Abstract
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.
Highlights
Atrial fibrillation (AF) is the most common persistent arrhythmia in clinics
The techniques and technologies of Radiofrequency catheter ablation (RFCA) have improving and have been associated with a higher clinical success rate, previous clinical studies have shown that the recurrence of AF after single RFCA varied from 11% to 29% and 7% to 24% after repeated RFCA in paroxysmal AF during 5 years follow-up, while up to 70% in persistent AF [2–4]. erefore, it is very important to identify the predictors of AF recurrence after RFCA, which will help to improve the successful rate of RFCA and guide clinical practice
All patients were included with the criteria as follows: AF was confirmed by history, ECG or Holter, and the treatment with at least one antiarrhythmic drug was ineffective and willing to undergo RFCA. e type of AF was classified according to the ESC Guidelines on AF 2020 [7]
Summary
Atrial fibrillation (AF) is the most common persistent arrhythmia in clinics. Radiofrequency catheter ablation (RFCA) has gradually become the most effective method to restore sinus rhythm and improve quality of life in patients with AF [1]. The techniques and technologies of RFCA have improving and have been associated with a higher clinical success rate, previous clinical studies have shown that the recurrence of AF after single RFCA varied from 11% to 29% and 7% to 24% after repeated RFCA in paroxysmal AF during 5 years follow-up, while up to 70% in persistent AF [2–4]. Erefore, it is very important to identify the predictors of AF recurrence after RFCA, which will help to improve the successful rate of RFCA and guide clinical practice. Univariate and multivariate Cox regression analysis were used to screen the risk factors for predicting the recurrence of AF after RFCA, and a International Journal of Clinical Practice nomogram prediction model based on screening was constructed to individually evaluate the risk of recurrence of AF
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