Shen, Win-Kuang

BACKGROUND: Catheter ablation for atrial fibrillation is a widely used rhythm-control strategy, yet its role in reducing thromboembolic risk and enabling oral anticoagulation (OAC) discontinuation remains uncertain. This meta-analysis aims to comprehensively synthesize and evaluate randomized controlled trial evidence supporting long-term antithrombotic strategies in patients with atrial fibrillation undergoing catheter ablation. METHODS: A systematic literature search was performed in MEDLINE/PubMed, Embase, and the Cochrane Central Register of Controlled Trials to identify randomized controlled trials evaluating antithrombotic strategies after catheter ablation for atrial fibrillation. The primary outcome was ischemic stroke. A frequentist network meta-analysis comparing reported treatment arms, along with a pooled incidence meta-analysis for outcomes of interest, was conducted. RESULTS: Four randomized controlled trials, including 3924 patients, met the inclusion criteria. Three trials compared long-term OAC continuation versus OAC discontinuation, and 1 compared OAC continuation with left atrial appendage occlusion after catheter ablation. No significant differences in stroke incidence were observed when comparing OAC or left atrial appendage occlusion with no antithrombotic therapy (incidence rate ratio, 0.90 [95% CI, 0.02–33.85]; P =0.95; incidence rate ratio, 0.79 [95% CI, 0.00–241.01]; P =0.94, respectively). Among patients who discontinued antithrombotic therapy without undergoing left atrial appendage occlusion (n=1161), with 2864 cumulative person-years of follow-up, the pooled incidence of stroke was 0.23 events per 100 person-years (95% CI, 0.02–2.43; I 2 =0%). CONCLUSIONS: This analysis reinforces that, across randomized data, the incidence of thromboembolic events in patients who discontinued OAC after successful ablation remained low. However, the evaluation of net clinical benefit is limited by the low number of events across all treatment arms, underscoring the need for larger studies with prolonged follow-up to further validate the safety of this strategy, particularly in higher-risk populations.

Abstract Aims Syncope remains a diagnostic challenge despite advancements in testing and treatment. Cardiac syncope is an independent predictor of mortality and can be difficult to distinguish from other causes of transient loss of consciousness (TLOC). This paper explores whether artificial intelligence (AI) can improve the evaluation and management of patients with syncope. Methods and results We conducted a literature review and incorporated the opinions of experts in the fields of syncope and AI. The cause of TLOC is often unclear, hospitalization criteria are ambiguous, diagnostic tests are frequently non-informative, and assessments are costly. Patients are left with unanswered questions and limited guidance. Artificial intelligence (AI) has the potential to optimize syncope evaluation by processing large data sets, detecting imperceptible patterns, and assisting clinicians. However, AI has limitations, including errors, lack of human empathy, and uncertain clinical utility. Liability issues further complicate its integration. We present three viewpoints: (i) AI is crucial for advancing syncope management; (ii) AI can enhance the patient experience; and (iii) AI in syncope care is inevitable. Conclusion Artificial intelligence may improve syncope diagnosis and management, particularly through machine learning–based test interpretation and wearable device data. However, it has yet to surpass human clinical judgment in complex decision-making. Current challenges include gaps in understanding syncope mechanisms, AI interpretability, generalizability, and clinical integration. Standardized diagnostic approaches, real-world validation, and curated data sets are essential for progress. Artificial intelligence may enhance efficiency and communication but raises concerns regarding confidentiality, bias, inequities, and legal implications.