在中年和老年人中开发和验证心脏代谢多病症预测模型
Hongjiang Li1, Xin Ma1, Tingting Cui1
1Department of General Practice, First Clinical Medical College, Shanxi Medical University, Taiyuan, Shanxi, China.
Scientific reports
|March 13, 2026
概括
一个新的后勤回归模型预测了中国成年人的五年心脏代谢多病症 (CMM) 风险. 这种工具有助于CMM的早期干预,减少医疗保健负担.
科学领域:
- 老年学是一门学科.
- 心脏病学 心脏病学
- 公共卫生 公共卫生
背景情况:
- 心脏代谢多病症 (CMM) 对老年人口的生活质量和医疗保健系统产生重大影响.
- 及时预测模型对于CMM的早期干预和管理至关重要.
- 在中国人口老龄化中,由于CMM,中国面临着巨大的健康和经济负担.
研究的目的:
- 开发和验证一种有效的预测模型,用于中国中年和老年人中CMM发病的五年风险.
- 整合来自中国健康与退休纵向研究 (CHARLS) 的多维数据,以提高预测.
- 为 CMM 风险人群提供早期干预策略.
主要方法:
- 分析了2015-2020年查尔斯调查的5388名参与者,最初没有CMM.
- 使用LASSO回归来从31个变量中选择预测因素,然后进行相关性分析以确定9个关键预测因素.
- 构建并比较极端梯度增强 (XGBoost) 和物流回归 (LR) 模型,使用ROC曲线,校准曲线和决策曲线分析验证性能.
主要成果:
- 确定了九个关键预测因素:缩血压,BMI,禁食血糖,总胆固醇,甘油三,尿酸,年龄,并发症和疼痛.
- 后勤回归模型在验证集上表现出优越和稳定的预测性能,AUC为0.732.
- 校准曲线证实了可靠的预测准确性,决策曲线分析表明了跨越各种风险值的临床效用.
结论:
- 开发并验证了一种可靠的,临床上适用的逻辑回归模型,使用名图来预测中国老年人5年CMM风险.
- 该模型有效地识别高风险个体,支持有针对性的早期干预和管理.
- 这种方法旨在减轻中国老龄化人口中与CMM相关的重大健康和经济负担.
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