挖掘基于NHANES数据库的中风风险因素和饮食保护因素:使用SHAP分析
Bo Wu1, Wanli Yu1, Gang Zhang1
1Department of Neurosurgery, Chongqing General Hospital, School of Medicine, Chongqing University, Chongqing 400014, China.
Journal of affective disorders
|June 14, 2025
概括
一个新的评分表有效地预测中风和中风后抑郁风险,使用年龄,收入和胆固醇等关键因素. 该工具有助于制定中风的初级预防策略.
科学领域:
- 医学研究 医学研究
- 公共卫生 公共卫生
- 生物统计学 生物统计学
背景情况:
- 脑卒中是一个显著且日益增长的全球健康挑战,患病率和死亡率高.
- 识别可修改的风险因素对于制定有效的初级预防策略至关重要.
- 脑卒中后抑郁症是一种常见的并发症,需要注意和管理.
研究的目的:
- 确定与中风和中风后抑郁症相关的关键风险因素.
- 开发一个准确的预测模型和一套针对中风风险的实际评分系统.
- 为中风和中风后抑郁症提供新的初级预防策略.
主要方法:
- 分析了49491名参与国家健康和营养检查调查 (NHANES) (1999-2016) 的数据.
- 在3972个人的培训队伍中开发了一个预测模型和分数表,使用后勤回归和SHAP值.
- 使用决策曲线分析 (DCA),接收器操作特征 (ROC) 曲线和校准曲线验证模型性能.
主要成果:
- 开发了一个具有82%的曲线下面积 (AUC) 的预测模型.
- 创建了一个得分尺度,AUC为79%,证明了良好的预测能力.
- 确定的重大风险因素包括年龄,收入水平,胆固醇,白蛋白,淋巴细胞百分比,性酸酶,葡萄糖,甘油三和中性粒细胞百分比.
结论:
- 已经开发出一种简单且临床上有用的评分表来预测中风和中风后抑郁症.
- 评分尺度提供了卓越的可用性和操作便利性.
- 该工具作为一种新的自我查方法,用于识别患中风和中风后抑郁症风险较高的人.
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