A Novel Clinical Score Integrating Low-Voltage Zones and Biomarkers Predicts Atrial Fibrillation Recurrence...

Despite technological advances, predicting atrial fibrillation (AF) recurrence after catheter ablation remains a clinical challenge. We developed a novel multi-parametric model integrating electrophysiological substrate characteristics, structural remodeling, and inflammatory/metabolic biomarkers to improve risk stratification.

This retrospective study analyzed 279 consecutive patients undergoing first-time AF ablation (June 2022 to January 2024) with 12-month follow-up. Using a 7:3 training-validation split, we identified independent predictors through multivariate logistic regression.

Four key parameters emerged as powerful predictors: low-voltage zone extent (LVZ), high-sensitivity C-reactive protein (hs-CRP), red cell distribution width (RDW), and left atrial diameter (LAD). The composite model showed exceptional discrimination (AUC, in the training set and 0.84 in the validation set), significantly outperforming both individual parameters (LAD AUC 0.77, LVZ 0.75) and the APPLE score (AUC: 0.73, p < 0.001). The model stratified patients into five distinct risk categories (recurrence risk < 5% to > 70%) with strong clinical utility.

This is the first East Asian study to integrate voltage mapping with hematological-inflammatory biomarkers, providing a cost-effective and precise tool for post-ablation management. The model's performance and generalizability support its adoption in precision medicine pathways, particularly for guiding substrate modification in high-risk patients.