The triglyceride-glucose index, a marker of insulin resistance, as a predictor of thrombotic risk in atrial fibrillation - José Miguel Rivera-Caravaca; Eva Soler-Espejo; María Pilar Ramos-Bratos; Raquel López-Gálvez; Eduardo González-Lozano; Gregory Y. H. Lip; Francisco Marín; Vanessa Roldán (Cardiovascular Diabetology)
Abstract Background Atrial fibrillation (AF) increases the risk of stroke making accurate risk stratification central for effective management. The triglyceride-glucose (TyG) index, a marker of insulin resistance, has been associated to cardiovascular diseases. Indeed, it is particularly relevant in the context of diabetes and metabolic syndrome, which are major contributors to cardiovascular risk. Herein, we explored whether the TyG index could predict thrombotic events in AF patients. Methods Prospective cohort study involving AF outpatients starting oral anticoagulation (OAC) therapy between January 2016 and November 2021. The primary endpoint was a composite of thrombotic events including myocardial infarction, venous thromboembolism, ischemic stroke, or transient ischemic attack, over 2 years follow-up. The TyG index was calculated at baseline and patients were stratified into tertiles (T1: TyG index < 4.59; T2: TyG index 4.59–4.83; T3: TyG index > 4.83). Results 2907 patients (52.5% women; median age 77 years, IQR 69–82 years) were included, with a median TyG index of 4.71 (4.53–4.91). At 2-years, 7.2% (208) of patients experienced a composite thrombotic event. Patients in T3 had a significantly higher incidence rate ratio (1.39 [95% CI 1.01–1.96], p = 0.047 vs. T1; 1.42 [95% CI 1.01–2.00], p = 0.038 vs. T2). Adjusted Cox regression identified the TyG index as an independent predictor for thrombotic events (aHR 1.82; 95% CI 1.15–2.89). T3 patients exhibited a 64% higher risk of thrombotic events (aHR 1.64, 95% CI 1.17–2.29; log-rank test p value = 0.014). Conclusions In this real-world cohort of AF patients on OAC, an elevated TyG index independently predicted thrombotic events. However, further research is needed to determine how to integrate this simple marker into existing risk stratification strategies and whether it truly improves risk assessment and treatment decisions.