Open AccessInfluencing Factors of Recurrence of Nonvalvular Atrial Fibrillation after Radiofrequency Catheter Ablation and Construction of Clinical Nomogram Prediction Model
Author(s) -
Zhongbao Ruan,
Hong-xia Liang,
Fei Wang,
Gecai Chen,
Junguo Zhu,
Yin Ren,
Li Zhu
Publication year - 2022
Publication title -
international journal of clinical practice
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.756
H-Index - 98
eISSN - 1742-1241
pISSN - 1368-5031
DOI - 10.1155/2022/8521735
Subject(s) - nomogram , medicine , atrial fibrillation , cardiology , proportional hazards model , catheter ablation , receiver operating characteristic , multivariate analysis , multivariate statistics , statistics , mathematics
Purpose. This study sought to investigate the predictive factors for atrial fibrillation (AF) recurrence in patients after radiofrequency ablation (RFCA) and construct a nomogram prediction model for providing precious information of ablative strategies. Methods. A total of 221 patients with AF who underwent RFCA were enrolled. Univariate and multivariate Cox regression were used to screen the predictors of recurrence. The receiver operating characteristic (ROC) curve and the Kaplan–Meier (K–M) curve were drawn to analyze the value of predictors. The nomogram model was further constructed to predict the recurrence of AF in patients after RFCA. Results. There were 59 cases of AF recurrence after RFCA. Monocyte count/high-density lipoprotein cholesterol (MHR), AF course (COURSE), coronary heart disease (CHD), and AF type (TYPE) were the independent risk factors for predicting AF recurrence after RFCA. Accordingly, a nomogram prediction model based on MHR, COURSE, CHD, and TYPE was constructed with a C-index of 0.818 (95% CI: 0.681∼0.954), while the C-index of verification was 0.802 (95% CI: 0.658∼0.946). Conclusions. Preoperative MHR, COURSE, CHD, and TYPE were independent risk factors for predicting recurrence of AF after RFCA. The nomogram model based on MHR, COURSE, CHD, and TYPE can be used to predict the recurrence of AF after RFCA accurately and individually.