Cardiologists Develop Five-Factor Nomogram to Predict Post-Ablation Atrial Fibrillation Recurrence

A clinical research team has developed and internally validated a prognostic nomogram designed to predict the likelihood of atrial fibrillation recurrence in patients following catheter ablation. The observational investigation, conducted using clinical records from patients undergoing first-time catheter ablation, aimed to identify robust prognostic factors that could help clinicians assess post-procedure arrhythmia risk. According to the study findings, approximately 21.8 percent of the evaluated patient cohort experienced a recurrence of atrial fibrillation following their initial ablation procedure.

The study cohort comprised 303 patients diagnosed with atrial fibrillation who underwent first-time catheter ablation between January 2020 and September 2021 in the cardiology department of the First Affiliated Hospital of Guangxi Medical University. To establish the predictive framework, researchers systematically collected comprehensive patient information, including baseline clinical data, specific procedural treatment details, and preoperative ultrasound examination results. These documented clinical and imaging parameters provided the foundational dataset for testing associations between baseline patient characteristics and subsequent post-procedural arrhythmia recurrence.

To isolate the most informative predictors from the clinical and imaging records, investigators conducted statistical analyses utilizing least absolute shrinkage and selection operator regression alongside multivariable logistic regression. Through this analytical pipeline, the authors identified five independent prognostic factors for inclusion in the final predictive nomogram: the degree of tricuspid regurgitation, the patient’s baseline CHA2DS2-VASc score, left ventricular ejection fraction, the clinical type of atrial fibrillation categorized as persistent versus paroxysmal, and the left atrial anteroposterior diameter measured during ultrasound evaluation.

The resulting five-factor prognostic model demonstrated strong discriminative performance during internal validation procedures. In the primary statistical assessment, the model achieved an area under the receiver operating characteristic curve of 0.862, with a 95 percent confidence interval ranging from 0.809 to 0.916, alongside an overall concordance index of 0.86. The authors further evaluated the nomogram’s reliability using calibration curves to examine the agreement between predicted recurrence probabilities and actual observed outcomes.

To evaluate potential model optimism and internal stability, the investigators performed bootstrap sampling validation and leave-one-out cross-validation. Bootstrap resampling yielded a corrected concordance index of 0.841, while leave-one-out cross-validation produced a concordance index of 0.822 alongside a calibration slope of 0.89. The authors concluded that the five-variable predictive nomogram demonstrated good discrimination in internal validation, noting that following adequate external validation in broader populations, the model may support post-ablation clinical risk assessment.

Subject of Research: Prognostic model for predicting atrial fibrillation recurrence following catheter ablation

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

Article References: Li, L., Yang, D., Chen, Q., Huang, Y., & Gui, C. (2026). Development of a prognostic model for predicting recurrence of atrial fibrillation after catheter ablation. BMC Cardiovascular Disorders. https://doi.org/10.1186/s12872-026-06937-9

Image Credits: AI Generated

DOI: 10.1186/s12872-026-06937-9

Keywords: atrial fibrillation, catheter ablation, prognostic model, nomogram, arrhythmia recurrence, cardiology, CHA2DS2-VASc score, tricuspid regurgitation, left ventricular ejection fraction, left atrial diameter, multivariable logistic regression, LASSO regression, clinical risk assessment, bootstrap validation, cross-validation, internal validation