Rattanawong, Pattara

Abstract Introduction Catheter ablation is a cornerstone treatment for atrial fibrillation (AF). However, AF recurrence after initial ablation remains a challenge, often requiring repeat ablation procedures. Purpose This meta-analysis evaluates the effectiveness of repeat catheter ablation for the management of recurrent atrial arrhythmia following an initial ablation, focusing on ablation techniques, anatomical targets, and pulmonary vein (PV) reconnection. Materials and Methods A systematic literature search of MEDLINE, Scopus, and the Cochrane Central Register of Controlled Trials (CENTRAL) was conducted on studies reporting outcomes of repeat and initial ablation procedures. Data on atrial arrhythmia recurrence, ablation technique, ablation target, and PV reconnection were extracted. A random-effects meta-analysis was performed using the ‘metaprop’ function to estimate the atrial arrhythmia recurrence rate after repeat ablation. Results A total of 53 studies (8,117 patients) were included. The pooled atrial arrhythmia recurrence rate after repeat ablation was 30% (95% CI: 27%–34%), with PV reconnection observed in 90% of cases following initial ablation. The lowest recurrence rate was observed with cryoballoon ablation (CBA) followed by radiofrequency ablation (RFA) at 23% (95% CI: 15%–33%, I² = 83%). Recurrence rates varied based on the ablation strategy, with RFA followed by CBA resulting in a 29% recurrence rate (95% CI: 19%–42%, I² = 83.7%), CBA used in both initial and repeat procedures at 30% (95% CI: 23%–37%, I² = 44.1%), and RFA performed for both ablations at 32% (95% CI: 26%–37%, I² = 80.2%). Patients who underwent repeat ablation with pulmonary vein isolation (PVI) alone had a recurrence rate of 25% (95% CI: 18%–35%, I² = 88.5%). In contrast, those who received PVI with additional ablation lines, excluding complex fractionated atrial electrograms (CFAE), had a higher recurrence rate of 31% (95% CI: 27%–34%, I² = 84.3%). The recurrence rate increased further to 38% (95% CI: 32%–46%, I² = 87.3%) when PVI was combined with CFAE and additional lines. PV reconnection rates varied by vein, with the left inferior pulmonary vein (LIPV) exhibiting the lowest rate at 23% (95% CI: 22%–24%, I² = 20.3%). The left superior pulmonary vein (LSPV) and right inferior pulmonary vein (RIPV) showed similar reconnection rates (26%), while the right superior pulmonary vein (RSPV) had a rate of 25% (I² = 0.0%). Conclusion Repeat ablation for atrial fibrillation carries a risk of atrial arrhythmia recurrence, largely driven by PV reconnection. Strategies involving CBA followed by RFA and PVI-based ablations demonstrated favourable outcomes. Lower reconnection rates in left-sided PVs, particularly the LIPV, highlight the need for optimised ablation techniques.

Brugada Syndrome (BrS) is a rare but clinically significant inherited arrhythmia disorder characterized by a type 1 ECG pattern and an increased risk of sudden cardiac death (SCD). Since its first description in 1992, BrS has been the subject of intensive investigation, yet risk stratification remains one of its greatest challenges. While survivors of cardiac arrest and patients with documented ventricular fibrillation (VF) are clear candidates for implantable cardioverter-defibrillators (ICDs), predicting risk in asymptomatic or intermediate-risk individuals is less straightforward. Over the past two decades, multiple risk scores have been developed—including the Sieira, Shanghai, BRUGADA-RISK, and PAT—each integrating combinations of clinical, ECG, electrophysiological study (EPS), and genetic data. Performance metrics vary, with C-statistics ranging from 0.70 to 0.82 in derivation cohorts, but external validation has often been limited. Importantly, current ESC and AHA/ACC guidelines only endorse syncope and EPS inducibility as validated predictors, reflecting the cautious stance of expert panels in the face of heterogeneous data. Nonetheless, the emergence of structured risk models has improved our ability to stratify intermediate-risk patients and stimulated further innovation. Looking ahead, opportunities lie in integrating artificial intelligence applied to raw ECG waveforms, wearable technology for dynamic monitoring, advanced cardiac imaging biomarkers, and polygenic risk scores. Multinational collaboration and federated learning will be essential to overcome statistical fragility and ensure global applicability. Ultimately, BrS risk scores should be considered decision-support tools that enrich but do not replace clinical judgment. Shared decision-making remains central, particularly in asymptomatic patients where ICD implantation is not a clear-cut choice.