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Development and Validation of a Prognostic Nomogram for Post-Transcatheter Aortic Valve Replacement Heart Failure Hospitalization in Patients With Concurrent Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction: A Multicenter Study 期刊论文

编号：

279D329B9DD4B5BB52D0E0A399DA5FBD
作者：

Wang, Jun#^[1,2,3,4]Duan, Shoupeng^[5];Li, Hui^[1];Wu, Shili^[1,6];Zhao, Peng^[1];Zhu, Tongjian^[7];Tang, Shengxing(汤圣兴)^[8]Zhu, Jiajun*^[9]Tang, Bi*^[1,2,3]Liu, Jinjun*^[1,2,3,4]
语种：

英文
期刊：

JOURNAL OF THE AMERICAN HEART ASSOCIATION ISSN：2047-9980 2026 年 15 卷 6 期 ; MAR 17
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关键词：

heart failure with preserved ejection fraction predictive modeling symptomatic aortic stenosis transcatheter aortic valve replacement
摘要：

Background Existing risk stratification models are insufficient in identifying patients at high risk for heart failure (HF) hospitalization, particularly among those presenting with symptomatic aortic stenosis and the HF with preserved ejection fraction phenotype.Methods This multicenter cohort study enrolled 321 patients diagnosed with severe aortic stenosis and HF with preserved ejection fraction who underwent transcatheter aortic valve replacement between January 2017 and February 2024. Various predictive modeling techniques were used, including random forest, XGBoost, SuperPC, plsRcox, least absolute shrinkage and selection operator-Cox, Gradient Boosting Machine, Coxboost, and Cox regression analysis, at multiple time points.Results Patients were divided into a derivation cohort (n=191) and an external validation cohort (n=130) based on institutional affiliation, with a median follow-up of 20 months. Feature selection using the Boruta algorithm and least absolute shrinkage and selection operator regression, combined with variance inflation factor analysis to assess multicollinearity, identified 6 independent predictors. Among 8 prediction models evaluated, the Cox regression-based nomogram demonstrated superior performance in external validation, achieving time-dependent area under the curve values of 0.824 (95% CI, 0.693-0.956) at 12 months and 0.818 (95% CI, 0.715-0.920) at 20 months. The nomogram exhibited excellent calibration and substantial clinical utility across both time points, consistently outperforming the European System for Cardiac Operative Risk Evaluation in discrimination and reclassification analyses. An interactive web-based clinical decision support tool was developed to facilitate point-of-care implementation.Conclusions This nomogram, based on machine learning and incorporating metabolic biomarkers, exhibits high predictive accuracy for HF hospitalization in patients with symptomatic aortic stenosis and high-risk HF with preserved ejection fraction phenotype following transcatheter aortic valve replacement.Registration URL: https://www.clinicaltrials.gov; Unique Identifier: ChiCTR2400092655.
推荐引用方式
GB/T 7714：

Wang Jun,Duan Shoupeng,Li Hui, et al. Development and Validation of a Prognostic Nomogram for Post-Transcatheter Aortic Valve Replacement Heart Failure Hospitalization in Patients With Concurrent Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction: A Multicenter Study [J].JOURNAL OF THE AMERICAN HEART ASSOCIATION,2026,15(6).
APA：

Wang Jun,Duan Shoupeng,Li Hui,Wu Shili,&Liu Jinjun.(2026).Development and Validation of a Prognostic Nomogram for Post-Transcatheter Aortic Valve Replacement Heart Failure Hospitalization in Patients With Concurrent Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction: A Multicenter Study .JOURNAL OF THE AMERICAN HEART ASSOCIATION,15(6).
MLA：

Wang Jun, et al. "Development and Validation of a Prognostic Nomogram for Post-Transcatheter Aortic Valve Replacement Heart Failure Hospitalization in Patients With Concurrent Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction: A Multicenter Study" .JOURNAL OF THE AMERICAN HEART ASSOCIATION 15,6(2026).
入库时间：

3/31/2026 10:11:55 PM
更新时间：

3/31/2026 10:11:55 PM

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