中年和老年中国人口中甘油三糖指数与中风风险之间的关系:基于可解释的机器学习的全国纵向研究
Ying Gao1, Meihui Zhang2, Chen Xu1
1Public Health Research Center, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Diabetes research and clinical practice
|August 9, 2025
概括
甘油三糖 (TyG) 指数是胰岛素抵抗的标志物,与老年人中风风险增加有关. 监测TyG指数可以帮助预防中风的策略.
科学领域:
- 心脏病学 心脏病学
- 内分泌学 在内分泌学.
- 流行病学 流行病学
背景情况:
- 胰岛素抵抗是代谢障碍和心血管疾病的关键因素.
- 甘油三-葡萄糖 (TyG) 指数作为可靠的替代标记物用于胰岛素耐药性.
- 了解中风发病率的预测因素对于公共卫生干预至关重要.
研究的目的:
- 调查基线甘油三糖指数 (TyG) 与中年及老年人中发生性中风风险之间的关联.
- 用可解释的机器学习来识别和排名中风发病率的各种预测因素的重要性.
- 探索不同年龄和性别子组的TyG指数-中风风险关系的潜在变化.
主要方法:
- 利用了6863名中国健康与退休长度研究 (CHARLS) 参与者的数据,没有先前的中风病史.
- 使用拉索-考克斯回归来选择预测因子,以及多变量考克斯比例危险模型来进行关联分析.
- 应用可解释的生存机器学习来评估预测因素的意义,考虑时间动态和进行子组分析.
主要成果:
- 在9年的时间里,787名参与者 (11.5%) 经历了第一次中风.
- 在基线TyG指数和中风风险之间观察到一个反转的U形关系.
- 与最低四分位数相比,提升的TyG指数四分位数 (第二,第三和最高) 与明显更高的中风风险有关 (调整后的HRs范围从1.36到1.64不等).
- 这些关联在各个子组中持续存在,除了在60岁以下的人群中.
- 可解释的机器学习确定年龄是最重要的中风预测因素,TyG指数也很重要.
结论:
- 甘油三糖 (TyG) 指数是中年和老年人中中风风险的重要预测指标,特别是在60岁及以上的人中.
- 可解释的机器学习有效地识别了主要的中风风险因素,包括年龄和TyG指数.
- 监测TyG指数,作为胰岛素抵抗的标志物,可能是中风预防策略的宝贵组成部分.
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