Front Endocrinol (Lausanne). 2026 Jan 14;16:1730404. doi: 10.3389/fendo.2025.1730404. eCollection 2025.
ABSTRACT
BACKGROUND: The triglyceride-glucose (TyG) index is a simple and reliable marker of insulin resistance and is associated with cardiovascular risk. Epicardial adipose tissue (EAT) volume reflects local visceral fat burden and also correlates with cardiovascular events. While both markers have been studied individually, their combined predictive value for major adverse cardiovascular events (MACE) after coronary artery bypass grafting (CABG) remains unclear. This study evaluated whether TyG index and EAT volume, alone or in combination, can improve risk prediction of MACE following CABG and assessed their potential interaction.
METHODS: We retrospectively analyzed 304 patients who underwent CABG between 2018 and 2022. TyG index and EAT volume were measured preoperatively. Patients were stratified based on optimal cut-off values derived from ROC analysis. Cox regression models were used to estimate associations with MACE. Interaction was assessed using relative excess risk due to interaction (RERI), attributable proportion (AP), and synergy index (SI). Model performance was evaluated using C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Model fit was assessed with the Akaike information criterion (AIC), Bayesian information criterion (BIC).
RESULTS: During follow-up of 44 months, 82 patients experienced MACE. Both TyG index and EAT volume were independently associated with increased risk. Patients with elevations in both markers had a significantly higher risk (adjusted HR = 7.62, 95% CI: 3.27-17.76). A significant additive interaction was observed (RERI = 3.81; AP = 0.50; SI = 2.34). Adding both variables improved model discrimination and fit.
CONCLUSION: TyG index and EAT volume are independent predictors of MACE after CABG. Their combined assessment provides additional information for risk stratification, but the findings are preliminary and require validation in larger, prospective, multi-center studies.
PMID:41613954 | PMC:PMC12846971 | DOI:10.3389/fendo.2025.1730404