Incremental Effect of TyG, an Indicator of Insulin Resistance, on Residual Risk after Myocardial Infarction
Year: 2025
Type: article
Study design: Observational Study
Abstract: 目的：本研究的目的是为了研究TyG与心肌梗死患者残余风险之间的关系。方法：选取712名急性心肌梗的患者进行5年随访，采集患者基本信息、体格检查等资料，检测实验室相关指标。绘制ROC曲线评估TyG对残余风险的预测能力，使用R语言计算分析净重分类指数(NRI)和综合判别改善指数(IDI)，以进一步评估TyG在心肌梗死后残余风险传统危险因素之上的额外预测价值。结果：ROC曲线显示，TyG指数曲线下面积0.554 (95%CI: 0.503~0.604, P = 0.042)，在基线风险模型中纳入TyG的综合判别改善指数[IDI]：0.0082，P = 0.022；纳入TyG的净重新分类指数[NRI]：0.2169，P = 0.017。在基线风险模型中纳入TyG对基线模型对MACE的预测能力有增量效应。结论：TyG对心血管残余风险具有一定的预测能力，在控制传统危险因素的同时，TyG可以指导急性心梗患者的进一步强化治疗。Objective: The purpose of this study was to investigate the relationship between TyG and residual risk in patients with myocardial infarction. Methods: 712 patients with acute myocardial infarction were selected for 5-year follow-up, and basic information, physical examination and other data were collected, and laboratory related indexes were tested. ROC curves were plotted to assess the predictive ability of TyG on residual risk. The net reclassification index (NRI) and integrated discriminant improvement index (IDI) were calculated and analyzed using the R language to further assess the additional predictive value of TyG over and above the traditional risk factors for residual risk after myocardial infarction. Results: ROC curves showed an area under the curve of the TyG index of 0.554 (95% CI: 0.503 to 0.604, P = 0.042), a composite discriminant improvement index [IDI] incorporating TyG in the baseline risk model: 0.0082, P = 0.022, and a net reclassification index [NRI] incorporating TyG: 0.2169, P = 0.017. In the baseline risk model, the inclusion of TyG had an incremental effect on the predictive power of the baseline model for MACE. Conclusion: TyG has a predictive ability for residual cardiovascular risk, and while controlling traditional risk factors, TyG may guide further intensive treatment for patients with acute myocardial infarction.
Source: Advances in Clinical Medicine
Author: 园园 汪
Language: English
Subfield: Endocrinology, Diabetes and Metabolism
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4409408729