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哪些替代胰岛素抵抗指数最能预测冠状动脉疾病? 一种机器学习方法

Seyed Reza Mirjalili¹, Sepideh Soltani¹, Zahra Heidari Meybodi²

¹Yazd Cardiovascular Research Center, Non-Communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.

Cardiovascular diabetology

|June 21, 2024

概括

泰格指数有效预测冠状动脉疾病 (CAD) 风险,优于其他胰岛素抵抗标志物. 它的简单性使它成为未来CAD预防策略的宝贵工具.

科学领域:

心脏病学心脏病学
内分泌学在内分泌学.
代谢综合征是代谢综合征的一种.

背景情况:

胰岛素抵抗与冠状动脉疾病 (CAD) 有关.
为了在没有血清胰岛素测量的情况下预测CAD,存在几种替代标记物.
在CAD预测中最有效的标志物方面尚未达成共识.

研究的目的:

评估和比较各种胰岛素抵抗替代标记在预测CAD中的有效性.
确定CAD风险评估中最可靠的标志物.

主要方法:

一组2000名个人 (年龄在20-74岁) 被跟踪了9.9年.
使用多变量Cox比例危险模型和ROC曲线来评估标志物 (TyG-index,TyG-BMI,TyG-WC,TG/HDL,METS-IR) 与CAD发生之间的关联.
采用Lasso,随机森林和Boruta算法来进行特征选择.

主要成果:

在完全调整的模型中,TyG指数是唯一与CAD显著相关的标志物 (HR:2.54).
泰格指数显示出最高的预测效率 (AUC:0.67),在女性中最为突出.
所有特征选择方法都认为TyG指数是预测CAD最可靠的标记.

结论:

TyG指数是一种简单而有效的替代标记,用于预测CAD.
使用常规测试进行评估的简单性支持其在CAD预防策略中的潜在纳入.

关键词:

心血管疾病的心血管疾病.机器学习机器学习代谢性疾病是一种代谢性疾病.公共卫生公共卫生

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