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ORIGINAL RESEARCH article

Front. Nutr.

Sec. Nutrition and Metabolism

The association between insulin resistance indices and the occurrence of major adverse cardiovascular events in patients with premature myocardial infarction: a prospective cohort study

Provisionally accepted
Yu  ZhouYu Zhou1Yuhang  WangYuhang Wang2Jingxi  ChenJingxi Chen1Lai  JiangLai Jiang1Ran  ChuRan Chu2Weiwei  TianWeiwei Tian2Jiaxin  WangJiaxin Wang2Jing  GaoJing Gao2,3,4*Yin  LiuYin Liu5*
  • 1Chest Hospital, Tianjin University, Tianjin, China
  • 2Clinical school of Thoracic, Tianjin Medical University, Tianjin, China
  • 3Cardiovascular Institute, Tianjin Chest Hospital, Tianjin, China
  • 4Tianjin Key Laboratory of Cardiovascular Emergency and Critical Care, Tianjin, China
  • 5Department of Cardiology, Tianjin Chest Hospital, Tianjin, China

The final, formatted version of the article will be published soon.

Background: Insulin resistance (IR) alternative markers, including the triglyceride-glucose index (TyG), TyG combined with body mass index (TyG-BMI), and the triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-C), have been shown to be significantly associated with prognosis of acute myocardial infarction (AMI). However, the prognostic value of these markers in patients with premature myocardial infarction (PMI) remains unclear. This study aims to investigate the association between IR markers and major adverse cardiovascular events (MACEs) in PMI patients. Methods: This was a prospective cohort study that consecutively enrolled 1,688 PMI patients (male ≤50 years, female ≤55 years) from Tianjin Chest Hospital between February 2015 and December 2024. TyG, TyG-BMI and TG/HDL-C indices were calculated. The median follow-up time was 17.4 months (IQR: 11.4-31.9), with the endpoint being MACEs. IR indices were grouped by quartiles. The risk association between IR indices and MACEs was analyzed using Cox proportional hazards models and restricted cubic spline analysis. The predictive performance of IR indices was assessed using Harrell's C-index, net reclassification improvement (NRI), integrated discrimination improvement (IDI). Results: Among 1,688 patients, 211 (12.5%) occurred MACEs. Restricted cubic spline analysis showed a positive nonlinear relationship between TyG-BMI and MACEs risk, while TyG and TG/HDL-C were linearly associated with MACEs risk. In the fully adjusted Cox proportional hazards model, the hazard ratios of occurring MACEs in the fourth quartile versus the first quartile were 2.88 (95% confidence interval (CI): 1.83-4.53) for TyG-BMI, 1.77 (95% CI: 1.11-2.82) for TyG, 1.44 (95% CI: 0.93-2.22) for TG/HDL-C. In the fourth quartile versus the first quartile of TyG-BMI, the hazard ratios of occurring MACEs were 3.85 (95%CI:1.79-8.27) in patients with diabetes and 3.38 (95%CI:1.78-6.43) in patients with high high-sensitivity C-reactive protein (hsCRP). Additionally, TyG-BMI demonstrated higher C-index, NRI and IDI for predicting MACEs risk in PMI patients. Conclusion: In patients with PMI, TyG-BMI is an independent predictor of MACEs demonstrating significantly superior predictive performance compared to TyG and TG/HDL-C. The association between elevated TyG-BMI and MACEs risk was significant in patients with diabetes and high hsCRP levels. The effect was particularly stronger in patients with diabetes.

Keywords: diabetes, Insulin Resistance, Major adverse cardiovascular events, Premature myocardial infarction, Triglyceride glucose-body mass index

Received: 13 Oct 2025; Accepted: 03 Feb 2026.

Copyright: © 2026 Zhou, Wang, Chen, Jiang, Chu, Tian, Wang, Gao and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

* Correspondence:
Jing Gao
Yin Liu

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