Development and Validation of a Risk Nomogram Model for Predicting Recurrence in Patients with Atrial Fibrillation After Radiofrequency Catheter Ablation
Zhihao Zhao, Fengyun Zhang, Ruicong Ma, Lin Bo, Zeqing Zhang, Chaoqun Zhang, Zhirong Wang, Chengzong Li, Yang Yu
Abstract
Purpose: This study aimed to develop and validate a risk nomogram model for predicting the risk of atrial fibrillation recurrence after radiofrequency catheter ablation. Patients and Methods: A retrospective observational study was conducted using data from 485 patients with atrial fibrillation who underwent the first radiofrequency ablation in our hospital from January 2018 to June 2021. All patients were randomized into training cohort (70%; n=340) and validation cohort (30%; n=145). Univariate and multivariate logistic regression analyses were used to identify independent risk factors. The predictive nomogram model was established by using R software. The nomogram was developed and evaluated based on differentiation, calibration, and clinical efficacy by concordance statistic (C-statistic), calibration plots, and decision curve analysis (DCA), respectively. Results: =0.005), type of atrial fibrillation (OR 2.164, 95% CI: 1.262-3.714), and systemic inflammation score (OR 1.905, 95% CI 1.408-2.577). The C-statistic of the nomogram was 0.741 (95% CI: 0.689-0.794) in the training cohort and 0.750 (95% CI: 0.670-0.831) in the validation cohort. The calibration plots showed good agreement between the predictions and observations in the training and validation cohorts. Decision curve analysis and clinical impact curves indicated the clinical utility of the predictive nomogram. Conclusion: The nomogram model has good discrimination and accuracy, which can screen high-risk groups intuitively and individually, and has a certain predictive value for atrial fibrillation recurrence in patients after radiofrequency ablation.