Abstract Background The triglyceride-glucose (TyG) index serves as a crucial indicator for evaluating insulin resistance (IR) and cardiovasc
Abstract Background The triglyceride-glucose (TyG) index serves as a crucial indicator for evaluating insulin resistance (IR) and cardiovascular risk among patients with type 2 diabetes mellitus (T2DM). Concurrently, hyperuricemia (HUA) strongly correlates with adverse cardiovascular outcomes. However, the prognostic value of the TyG index, particularly in patients exhibiting both conditions, remains inadequately defined. This study assessed the association between TyG index measurements and the incidence of major adverse cardiovascular events (MACEs) among patients simultaneously diagnosed with T2DM and HUA. Methods This retrospective, single-center cohort study included 628 patients diagnosed with both T2DM and HUA at the Chaohu Hospital (Anhui Medical University) between 2019 and 2024. Participants were stratified into tertiles based on their TyG index values. Kaplan–Meier survival curves with log-rank tests estimated the risk of MACEs, and Cox regression analyses calculated hazard ratios. The additional predictive contribution of the TyG index was evaluated using C statistics, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) metrics. Results During the 38.00 ± 8.78 months follow-up period, 74 MACEs were recorded. A significant proportional relationship emerged between the TyG index and cardiovascular events—patients in the highest tertile demonstrated markedly increased risk compared with those in the lowest tertile (HR = 2.45, 95% CI 1.23–4.95). A pivotal threshold was identified at TyG > 8.40, beyond which each standard deviation increase corresponded to a 66% higher probability of MACEs (HR = 1.66, 95% CI 1.36–2.36, P = 0.014). Integrating the TyG index into traditional risk models significantly improved predictive performance (C statistic increase: 0.64 → 0.67, P = 0.029; NRI = 0.14, IDI = 0.02, both P 8.40 threshold in T2DM patients with HUA and identify a synergistic interaction between serum uric acid (SUA) and TyG, providing a novel stratification tool for managing dual metabolic disorders. Graphical abstract
