# Additive predictive value of triglyceride-glucose index and epicardial adipose tissue volume for major adverse cardiovascular events following coronary artery bypass grafting

**Authors:** Juan Wang, Run Zhang, Zhihui Yan, Shimiao Ruan, Jia Liu, Zhengliang Li, Fangfang Shang, Wenzhong Zhang

PMC · DOI: 10.3389/fendo.2025.1730404 · Frontiers in Endocrinology · 2026-01-14

## TL;DR

This study shows that combining two markers—triglyceride-glucose index and epicardial fat volume—can better predict heart complications after heart surgery.

## Contribution

The novel contribution is demonstrating the additive predictive value of TyG index and EAT volume for post-CABG cardiovascular events.

## Key findings

- Both TyG index and EAT volume independently predict major adverse cardiovascular events after CABG.
- Combined use of TyG and EAT volume significantly improves risk prediction and model performance.
- An additive interaction between TyG and EAT volume increases MACE risk substantially.

## Abstract

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.

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).

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.

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.

## Full-text entities

- **Diseases:** insulin resistance (MESH:D007333)
- **Chemicals:** triglyceride (MESH:D014280), glucose (MESH:D005947)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

41 references — full list in the complete paper: https://tomesphere.com/paper/PMC12846971/full.md

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Source: https://tomesphere.com/paper/PMC12846971