Department of Cardiology, Maqsood Medical Complex General Hospital, Peshawar, Pakistan.
Department of Electrophysiology, DHQ Teaching Hospital, Kohat, Pakistan.
Angiology. 2023 Jul;74(6):563-568. doi: 10.1177/00033197221124776. Epub 2022 Aug 30.
Epicardial fat may play an important role in the pathogenesis of coronary artery disease (CAD). We investigated the relationship between coronary artery ectasia (CAE) and epicardial fat volume (EFV). This retrospective study included 506 patients with CAE (group 1), 500 with CAD (group 2), and 500 patients with normal coronaries as controls (group 3). The pericardium was traced manually from the edge of the pulmonary trunk to the last measured by computed tomography slice containing images of the heart to obtain a region of interest. EFV was significantly higher in patients with CAD than in those with CAE (87.94 ± 22.18 vs 61.33 ± 12.75 mL; < .001). Patients with normal coronaries had EFV of 56.62 ± 9.82 mL. Multivariate logistic regression analysis showed that male gender [Odds ratio (OR) (95% confidence interval (CI)): 1.220 (1.015-1.682), = .042], diabetes [OR (95% CI): 1.036 (1.008-1.057); = .002], and smoking [OR (95% CI): 3.043 (1.022-9.462); = .005] were significantly associated with CAE. The receiver operating characteristic (ROC) curve showed that EFV had strongest diagnostic value for detecting CAD rather than CAE [AUC .502 = .074 (95% CI: .311-.784)]. This study demonstrated that EFV is an independent predictor for CAE and CAD. However, sensitivity and specificity for detecting CAE is low when compared with CAD.
心外膜脂肪可能在冠状动脉疾病 (CAD) 的发病机制中发挥重要作用。我们研究了冠状动脉扩张 (CAE) 与心外膜脂肪量 (EFV) 之间的关系。这项回顾性研究纳入了 506 例 CAE 患者（第 1 组）、500 例 CAD 患者（第 2 组）和 500 例冠状动脉正常的患者作为对照组（第 3 组）。通过计算机断层扫描从肺动脉边缘追踪到最后一张包含心脏图像的切片来手动追踪心包，以获得感兴趣区域。CAD 患者的 EFV 明显高于 CAE 患者（87.94 ± 22.18 比 61.33 ± 12.75 mL； <.001）。冠状动脉正常的患者 EFV 为 56.62 ± 9.82 mL。多变量 logistic 回归分析显示，男性[比值比（OR）（95%置信区间（CI））：1.220（1.015-1.682）， =.042]、糖尿病[OR（95% CI）：1.036（1.008-1.057）； =.002]和吸烟[OR（95% CI）：3.043（1.022-9.462）； =.005]与 CAE 显著相关。受试者工作特征（ROC）曲线显示，EFV 对检测 CAD 的诊断价值强于 CAE [AUC.502 =.074（95% CI：.311-.784)]。本研究表明，EFV 是 CAE 和 CAD 的独立预测因子。然而，与 CAD 相比，EFV 检测 CAE 的敏感性和特异性较低。
