Related Experiment Video
Updated: Jun 9, 2026
Estimating Bilateral Atrial Function by Cardiovascular Magnetic Resonance Feature Tracking in Patients with Paroxysmal Atrial Fibrillation
Published on: July 20, 2022
Epicardial fat area as an independent predictor of atrial fibrillation occurrence and severity
Xiting Liu1, Ani Gao1, Sixu Liu1
1Department of Cardiovascular Medicine, Affiliated Zhongshan Hospital of Dalian University, Dalian, Liaoning, China.
Objective:
This study aimed to investigate the relationship between the epicardial fat area (EFA), and both the occurrence and severity of atrial fibrillation (AF), and explore the potential factors associated with AF development.
Methods:
Three hundred hospitalized patients with AF (100 paroxysmal, 100 persistent, and 100 permanent) and 200 patients with sinus rhythm (SR), who were admitted during the same period, were retrospectively included. The EFA was quantified using chest computed tomography images analyzed with the sliceOmatic software. Then, the demographic, laboratory, echocardiographic, and EFA data were collected and compared between groups. Afterwards, logistic regression and receiver-operating characteristic (ROC) analyses were performed to identify the factors associated with AF.
Results:
The body mass index, neutrophil-to-lymphocyte ratio, red blood cell distribution width, blood urea nitrogen, serum creatinine, blood glucose, left ventricular end-diastolic diameter, and left atrial volume index (LAVI) were higher in AF patients, when compared with SR controls (all, p < 0.05). The EFA was significantly elevated in AF patients [13.42 [9.06-17.72] vs. 7.30 [5.29-9.32], p < 0.001], with a progressive increase from paroxysmal to persistent, to permanent AF. The multivariate analysis identified EFA (odds ratio: 1.307, 95% confidence interval: 1.214-1.407) and LAVI (odds ratio: 1.057, 95% confidence interval: 1.034-1.081) as independent factors associated with AF occurrence. In the AF subgroups, EFA and LAVI were also identified as independent factors associated with AF severity. Furthermore, age, body mass index, red blood cell distribution width, serum creatinine, and LAVI were identified as independent determinants of EFA. The ROC analyses revealed good predictive performance for AF, with EFA showing an area under the ROC curve of 0.836 (cut-off: 10.08 cm2, sensitivity: 69.30%, specificity: 83.00%) and LAVI showing an area under the ROC curve of 0.812 (cut-off: 30.82 mL/m2, sensitivity: 74.00%, specificity: 80.50%).
Conclusion:
EFA is closely associated with both the occurrence and severity of AF. Along with LAVI, EFA may serve as a valuable independent factor associated with the risk of AF.