Value of Epicardial Adipose Tissue Thickness in Predicting Major Adverse Cardiovascular Events in Patients with Coronary Artery Disease and Metabolic Syndrome

Background: Currently, coronary artery disease (CAD) combined with cardiometabolic disorders and diabetes mellitus is one of the most common phenotypes of residual risk in cardiology. Epicardial adipose tissue (EAT) thickness attracts attention in CAD risk stratification as a significant integral marker of lipid metabolism disorders and insulin resistance. The aim of the study was to evaluate EAT thickness as an additional non-invasive criterion for diagnosis and risk stratification in patients with CAD and metabolic syndrome (MetS) in the Uzbek population. Methods and Results: The study included 224 patients diagnosed with CAD, specifically those with functional class III angina pectoris and MetS. MetS criteria were defined in accordance with the IDF criteria (2005). Parameters assessed included biochemical markers of lipid and glucose metabolism, inflammatory markers, and imaging markers such as EAT thickness, carotid intima-media thickness, and carotid artery stenosis percentage. Major adverse cardiovascular events (MACE) during the 2-year follow-up included cardiovascular mortality, non-fatal myocardial infarction, non-fatal stroke, and recurrent hospitalizations due to destabilization requiring coronary angiography and revascularization. All patients were divided into 2 groups: Group 1 (n=137) included 137 patients without MACE, and Group 2 included 87 patients who experienced MACE during the 2-year follow-up. Group 2 showed significantly higher age (P<0.05), prevalence of T2DM (P<0.05), history of coronary revascularization (P<0.05), body mass index (BMI) (P<0.01), waist circumference (WC) (P<0.05), hsCRP (P<0.05), EAT thickness (P<0.01), and lower levels of HDL-C (P=0.000). Among imaging markers, EAT thickness was significantly higher in Group 2 (P<0.01), contrasting with the IMT and the percentage of carotid artery stenosis, which did not show significant differences. The results showed the substantial predictive value of EAT thickness and age, followed by Lp(a) and BMI, in assessing the 2-year risk of MACE in patients with CAD and MetS. Using all four significant variables—EAT thickness, age, Lp(a), and BMI—a multiple logistic regression model was constructed, in which the odds ratios for the selected variables were 1.246, 1.054, 1.016, and 1.087, respectively. Conclusion: EAT thickness measured by echocardiography is a valuable prognostic factor in the risk stratification of patients with CAD and MetS.