Systemic inflammatory markers and epicardial fat volume as predictors of cardiometabolic risk in type 2 diabetes
Mehmet Coşgun, Zeliha Coşgun, Melike Elif Kalfaoğlu, Gülali Aktaş
Abstract
BACKGROUND: This study aims to examine the relationship between markers indicating systemic inflammatory response and epicardial fat volume (EFV) detected by computed tomography (CT) in type 2 diabetes mellitus (T2DM) patients. METHODS: A total of 165 patients (92 patients with diabetes and 73 control group) who underwent thoracic CT examination were included in the study. Hemogram parameters, lipid profiles, HbA1c, glucose, C-reactive protein, and uric acid levels were recorded. The systemic inflammatory response was calculated using the formula P × N/L. CT images were analysed by an experienced radiologist using 3D Slicer software. RESULTS: EFV and surface area were significantly higher in T2DM patients compared to the control group (P < .001). Additionally, the uric acid to HDL ratio (UHR) and systemic inflammatory index (SII) values of T2DM patients were significantly higher than those of control subjects (P = .04 for UHR and P = .035 for SII). Receiver operating characteristic analysis showed that EFV was >15.5 in T2DM patients with a sensitivity of 92% and a specificity of 37%. CONCLUSIONS: This study reveals that EFV is higher in T2DM patients and shows a positive correlation SII. Evaluating EFV, SII, and UHR together may be significant in assessing the inflammatory burden and cardiac risk of T2DM. The ease and cost-effectiveness of these markers increase their usability in clinical practice. Key messages What is already known on this topic: Epicardial fat volume (EFV) and systemic inflammatory index (SII) have been reported to be associated with type 2 diabetes mellitus (T2DM). What this study adds: Besides correlated with SII, EFV was further associated with T2DM and high sensitivity in detecting diabetic subjects. How this study might affect research, practice, or policy: The results of the present study may guide clinicians in personalizing preventive strategies, such as, identifying patients at higher cardiometabolic risk who could benefit from intensive lifestyle or pharmacological interventions.