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Development and Validation of a Novel Prognostic Model Predicting the Atrial Fibrillation Recurrence Risk for
Youzheng Dong1, Zhenyu Zhai1, Bo Zhu1
1Department of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, 330006, People's Republic of China.
Background:
This study aimed to establish and assess a prediction model for patients with persistent atrial fibrillation (AF) treated with nifekalant during the first radiofrequency catheter ablation (RFCA).
Methods:
In this study, 244 patients with persistent AF from January 17, 2017 to December 14, 2017, formed the derivation cohort, and 205 patients with persistent AF from December 15, 2017 to October 28, 2018, constituted the validation cohort. The least absolute shrinkage and selection operator regression was used for variable screening and the multivariable Cox survival model for nomogram development. The accuracy and discriminative capability of this predictive model were assessed according to discrimination (area under the curve [AUC]) and calibration. Clinical practical value was evaluated using decision curve analysis.
Results:
Body mass index, AF duration, sex, left atrial diameter, and the different responses after nifekalant administration were identified as AF recurrence-associated factors, all of which were selected for the nomogram. In the development and validation cohorts, the AUC for predicting 1-year AF-free survival was 0.863 (95% confidence interval (CI) 0.801-0.926) and 0.855 (95% CI 0.782-0.929), respectively. The calibration curves showed satisfactory agreement between the actual AF-free survival and the nomogram prediction in the derivation and validation cohorts. In both groups, the prognostic score enabled stratifying the patients into different AF recurrence risk groups.
Conclusions:
This predictive nomogram can serve as a quantitative tool for estimating the 1-year AF recurrence risk for patients with persistent AF treated with nifekalant during the first RFCA.
