Abstract
BACKGROUND: The triglyceride glucose index (TyG index) is a marker of insulin resistance linked to the incidence of major adverse cardiovascular events (MACE) in diverse populations. However, its long-term prognostic role in type 2 diabetes (T2D) remains underexplored. This study evaluated the predictive value of the TyG index for all-cause mortality and MACE in T2D over a period of more than 15 years. METHODS: A retrospective analysis was conducted on a cohort of 568 patients with T2D (median age: 67 years, IQR 61-72 years; 54% males; median disease duration: 14 years, IQR 7-21 years; median HbA1c: 7.3%, IQR 6.6-8.0%) and 376 presumably healthy controls (CTR, median age: 65 years, IQR 60-71 years) followed for a median period of 16.8 (IQR, 13.1-16.8) years. Routine biomarkers were measured on serum samples using commercially available methods. One-way ANOVA/ANCOVA, logistic regression, and Spearman's correlations were used to compare the TyG index among groups and to assess its correlations with biochemical variables. The association between TyG index and the follow-up endpoints was investigated by Kaplan-Meier curves and Cox proportional hazards analysis. RESULTS: Patients with T2D exhibited higher TyG Index values compared to CTR, with significant correlations between the TyG Index and markers of obesity, glucose metabolism, inflammation, and liver function. Patients with preexisting diabetic kidney disease (DKD) or atherosclerotic vascular disease had higher baseline values of TyG index. Sex-specific differences were observed among CTR but not in T2D patients. The TyG Index was predictive of all-cause mortality (HR = 1.39, 95% CI 1.07-1.79) and associated with the onset of complications MACE, DKD, and neuropathy independent of other conventional predictors. Age modified the TyG Index-mortality association, with the strongest effect in individuals aged 57-74. CONCLUSION: The TyG index is a valuable prognostic marker for long-term risk of all-cause mortality and MACE in patients with T2D, supporting its use in clinical risk stratification.