Development of a prognostic model for predicting recurrence of atrial fibrillation after catheter ablation

This study aimed to identify predictors of AF recurrence following catheter ablation and develop a predictive model for assessing the likelihood of recurrence. The study included 303 patients with AF who underwent first-time catheter ablation from January 2020 to September 2021 in the cardiology department of the First Affiliated Hospital of Guangxi Medical University. Clinical data, treatment details, and ultrasound examination results were collected. Statistical analyses were performed to identify prognostic factors, including LASSO and multivariable logistic regression. A predictive model was developed and evaluated using calibration curves. Among the patients, 21.8% experienced AF recurrence. By LASSO regression and multivariable logistic regression, five prognostic factors were identified for the nomogram model: degree of tricuspid regurgitation, CHA2DS2-VASc score, left ventricular ejection fraction, type of AF (persistent vs. paroxysmal), and left atrial anteroposterior diameter. The AUC for AF recurrence was 0.862 (95% CI 0.809–0.916) and the C-index of the model was 0.86. Bootstrap sampling validation was performed, resulting in a corrected C-index of 0.841. Leave-one-out cross-validation yielded a C-index of 0.822 and a calibration slope of 0.89, indicating good discrimination in internal validation. This study identified predictors of AF recurrence after catheter ablation and developed a predictive model for assessing recurrence likelihood. After adequate external validation, the model may support clinical risk assessment after ablation.