Analysis of risk factors in patients with nonvalvular persistent atrial fibrillation complicated with ventricular hypertrophy and construction and validation of prediction model
10.19405/j.cnki.issn1000–1492.2026.03.023
- VernacularTitle:非瓣膜性持续性房颤患者合并左心室肥厚的危险因素模型预测及预后分析
- Author:
Fang LIU
1
;
Peiyang ZHENG
1
;
Huimin WANG
1
;
Danni LI
1
;
Ao LIANG
1
;
Ren ZHAO
1
Author Information
1. Department of Cardiology， The First Affiliated Hospital of Anhui Medical University，Hefei 230022
- Publication Type:Journal Article
- Keywords:
persistent atrial fibrillation;
left ventricular hypertrophy;
risk factor;
nomogram;
major adverse cardiovascular events;
recrudesce;
Cox regression analysis
- From:
Acta Universitatis Medicinalis Anhui
2026;61(3):552-561
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo construct a nomogram prediction model for non-valvular persistent atrial fibrillation （PeAF） patients with left ventricular hypertrophy （LVH） ， followed by prognostic analysis through follow-up. MethodsThis study retrospectively enrolled 949 patients with newly diagnosed and hospitalized non-valvular PeAF. Among them， 403 patients presented with LVH. The cohort was randomly stratified into a training set （n=665） and a validation set （n=284）. Univariate and multivariate Logistic regression analyses were employed to identify independent risk factors for PeAF complicated by LVH. A nomogram prediction model was subsequently constructed and evaluated for discriminative ability， calibration， and clinical utility using receiver operating characteristic （ROC） curve analysis， calibration plots， and decision curve analysis （DCA）. ResultsSeven independent risk factors were ultimately identified and included in the prediction model： female sex， hypertension， diabetes， red blood cell distribution width-SD （RDW-SD）， body mass index （BMI）， left atrial diameter （LAD）， and left ventricular ejection fraction （LVEF）. The area under the ROC curve （AUC） in the training set was 0.862 （95% CI： 0.834-0.890）， and in the validation set， it was 0.870 （95% CI： 0.829-0.911）， demonstrating excellent predictive performance. ConclusionIndependent risk factors for LVH in PeAF patients include female， hypertension， diabetes， RDW-SD， BMI， LAD， and LVEF. The prediction model built based on this can help early identification of PeAF patients with high risk of LVH. At the same time， the incidence of major adverse cardiovascular events （MACE） is higher in PeAF patients with LVH. Patients with atrial fibrillation combined with LVH may benefit from catheter ablation.
