Sun Yazhao, Sun Pei, Liu Dongsheng
Department of Cardiology, Cangzhou People's Hospital, Cangzhou, Hebei Province, China.
PLoS One. 2025 Jul 23;20(7):e0328150. doi: 10.1371/journal.pone.0328150. eCollection 2025.
BACKGROUND: The triglyceride-glucose (TyG) index and the metabolic score for insulin resistance (METS-IR) are insulin resistance indicators based on different metabolic parameters. However, their cumulative effect on the outcomes of patients with acute myocardial infarction (AMI) remains unclear. This study aims to investigate whether the combined assessment of the TyG index and METS-IR can improve risk stratification and prognostic prediction in AMI patients. METHODS: This retrospective cohort study included AMI patients admitted to Cangzhou People's Hospital from January to December 2018. The baseline TyG index and METS-IR were calculated for each patient. The primary endpoint was major adverse cardiovascular and cerebrovascular events (MACCEs) during a 6-year follow-up, defined as a composite of all-cause mortality, coronary revascularization, and stroke. Logistic regression models and restricted cubic splines (RCS) were used to assess the association between TyG index, METS-IR, and the risk of MACCEs. Receiver operating characteristic (ROC) curves were applied to evaluate the discriminative ability of TyG index, METS-IR, and their combined predictive model (TyG index + BMI) for MACCEs. The area under the curve (AUC) was calculated to quantify predictive performance. Additionally, the net reclassification index (NRI) and integrated discrimination improvement (IDI) were computed to assess the incremental predictive value of TyG index + METS-IR beyond traditional risk factors. Subgroup analyses were conducted, and mediation analysis was performed to explore the potential mediating role of METS-IR in the relationship between TyG index and MACCEs. RESULTS: A total of 1,899 patients were included in the study. Multivariable logistic regression analysis showed that TyG index (OR = 1.655, 95% CI: 1.305-2.100, P < 0.001) and METS-IR (OR = 1.026, 95% CI: 1.001-1.052, P = 0.048) were both independent risk factors for MACCEs. Further analysis showed that patients with both high TyG index and high METS-IR had the highest risk of MACCEs (OR = 1.908, 95% CI: 1.188-3.114, P = 0.008). ROC curve analysis demonstrated that the combined prediction of MACCEs using TyG index and METS-IR achieved an AUC of 0.625, which was significantly superior to METS-IR alone (AUC = 0.573, P DeLong = 0.003). When compared with the traditional risk prediction model (AUC = 0.696), incorporating TyG index and METS-IR significantly improved predictive performance (optimized AUC = 0.717, P DeLong = 0.038). This also resulted in notable enhancements in NRI (0.353, P < 0.001) and IDI (0.156, P < 0.001). Subgroup analysis revealed no significant interaction effects of sex, age, hypertension, or diabetes status on the association between TyG index, METS-IR, and MACCEs (P-interaction > 0.05). Mediation analysis indicated that METS-IR partially mediated the relationship between TyG index and MACCEs. CONCLUSION: TyG index and METS-IR are predictors of adverse outcomes in AMI patients.
背景：甘油三酯-葡萄糖（TyG）指数和胰岛素抵抗代谢评分（METS-IR）是基于不同代谢参数的胰岛素抵抗指标。然而，它们对急性心肌梗死（AMI）患者预后的累积影响仍不清楚。本研究旨在探讨TyG指数和METS-IR的联合评估是否能改善AMI患者的风险分层和预后预测。 方法：这项回顾性队列研究纳入了2018年1月至12月在沧州市人民医院住院的AMI患者。计算每位患者的基线TyG指数和METS-IR。主要终点是6年随访期间的主要不良心血管和脑血管事件（MACCEs），定义为全因死亡、冠状动脉血运重建和中风的综合结果。采用逻辑回归模型和限制立方样条（RCS）评估TyG指数、METS-IR与MACCEs风险之间的关联。应用受试者工作特征（ROC）曲线评估TyG指数、METS-IR及其联合预测模型（TyG指数+BMI）对MACCEs的判别能力。计算曲线下面积（AUC）以量化预测性能。此外，计算净重新分类指数（NRI）和综合判别改善（IDI）以评估TyG指数+METS-IR相对于传统危险因素的增量预测价值。进行亚组分析，并进行中介分析以探讨METS-IR在TyG指数与MACCEs关系中的潜在中介作用。 结果：本研究共纳入1899例患者。多变量逻辑回归分析显示，TyG指数（OR = 1.655，95%CI：1.305-2.100，P < 0.001）和METS-IR（OR = 1.026，95%CI：1.001-1.052，P = 0.048）均为MACCEs的独立危险因素。进一步分析表明，TyG指数和METS-IR均高的患者发生MACCEs的风险最高（OR = 1.908，95%CI：1.188-3.114，P = 0.008）。ROC曲线分析表明，使用TyG指数和METS-IR联合预测MACCEs的AUC为0.625，显著优于单独使用METS-IR（AUC = 0.５73，P DeLong = 0.003）。与传统风险预测模型（AUC = 0.696）相比，纳入TyG指数和METS-IR显著提高了预测性能（优化后的AUC = 0.717，P DeLong = 0.038）。这也导致NRI（0.353，P < 0.001）和IDI（0.156，P < 0.001）显著提高。亚组分析显示，性别、年龄、高血压或糖尿病状态对TyG指数、METS-IR与MACCEs之间的关联无显著交互作用（P交互>0.05）。中介分析表明，METS-IR部分介导了TyG指数与MACCEs之间的关系。 结论：TyG指数和METS-IR是AMI患者不良预后的预测指标。
BMC Cardiovasc Disord. 2024-12-30
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