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. 2024 May 16;19(1):290.
doi: 10.1186/s13019-024-02742-7.

Model for predicting the recurrence of atrial fibrillation after monopolar or bipolar radiofrequency ablation in patients with AF and mitral valve disease

Wei Si  1 , Peng Teng  1 , Liang Ma  2
Affiliations

Model for predicting the recurrence of atrial fibrillation after monopolar or bipolar radiofrequency ablation in patients with AF and mitral valve disease

Wei Si et al. J Cardiothorac Surg. .

Abstract

Objectives: This study aimed to identify the risk factors for postoperative atrial fibrillation in patients with valvular atrial fibrillation, and establish predictive models of atrial fibrillation recurrence.

Methods: Overall, 224 patients who underwent radiofrequency ablation of atrial fibrillation from November 2014 to November 2020 were included. The statistical package for social sciences, X-tile, and R-studio were used for statistical analysis.

Results: Patients were divided into training and validation sets according to a ratio of 3:1. The training set was analysed using univariate and multivariate Cox regression analysis and showed that preoperative uric acid > 401 μmol/L (P = 0.006), B-type natriuretic peptide > 202 ng/L (P = 0.042), hypersensitivity C-reactive protein > 6.1 mg/L (P = 0.026), erythrocyte sedimentation rate > 7.0 mm/h (P = 0.016), preoperative left atrial diameter > 48 mm (P = 0.031) were significantly correlated with the recurrence of atrial fibrillation after radiofrequency ablation in patients with valvular atrial fibrillation. In the training set, a Cox regression model of the five related factors was established using the R language. The C-index of the model was 0.82, and the area under the receiver operating characteristic curve was 0.831 (P < 0.001). Internal and external verification was performed in the training and validation sets, respectively, and both showed that the fit of the verification curve was relatively good at 3 months, 6 months, 1 year, and 3 years postoperatively. After calculating the weight of each related factor using the nomogram, a new risk predictive model (BLUCE) for postoperative atrial fibrillation was established.

Conclusions: In patients with atrial fibrillation, preoperative uric acid, B-type natriuretic peptide, hypersensitivity C-reactive protein, erythrocyte sedimentation rate, and left atrial diameter are risk factors for atrial fibrillation or atrial flutter recurrence after radiofrequency ablation. The BLUCE predictive model can distinguish high-risk groups of postoperative atrial fibrillation. High-risk patients in the BLUCE model were more likely to experience recurrence of atrial fibrillation after radiofrequency ablation and a low possibility of maintaining sinus rhythm.

Keywords: Atrial fibrillation; Predictive model; Radiofrequency ablation; Recurrence.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Thresholds determined by X-tile
Fig. 2
Fig. 2
Training set: internal verification. The abscissa is the predicted sinus rate, and the ordinate is the actual postoperative maintenance sinus rate, “·” is the actual maintenance sinus rate of each subgroup, “×” is the corrected maintenance sinus rate obtained by repeated sampling 1000 times, the diagonal line is the reference line, The vertical bar is the 95% confidence interval. A: 3 months; B: 6 months; C: 1 year; D:3 years after surgery
Fig. 3
Fig. 3
Training set: Nomogram
Fig. 4
Fig. 4
Training set: the Kaplan-Meier estimates and area under ROC curve of BLUCE model. AUC = 0.831(P < 0.001)
Fig. 5
Fig. 5
General population: the Kaplan-Meier estimates of BLUCE model
See this image and copyright information in PMC

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