Triglyceride-glucose index in the prediction of adverse cardiovascular events in patients with premature coronary artery disease: a retrospective cohort study

Abstract

Background: Premature coronary artery disease (PCAD) has become more common in recent years and is often associated with poor outcomes. Triglyceride-glucose (TyG) index is a simple and reliable surrogate for insulin resistance (IR) and is an independent predictor of cardiovascular prognosis. However, the prognostic value of the TyG index in patients with PCAD remains uncertain. Thus, this study aimed to investigate the prognostic value and predictive performance of the TyG index in patients with PCAD. Methods: A total of 526 young subjects (male < 45 years, female < 55 years) with angiographically proven CAD from January 2013 to December 2018 were included consecutively in this study. Their clinical and laboratory parameters were collected, and the TyG index was calculated as Ln [ fasting triglyceride (TG ) (mg / dL ) × fasting plasma glucose (FPG ) (mg / dL ) / 2 ]. The follow-up time after discharge was 40–112 months (median, 68 months; interquartile range, 49‒83 months). The primary endpoint was the occurrence of the major adverse cardiovascular events (MACE), defined as the composite of all-cause death, non-fatal myocardial infarction (MI), coronary artery revascularization, and non-fatal stroke. Results: The TyG index was significantly associated with traditional cardiovascular risk factors and the Gensini score (GS). Kaplan–Meier survival (MACE-free) curves by tertiles of the TyG index showed statistically significant differences (log-rank test, p = 0.001). In the fully adjusted Cox regression model, the Hazard ratio (95% CI) of MACE was 2.17 (1.15–4.06) in tertile 3 and 1.45 (1.11–1.91) for per SD increase in the TyG index. Time-dependent ROC analyses of the TyG for prediction of MACE showed the area under the curves (AUC) reached 0.631 at 3 years, 0.643 at 6 years, and 0.710 at 9 years. Furthermore, adding TyG index to existing risk prediction model could improve outcome prediction [C-statistic increased from 0.715 to 0.719, p = 0.007; continuous net reclassification improvement (NRI) = 0.101, p = 0.362; integrated discrimination improvement (IDI) = 0.011, p = 0.017]. Conclusion: The TyG index is an independent predictor of MACE in patients with PCAD, suggesting that the TyG index has important clinical implications for risk stratification and early intervention of PCAD.