使用甘油三糖指数预测冠心病的创新模型:基于机器学习的队列研究
Seyed Reza Mirjalili1, Sepideh Soltani1, Zahra Heidari Meybodi1
1Yazd Cardiovascular Research Center, Non-Communicable Diseases Research Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Cardiovascular diabetology
|August 4, 2023
概括
三甘油-葡萄糖指数 (TyG指数) 是冠心病 (CHD) 的更好的预测指标,而不是糖尿病. 将TyG指数纳入机器学习模型可以改善心脏病风险预测,并有助于预防策略.
科学领域:
- 心脏病学 心脏病学
- 代谢综合征是代谢综合征的一种.
- 医疗保健中的机器学习
背景情况:
- 现有的冠心病 (CHD) 预测模型缺乏最佳准确性.
- 这些模型往往忽略了胰岛素抵抗和甘油三 (TG) 水平,尽管它们已知对心血管疾病的影响.
- 甘油三糖指数 (TyG指数) 是一种已验证的胰岛素耐药性的指标.
研究的目的:
- 通过纳入TyG-index来增强CHD预测模型.
- 与糖尿病相比,评估TyG指数作为心脏病预测指标的有效性.
- 开发机器学习模型,以改善心血管疾病风险评估.
主要方法:
- 一组2000名伊朗成年人 (年龄在20-74岁之间) 被跟踪平均9.9年.
- 多变量Cox比例危险模型评估了TyG指数和CHD发病率之间的关联.
- 开发了机器学习模型,在已建立的心血管疾病风险得分中取代TyG指数的糖尿病.
主要成果:
- 在研究人群中,心脏病发病率为14.5%.
- 较高的TyG指数四分位数与心脏病风险增加显著相关 (最高四分位数的HR为2.32).
- 一个TyG指数>8.42显示高负预测值;基于TyG指数的SVM模型优于基于糖尿病的模型.
结论:
- 泰格指数是一个比糖尿病更强大的心血管疾病预测指标.
- 在机器学习模型中,TyG指数成为年龄之后最重要的预测指标.
- 建议对TyG指数进行临床实施,以识别和预防心脏病风险.
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