A simple clinical model to predict atrial fibrillation recurrence after catheter ablation—derivation and external validation

BACKGROUND: Reliable predictors of recurrence after Catheter ablation (CA) for atrial fibrillation (AF) remain limited. We aimed to develop and validate a clinically applicable score to predict AF recurrence and procedural complexity following CA. METHODS: We conducted a prospective, single-centre observational study enrolling 402 consecutive patients undergoing CA for AF. Clinical, echocardiographic, and procedural data were collected. The primary endpoint was AF recurrence at 12 months. Predictors were identified by Cox regression. A composite score (LUCA) was developed (0-3 points). Prognostic performance was assessed using Cox regression and Kaplan-Meier analysis. An independent retrospective cohort (277 patients) served as validation cohort for external validation. RESULTS: Three predictors (LAVi, timing of ablation, AF at presentation) were independently associated with recurrence. The LUCA score stratified recurrence risk: one-year AF-free survival was 94.9% (score 0), 81.9% (1), 73.4% (2), and 30.0% (3) (log-rank p < 0.001). Each point increase corresponded to a 2.52-fold higher recurrence risk (HR 2.52, 95% CI 1.88-3.39, p < 0.001; C-index 0.69). Findings were consistent in external validation cohort (model C-index 0.776), where LUCA performed better compared to both APPLE (AUC 0.87 vs 0.77; ΔAUC 0.103, 95% CI 0.037-0.168, Z = 3.08, p = 0.002) and CHA2DS2-VASc (AUC 0.87 vs 0.56; ΔAUC 0.312, 95% CI 0.224-0.401, Z = 6.9, p < 0.001). Higher LUCA scores correlated with longer procedural time (ρ = 0.3, p < 0.001). CONCLUSIONS: The LUCA score predicts AF recurrence and procedural complexity after CA. It provides a practical and personalized tool to improve patient selection, guide procedural strategy, and optimize follow-up.