# Development and validation of a risk nomogram for predicting recurrence in patients with non-valvular atrial fibrillation after radiofrequency catheter ablation

## TL;DR

This study created a risk prediction model to estimate the chance of atrial fibrillation recurrence after ablation, using factors like heart volume and health scores.

## Contribution

A novel nomogram was developed and validated for predicting recurrence after radiofrequency catheter ablation in non-valvular atrial fibrillation patients.

## Key findings

- The nomogram included left atrial volume index, right atrial volume index, systemic immune-inflammatory index, NYHA classification, and CHA₂DS₂-VASc score.
- The model showed strong discrimination with a C-index of 0.837 in training and 0.895 in validation cohorts.
- Calibration and decision curve analysis confirmed the model's accuracy and clinical utility.

## Abstract

Limited evidence exists regarding predictors of recurrence in patients with non-valvular atrial fibrillation (NVAF) following radiofrequency catheter ablation (RFCA). This study aimed to develop and validate a risk model for post-ablation recurrence in these patients.

242 patients were enrolled and randomly divided into a modeling group (n = 169) and a validation group (n = 73) according to 7:3. The echocardiographic parameters, laboratory values and clinical features were used to derive a predictive model. Univariate and multivariate logistic regression analyses were used to identify independent risk factors.

During the 1-year follow-up, 87(36.00%) patients experienced AF recurrence. The nomogram was established by five variables including left atrial volume index (OR1.055, 95% CI: 1.021–1.090, P = 0.001), right atrial volume index (OR1.040, 95% CI: 1.008–1.073, P = 0.014), systemic immune-inflammatory index(OR1.015, 95% CI: 1.001–1.030, P = 0.036), New York Heart Association classification (OR 2.861, 95% CI: 1.282–6.383, P = 0.010), and CHA₂DS₂-VASc score(OR1.417, 95% CI: 1.077–1.864, P = 0.013). The model was developed, an online Dynamic Nomogram (https://cardiologyresearch.shinyapps.io/DynNomapp) application via the platform, and subsequently validated. The calculator achieved a C-index of 0.837(95% Cl: 0.774–0.899) in the training cohort and 0.895 (95% Cl: 0.823–0.968) in the validation cohort. The calibration curve showed good consistency between the predictions and observations in the training and validation cohorts. Decision curve analysis and clinical impact curves indicated the clinical utility of the nomogram.

We developed a nomogram based on LAVI, RAVI, SII, NYHA classification, CHA₂DS₂-VASc score to estimate the risk of AF recurrence after RFCA. The newly developed nomogram demonstrated good discrimination and accuracy, suggesting its potential utility in predicting AF recurrence. Given its performance, the model is a promising tool; however, it is still in its preliminary stages and requires further validation with larger, multi-center, prospective studies involving diverse populations to confirm its generalizability.

The online version contains supplementary material available at 10.1186/s12911-025-03338-4.