What question did this study set out to answer?

The aim is to identify predictors of atrial fibrillation recurrence and major cardiovascular events post-ablation.

January 10, 2026International Journal of General Medicine0 citationsOpen Access

Predictors of Atrial Fibrillation Late Recurrence and Major Adverse Cardiovascular Events After Radiofrequency Catheter Ablation: A Clinical Nomogram Model

YZYanxiang ZhouWuhan University YHYugang HuWuhan University SCSheng CaoWuhan University

Key Result

The nomogram model using early recurrence, LAVImax, and E/Vp effectively predicts atrial fibrillation late recurrence and major adverse cardiovascular events post-RFCA.

Key Points

The aim is to identify predictors of atrial fibrillation recurrence and major cardiovascular events post-ablation.
Developed a clinical nomogram model
Analyzed patient data from ablation procedures
Evaluated predictors for late recurrence and cardiovascular outcomes
Identified key predictors for recurrence and adverse events
Demonstrated the nomogram's ability to stratify risk effectively
Showed improved patient management based on predicted outcomes

Structured PICO

Population

128 patients with atrial fibrillation (AF) who underwent radiofrequency catheter ablation (RFCA), mean age 59.63 ± 9.90 years, 80 males (62.5%). Excluded: previous ablation, left ventricular wall-motion abnormalities, valvular heart disease, congenital heart disease, cardiomyopathy, and presence of left atrial thrombus.

Intervention

Radiofrequency catheter ablation (RFCA) and construction of a clinical nomogram prediction model based on early recurrence, LAVImax, and E/Vp

Outcome

Atrial fibrillation late recurrence (AFLR) defined as an episode lasting more than 30s including AF, atrial flutter and atrial tachycardia >90 days after RFCAhard clinical

Main Result

Absolute Event Rate: 0% vs 0%

Abstract

Purpose: This study sought to investigate the predictive factors for atrial fibrillation late recurrence (AFLR) and major adverse cardiovascular events (MACEs) in atrial fibrillation (AF) patients after radiofrequency catheter ablation (RFCA) and construct a nomogram prediction model for providing precious information of screening the high risk patients and giving appropriate preventive interventions. Patients and Methods: A total of 128 patients with atrial fibrillation (AF) who underwent RFCA were enrolled. Univariate and multivariate Cox regression were used to screen the predictors of AFLR and MACEs (including rehospitalization due to AF recurrence, heart failure, myocardial infarction, coronary revascularization, stroke and all-cause mortality). The nomogram model was constructed to predict AFLR after RFCA. Risk stratification based on the nomogram further predicted AFLR and MACEs after RFCA. Subgroup analysis and survival analysis of high and low risk groups in individuals with AF after RFCA were performed. Results: During median follow-up of 76.50 (5.75) months, 71 (55.47%) patients experienced AFLR, while 56 (43.75%) suffered from MACEs. Early recurrence, maximum left atrial volume index (LAVImax) and E/Vp were the independent risk factors for predicting AFLR after RFCA. And AFLR was the only independent predictor for MACEs. Accordingly, a nomogram prediction model based on early recurrence, LAVImax and E/Vp was constructed, the 1-year, 3-year and 5-year AUC of AFLR were 0.904, 0.826 and 0.793, respectively. Risk stratification based on the nomogram had high predictive value for AFLR and MACEs. The Kaplan–Meier survival curves showed great discrimination between the low and high risk groups in the probability of free from AFLR and MACEs. Conclusion: The nomogram model based on early recurrence, LAVImax and E/Vp can be used to predict the AFLR and MACEs after RFCA accurately and individually, in order to provide scientific and effective patient management basis for AF patients after RFCA.

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