开发和验证用于预测缺血性中风康复患者失眠风险的决策树模型
Xuefeng Sun1, Zilin Wang1, Yuqing Song1
1Changchun University of Chinese Medicine, Changchun, China.
BMC public health
|August 20, 2025
概括
一个新的决策树模型准确地预测了缺血性中风康复患者的失眠. 焦虑和社会支持是关键预测因素,
科学领域:
- 神经科学
- 睡眠医学
- 临床预测模型
背景情况:
- 失眠是缺血性中风康复过程中的常见并发症.
- 没有预测ISC患者失眠风险的模型.
- 了解临床,心理和社会因素对于有效管理至关重要.
研究的目的:
- 开发和验证用于预测ISC患者失眠风险的决策树模型.
- 在ISC群体中确定失眠的关键预测因素.
- 改善中风后睡眠障碍的治疗.
主要方法:
- 一项涉及中国823名成年ISC患者的横截面研究.
- 按照TRIPOD+AI指南使用分类和回归树算法.
- 使用PSQI,FSS,SSRS和其他工具收集的数据;经过10倍交叉验证和外部队列验证.
主要成果:
- 在ISC患者中,失眠的患病率为37. 72%.
- 确定了主要预测因素:焦虑 (SAS),社会支持 (SSRS),疲劳 (FSS),抑郁 (SDS),BMI和中风严重程度 (NIHSS).
- 决策树模型实现了高准确度 (90.4%的内部验证,82%的外部验证),AUC为0.96.
结论:
- 开发的决策树模型对预测ISC患者的失眠有显著的前景.
- 焦虑和社会支持是中风后失眠的最重要因素.
- 该模型有助于制定针对性治疗ISC患者失眠的策略.
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