Key result
Novel nomogram predicts AF recurrence after catheter ablation with ~0.75 C-statistic discrimination.
Why the study?
The study aimed to develop and validate a risk nomogram model to predict the risk of atrial fibrillation recurrence after radiofrequency catheter ablation.
Does a risk nomogram model incorporating LAD, LVEF, AF type, and systemic inflammation score accurately predict atrial fibrillation recurrence after radiofrequency catheter ablation?
Cohort (n=485)
No
Does a risk nomogram model incorporating LAD, LVEF, AF type, and systemic inflammation score accurately predict atrial fibrillation recurrence after radiofrequency catheter ablation?
A novel visual nomogram integrating systemic inflammation score with clinical and echocardiographic parameters provides robust individual risk prediction for atrial fibrillation recurrence after ablation.
Answers are grounded in this paper and cite their sources.
Nomogram may aid post-ablation AF risk counseling; leaves open prospective validation before clinical adoption.
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. 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.
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Zhao et al. (2022) conducted a cohort in Non-valvular atrial fibrillation undergoing first-time radiofrequency catheter ablation (n=485). Risk nomogram model (incorporating LAD, LVEF, AF type, and systemic inflammation score) was evaluated on Predictive performance (C-statistic) for atrial fibrillation recurrence in the training cohort (C-statistic 0.741, 95% CI 0.689-0.794). The developed nomogram model demonstrated good discrimination for predicting atrial fibrillation recurrence after radiofrequency catheter ablation, achieving a C-statistic of 0.741 in the training cohort and 0.750 in the validation cohort.
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