Background: Delayed pericardial effusion or pericardial tamponade (PE/PT) is a relatively rare complication of left atrial appendage closure (LAAC) but has serious consequences for affected patients. There are limited data related to delayed PE/PT. The aim of this study was to analyze the incidence and potential risks of delayed PE/PT following LAAC. Methods: Patients with nonvalvular atrial fibrillation who were successfully implanted with LAAC devices from October 2014 to July 2023 were screened retrospectively. Patients were divided into two groups according to whether delayed PE/PT occurred. Univariate and multivariate analyses were used to evaluate the potential risks of delayed PE/PT. Results: A total of 1866 patients with successfully implanted LAAC devices were included. Fifty-two patients were excluded because of missing transesophageal echocardiogram or cardiac CT angiogram data 45 days after the procedure, and 106 patients were excluded because of loss to follow-up. Thirty-seven patients were excluded because of acute PE/PT during perioperative period. Among the remaining 1671 patients, 11 developed delayed PE/PT during the follow-up period (2 Watchman2.5, 2 ACP and 7 LAmbre). Ten of these patients recovered after pericardiocentesis, and one patient required cardiac surgery. Patients with delayed PE/PT had a larger left atrial appendage (LAA) orifice diameter, a higher rate of nitinol plug device use and a lower incidence of systolic heart failure. Univariate and multivariate analyses revealed that the use of a nitinol plug device was associated with delayed PE/PT (OR=1.819 95% CI: 0.757-4.343, P=0.018). A larger maximal LAA orifice diameter was also associated with the occurrence of delayed PE/PT (OR=1.473 95% CI: 1.163-1.866, P=0.001). Conclusion: Delayed PE/PT is a rare complication of LAAC device implantation and is related to the use of a nitinol plug device rather than a nitinol cage device. Patients with larger LAA orifice diameters are at greater risk of delayed PE/PT after LAAC.

Several algorithms based on 12-lead ECG measurements have been proposed to identify right ventricular outflow tract (RVOT) and left ventricular outflow tract (LVOT) locations from which ventricular tachycardia (VT) and frequent premature ventricular complex (PVC) originated. However, a clinical-grade artificial intelligence algorithm is not available yet, which can automatically analyze characteristics of 12-lead ECGs and predict RVOT to LVOT origins of VT and PVC. We randomly sampled training, validation, and testing datasets from 420 patients who underwent successful catheter ablation (CA) to treat VT or PVCs, containing (340, 80%), (38, 9%), and (42, 10%) patients, respectively. We iteratively trained an AI algorithm that was supplied with 1,600,800 features extracted from 12-lead ECGs of the patients in the training cohort. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was calculated from the internal validation dataset to choose an optimal discretization cutoff threshold. After running on the testing dataset, the proposed approach attained the following performance metrics and 95% CIs (confidence intervals), accuracy (ACC) of 97.62 (87.44 -99.99), weighted F1-score of 98.46 (90-100), AUC of 98.99 (96.89-100), sensitivity (SE) of 96.97 (82.54-99.89), and specificity (SP) of 100 (62.97-100). The proposed multi-stage diagnostic scheme attained clinical-grade precision of prediction for LVOT and RVOT locations of VT origin with fewer applicability restrictions than prior studies.