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双重任务作为中风后跌倒的预测因素:一个横截面分析,比较走路时说话与停止走路时说话
Disha Lamba1, Abraham M Joshua1, Vijaya Kumar K1
1Department of Physiotherapy, Kasturba Medical College Mangalore, Manipal Academy of Higher Education, Karnataka, Manipal, 576 104, India.
F1000Research
|August 4, 2025
概括
走路而说话 (WWT) 测试显示,与停止走路而说话 (SWWT) 相比,中风幸存者的跌倒风险预测优越. 这些双重任务评估增强了临床评估,以获得更好的中风康复结果.
科学领域:
- 神经学 神经学
- 康复医学 康复医学 康复医学
- 老年学是一门学科.
背景情况:
- 双任务评估,如走路时说话 (WWT) 和停止走路时说话 (SWWT),用于预测中风幸存者的跌倒风险.
- 对WWT和SWWT与已建立的措施,如伯格平衡尺度 (BBS) 和布效率尺度 (FES) 的比较有效性尚未确定.
研究的目的:
- 评估WWT和SWWT测试对中风幸存者的跌倒风险的比较预测价值.
- 为了比较双任务测试的性能与已建立的平衡和恐惧下降的天平.
主要方法:
- 一项涉及68名中风幸存者的横截面研究,他们接受了WWT-简单 (WWT-S),WWT-复杂 (WWT-C),SWWT,BBS和FES评估.
- 斯皮尔曼相关性分析了平衡,跌倒恐惧和双重任务性能之间的关系.
- 后勤回归和接收器操作特征 (ROC) 分析确定了预测因素,并评估了预测准确性.
主要成果:
- WWT-S和WWT-C与BBS有很强的负相关性,与FES有积极相关性,表明平衡较差,随着双重任务的完成速度较慢,下降的恐惧更高.
- 与SWWT相比,WWT测试显示出更高的灵敏度 (97.8%) 和特异性 (99%),分别为68.9%和91.3%).
- SWWT (积极) 被确定为一个显著的跌倒风险预测指标 (AUC = 0.911).
结论:
- 与SWWT相比,WWT测试在中风幸存者中降落风险的预测价值更高.
- 将双重任务措施纳入临床实践可以改善跌倒风险评估,并指导针对性中风康复.
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