A predictive model using gender, the diagnosis-to-ablation time and left atrial function in predicting the recurrence of atrial fibrillation within 1 year after radiofrequency catheter ablation

Objective: Radiofrequency catheter ablation (RFCA) serves as a first‑line treatment for symptomatic atrial fibrillation (AF); however, its clinical application is still challenged by a relatively high postoperative recurrence rate. Therefore, numerous studies have focused on identifying factors associated with AF recurrence after RFCA, such as atrial size, gender, diagnosis‑to‑ablation time (DAT), and echocardiographic indices reflecting left atrial function. This study aims to investigate the risk factors for AF recurrence within one year after RFCA and to develop a simple yet effective prediction model based on these factors to guide clinical practice. Methods: This was a single-center retrospective study. We enrolled patients with atrial fibrillation (n=202) who underwent their first catheter radiofrequency ablation in the Third Department of Cardiology at the Second Hospital of Hebei Medical University between January 2019 and January 2022. Clinical characteristics, diagnosis-to-ablation time (DAT), and left atrial functional parameters were compared. A prediction model was constructed using Logistic regression, and its diagnostic performance was evaluated using the receiver operating characteristic (ROC) curve. Finally, a predictive model for atrial fibrillation recurrence was established. Results: (1)A total of 202 symptomatic atrial fibrillation patients who underwent radiofrequency ablation were enrolled, and follow-up data at 1, 3, 6, and 12 months post-procedure were collected. Based on recurrence status, the patients were divided into a sinus rhythm maintenance group (n=136) and a recurrence group (n=66), with an overall postoperative recurrence rate of 32.7%. (2)Univariate analysis showed statistically significant differences between the two groups in terms of gender, diagnosis-to-ablation time (DAT), N-terminal pro-B-type natriuretic peptide (NT‑proBNP), Homocysteine (Hcy), and Left atrial appendage emptying velocity (LAAeV)(P<0.05). (3)Multivariate Logistic regression analysis further indicated that gender, DAT, and LAAeV were independent risk factors for postoperative AF recurrence. The regression equation derived was: Logit(P)=−0.824 + 1.19×gender + 0.015×DAT − 0.016×LAAeV. Goodness-of-fit testing yielded χ²=5.975, and the Hosmer‑Lemeshow test showed P=0.650 (>0.05), indicating a well-fitted model. (4)Receiver operating characteristic (ROC) curve analysis revealed that DAT had the largest area under the curve (AUC=0.665) among the three indicators, while the combined prediction model demonstrated better discriminative ability than DAT alone (AUC=0.722). Conclusions: Gender, DAT, and LAAeV are independent risk factors for early postoperative recurrence in patients with atrial fibrillation. The combined model of these three factors demonstrates good predictive value for early AF recurrence after the procedure. Furthermore, the constructed nomogram can serve as a non‑invasive preoperative assessment tool prior to RFCA, offering enhanced predictive utility.