糖尿病病残留胆固醇2型糖尿病的风险分层:基于机器学习的预防工具
Yuehong Dai1, Qi Pan2, Yujie Yu3
1Department of Clinical Laboratory, Affiliated Jinhua Hospital, Zhejiang University School of Medicine, Jinhua, Zhejiang, China.
Frontiers in nutrition
|November 27, 2025
概括
剩余胆固醇 (RC) 与2型糖尿病 (T2D) 患者糖尿病病 (DKD) 风险增加有关. 使用RC的新模型显示了个性化DKD风险预测的前景.
科学领域:
- 内分泌学 在内分泌学.
- 腎臟病學 (nephrology) 是一種醫學專業.
- 心血管医学 心血管医学
背景情况:
- 脂质代谢障碍是糖尿病病 (DKD) 发展的关键.
- 剩余胆固醇 (RC) 是心血管风险因素,但其与发生的DKD的联系尚不清楚.
- 这项研究调查了RC与DKD在2型糖尿病 (T2D) 中的关联.
研究的目的:
- 检查残留胆固醇 (RC) 与患糖尿病病 (DKD) 的风险之间的关系.
- 创建DKD风险的预测模型,将RC和其他临床因素纳入2型糖尿病 (T2D) 患者的临床风险.
主要方法:
- 一项对2,122名没有基线DKD的T2D患者进行的回顾性队列研究.
- 多变量考克斯回归和受限立方线 (RCS) 分析,以评估RC和DKD风险.
- 随机生存森林 (RSF) 算法用于预测器识别和预测模型开发.
主要成果:
- 较高的RC水平与增加的DKD风险有关,并观察到非线性关联.
- 该RSF模型确定了14个预测因素,包括RC和白蛋白与肌素比率 (ACR),具有良好的多线性.
- 预测模型表现出强烈的歧视 (3年AUC=0.86,5年AUC=0.91) 和校准.
结论:
- 剩余胆固醇 (RC) 独立且非线性地与T2D患者的DKD风险有关.
- 开发的RSF模型显示了DKD的有效预测性能.
- 该模型可能有助于在T2D中对DKD进行个性化风险评估和管理.
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