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描述性特征作为中风后患者进行强制性运动疗法后预后的潜在预测指标。

Descriptive characteristics as potential predictors of outcomes following constraint-induced movement therapy for people after stroke.

作者信息

Fritz Stacy L, Light Kathye E, Clifford Shannon N, Patterson Tara S, Behrman Andrea L, Davis Sandra B

机构信息

Department of Exercise Science, University of South Carolina, 1300 Wheat St, Blatt PE Bldg, Columbia, SC 29208, USA.

出版信息

Phys Ther. 2006 Jun;86(6):825-32.

Abstract

BACKGROUND AND PURPOSE

Limited evidence exists regarding the characteristics of people who benefit most from constraint-induced movement therapy (CIMT). This study's purpose was to investigate 6 potential descriptors in predicting CIMT outcomes.

SUBJECTS

The participants were a convenience sample (N=55) of people who were more than 6 months poststroke.

METHODS

The Wolf Motor Function Test (WMFT) and the Motor Activity Log amount scale (MALa) were used to assess outcomes for CIMT. The potential predictors (side of stroke, time since stroke, hand dominance, age, sex, and ambulatory status) were entered into a linear regression model using stepwise entry, with simultaneous entry of the dependent variables' pretest scores as the covariate.

RESULTS

Age was the only significant predictor of the 6 potential predictors in the model and was predictive only of MALa scores. None of the independent variables showed a predictive relationship with the WMFT.

DISCUSSION AND CONCLUSION

Although age was the only significant predictor, an equally strong finding in this study was that side of stroke, chronicity, hand dominance, sex, and ambulatory status were not found to be predictors at the follow-up session. This finding emphasizes the importance of not excluding people from CIMT based on these predictors.

摘要

背景与目的

关于从强制性运动疗法(CIMT)中获益最多的人群特征,现有证据有限。本研究的目的是调查6个潜在指标对CIMT疗效的预测作用。

研究对象

参与者为卒中后6个月以上的便利样本(N = 55)。

方法

采用Wolf运动功能测试(WMFT)和运动活动日志量表(MALa)评估CIMT的疗效。将潜在预测因素(卒中侧、卒中后时间、利手、年龄、性别和步行状态)纳入线性回归模型,采用逐步纳入法,并将因变量的预测试分数作为协变量同时纳入。

结果

年龄是模型中6个潜在预测因素中唯一具有显著预测作用的因素,且仅对MALa分数具有预测性。没有自变量与WMFT显示出预测关系。

讨论与结论

虽然年龄是唯一具有显著预测作用的因素,但本研究同样重要的一个发现是,在随访时未发现卒中侧、病程、利手、性别和步行状态是预测因素。这一发现强调了不要基于这些预测因素将患者排除在CIMT之外的重要性。

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