前尚无关于强制性诱导治疗（CIT）后生活质量（QoL）的预测模型或预测因素的报告。
本研究采用卡方自动交互检测（CHAID）方法，确定了分布式 CIT 后与中风相关的 QoL 变化的预测因素。
共有 58 例慢性中风患者接受 CIT 治疗，每天 2 小时，持续 3 周。7 个潜在预测因素为年龄、性别、病变侧、中风后时间、认知状态、上肢运动障碍和日常生活活动（ADL）。QoL 通过中风影响量表（SIS）进行测量。CHAID 分析用于检查 7 个预测因素与每个 SIS 域之间的关联。分析生成的每个模型的有效性进行了评估。
功能性独立测量（FIM）每日功能表现被发现决定 SIS 结果，包括总体评分（P =.006）和 ADL/工具性 ADL（IADL）域（P =.004）。在 SIS 的强度、记忆、情绪、沟通、移动性、手部功能和参与域中，没有一个潜在的预测因素被认为是 SIS 的显著预测因素。错误分类风险估计较小，表明 CHAID 模型具有良好的有效性。
FIM 的功能独立性评分可以预测接受 CIT 的慢性中风患者的总体 SIS 评分以及 SIS 的 ADL/IADL 域，但需要更大的数据库来证实这一点。CHAID 分析是一种有用的探索性研究方法。
