Table 1_A computed tomography-based radiomics-clinical model incorporating left atrial and proximal pulmonary vein features predicts recurrence after radiofrequency catheter ablation of atrial fibrillation: a multicenter study.docx

A combined model was then developed by integrating the radiomics score with independent clinical predictors. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), and model comparisons were performed using the DeLong test.</p>Results<p>Of the 379 included patients, 106 (28.0%) developed late AF recurrence within 2 years after ablation. Multivariable logistic regression identified sex and left ventricular ejection fraction as independent clinical predictors.

The combined model achieved AUCs of 0.896, 0.894, and 0.869 in the training, internal validation, and external validation cohorts, respectively, consistently outperforming the radiomics model (0.874, 0.840, and 0.787, respectively) and the clinical model (0.694, 0.658, and 0.704, respectively). These findings indicate good predictive performance, with maintained performance in the external validation cohort.</p>Conclusion<p>The CCTA-based radiomics-clinical model derived from the LAC showed good performance for predicting late recurrence after RFCA for AF and may serve as a practical tool for individualized preprocedural risk stratification.</p>