ArticleInternational journal of general medicine2026
Predictors of Atrial Fibrillation Late Recurrence and Major Adverse Cardiovascular Events After Radiofrequency Catheter Ablation: A Clinical Nomogram Model.
Article in International journal of general medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Predictors of atrial fibrillation recurrence after catheter ablation: a systematic review.The Egyptian heart journal : (EHJ) : official bulletin of the Egyptian Society of Cardiology · 2026Review
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7 authors.
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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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