Retrospective study identifies f-wave amplitude and AF duration as predictors of post-ablation recurrence, highlighting clinical utility.
Background Predicting recurrence after radiofrequency catheter ablation (RFCA) in persistent atrial fibrillation (PeAF) remains challenging. This study evaluated the predictive value of F‐wave amplitude (FWA), F‐wave duration (FWD) in inferior ECG leads (II, III, aVF), and AF duration for post‐ablation recurrence. Methods In this dual‐center retrospective study, 763 persistent atrial fibrillation (PeAF) patients undergoing first RFCA (2017–2022) were analyzed. Pre‐procedural FWA and FWD were measured across 12‐lead ECGs using MATLAB. Clinical data and 12‐month follow‐up outcomes were collected. Independent predictors were identified via binary logistic regression, and a gradient boosting machine (GBM) model was developed. Model performance was assessed using ROC curves, calibration plots, and decision curve analysis (DCA), with internal (random split) and external (between‐center) validation. Results At 12 months, 198 patients (26%) experienced recurrence. Recurrence patients exhibited significantly lower inferior lead FWA (0.108 [0.076–0.157] vs. 0.126 [0.087–0.173] mV, p = 0.003), narrower FWD (54.96 [40.26–71.31] vs. 61.46 [42.7–76] ms, p = 0.038), and longer AF duration (13.8 [4–38] vs. 6.5 [3–21] months, p < 0.001). Multivariate analysis identified inferior lead FWA (OR = 0.788, 95%CI 0.662–0.937, p = 0.007) and AF duration (OR = 1.014, 95%CI 1.007–1.021, p < 0.001) as independent predictors. The model combining AF duration and FWA achieved an AUC of 0.692 (95%CI 0.648–0.737), improving to 0.746 (0.701–0.787) with FWD inclusion. Validation demonstrated stable discrimination (internal AUC = 0.722, 95%CI 0.680–0.762; external AUC = 0.703, 0.659–0.747). Conclusion Inferior lead FWA and AF duration are independent predictors of post‐RFCA recurrence in persistent AF. The combined model integrating these parameters with FWD shows robust discriminative ability and clinical utility, supporting personalized treatment strategies.
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Chen et al. (2025) studied this question.
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