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

Authors

Luca Segreti, Lorenzo Pistelli, Federico Fiorentini, Massimo Magnano, Valentina Barletta, Andrea Di Cori, Mario Giannotti Santoro, Antonio Canu, Matteo Parollo, Gino Grifoni, Stefano Marco Viani, Raffaele De Lucia, Maria Grazia Bongiorni, Francesco Rametta, Giulio Zucchelli

Published in

International journal of cardiology. Pages 134732. Aug 22, 2026. Epub Aug 22, 2026.

Abstract

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.
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.
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).
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.

PMID:
42632552
Bibliographic data and abstract were imported from PubMed on 23 Aug 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.