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已发表论文
射频导管消融术后心房颤动晚期复发及主要不良心血管事件的预测因素：一种临床列线图模型
Authors Zhou YX, Hu YG, Cao S, Lei JR, Xu FF, Tan TT, Zhou Q
Received 28 July 2025
Accepted for publication 8 October 2025
Published 8 January 2026 Volume 2026:19 553219
DOI https://doi.org/10.2147/IJGM.S553219
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Redoy Ranjan
Yan-Xiang Zhou, Yu-Gang Hu, Sheng Cao, Jia-Rui Lei, Fen-Fen Xu, Tuan-Tuan Tan, Qing Zhou
Department of Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, Hubei, People’s Republic of China
Correspondence: Qing Zhou, Department of Ultrasonography, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, Hubei, 430060, People’s Republic of China, Tel + 86 027 88041911 x88037, Fax +86 027 88040334, Email qingzhou.wh.edu@hotmail.com
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.
Keywords: atrial fibrillation, radiofrequency catheter ablation, late recurrence, major adverse cardiovascular events
Department of Ultrasonography, Renmin Hospital of Wuhan University, Wuhan, Hubei, People’s Republic of China
Correspondence: Qing Zhou, Department of Ultrasonography, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, Hubei, 430060, People’s Republic of China, Tel + 86 027 88041911 x88037, Fax +86 027 88040334, Email qingzhou.wh.edu@hotmail.com
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.
Keywords: atrial fibrillation, radiofrequency catheter ablation, late recurrence, major adverse cardiovascular events