Gregory P. Fontana MD , Harun Kundi MD, MMSc , Steven V. Manoukian MD , Bruce Bowers MD , Todd M. Dewey MD , Charles T. Klodell MD , V. Seenu Reddy MD , John A. Riddick MD , Jorge A. Alvarez MD , Michael S. Chenier MD , Mark A. Groh MD , Marcos A. Nores MD , Pranav Loyalka MD , Francis J. Zidar MD , Julia B. Thompson MS , Maria C. Alu MS , David J. Cohen MD, MSc , Juan F. Granada MD , Martin B. Leon MD , Jeffrey J. Popma MD , Saibal Kar MD
{"title":"Outcomes After Transcatheter Aortic Valve Replacement Among Medicare Beneficiaries: The Impact of Frailty and Social Vulnerability","authors":"Gregory P. Fontana MD , Harun Kundi MD, MMSc , Steven V. Manoukian MD , Bruce Bowers MD , Todd M. Dewey MD , Charles T. Klodell MD , V. Seenu Reddy MD , John A. Riddick MD , Jorge A. Alvarez MD , Michael S. Chenier MD , Mark A. Groh MD , Marcos A. Nores MD , Pranav Loyalka MD , Francis J. Zidar MD , Julia B. Thompson MS , Maria C. Alu MS , David J. Cohen MD, MSc , Juan F. Granada MD , Martin B. Leon MD , Jeffrey J. Popma MD , Saibal Kar MD","doi":"10.1016/j.shj.2025.100685","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Transcatheter aortic valve replacement (TAVR) is an accepted alternative to surgery in many patients with severe aortic stenosis. Clinical trials have evaluated early and late outcomes in selected TAVR patients, but predictors of late mortality have been less well studied in a broadly inclusive, national patient cohort undergoing TAVR. We sought to characterize 5-year outcomes after TAVR in Medicare beneficiaries and to evaluate the incremental predictive value of demographics, comorbidities, procedural factors, frailty, and social vulnerability in determining late mortality risk.</div></div><div><h3>Methods</h3><div>We studied the fee-for-service Centers for Medicare & Medicaid Services MedPAR database that includes patients aged ≥65 years undergoing TAVR between 2017 and 2022. The primary endpoint was 5-year mortality. Sequential multivariable Cox models were constructed, incrementally adjusting for demographics, comorbidities, procedural and hospital characteristics, and frailty and social vulnerability. Model performance was assessed using C-statistics and integrated discrimination improvement (IDI).</div></div><div><h3>Results</h3><div>A total of 371,248 TAVR patients were included in the analysis. The baseline model, including only demographic factors (age, sex, and race), yielded modest model performance (C = 0.589). Inclusion of comorbidities improved the model discrimination substantially (C = 0.684; IDI +6.9%, <em>p</em> < 0.001), and adding hospital and procedural characteristics yielded additional gains (C = 0.695; IDI +0.9%, <em>p</em> < 0.001). The final model integrated frailty and social vulnerability and achieved the highest predictive accuracy (C = 0.705; IDI +1.0%, <em>p</em> < 0.001).</div></div><div><h3>Conclusions</h3><div>In this large national cohort, frailty and social vulnerability significantly improved risk prediction for long-term mortality after TAVR. We conclude that sociodemographic and frailty-related factors are important components for prediction of 5-year mortality after TAVR.</div></div>","PeriodicalId":36053,"journal":{"name":"Structural Heart","volume":"9 8","pages":"Article 100685"},"PeriodicalIF":2.8000,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Heart","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2474870625002775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Transcatheter aortic valve replacement (TAVR) is an accepted alternative to surgery in many patients with severe aortic stenosis. Clinical trials have evaluated early and late outcomes in selected TAVR patients, but predictors of late mortality have been less well studied in a broadly inclusive, national patient cohort undergoing TAVR. We sought to characterize 5-year outcomes after TAVR in Medicare beneficiaries and to evaluate the incremental predictive value of demographics, comorbidities, procedural factors, frailty, and social vulnerability in determining late mortality risk.
Methods
We studied the fee-for-service Centers for Medicare & Medicaid Services MedPAR database that includes patients aged ≥65 years undergoing TAVR between 2017 and 2022. The primary endpoint was 5-year mortality. Sequential multivariable Cox models were constructed, incrementally adjusting for demographics, comorbidities, procedural and hospital characteristics, and frailty and social vulnerability. Model performance was assessed using C-statistics and integrated discrimination improvement (IDI).
Results
A total of 371,248 TAVR patients were included in the analysis. The baseline model, including only demographic factors (age, sex, and race), yielded modest model performance (C = 0.589). Inclusion of comorbidities improved the model discrimination substantially (C = 0.684; IDI +6.9%, p < 0.001), and adding hospital and procedural characteristics yielded additional gains (C = 0.695; IDI +0.9%, p < 0.001). The final model integrated frailty and social vulnerability and achieved the highest predictive accuracy (C = 0.705; IDI +1.0%, p < 0.001).
Conclusions
In this large national cohort, frailty and social vulnerability significantly improved risk prediction for long-term mortality after TAVR. We conclude that sociodemographic and frailty-related factors are important components for prediction of 5-year mortality after TAVR.
背景:经导管主动脉瓣置换术(TAVR)是许多严重主动脉瓣狭窄患者接受的手术替代方法。临床试验已经评估了选定TAVR患者的早期和晚期结局,但在广泛包容的全国TAVR患者队列中,晚期死亡率的预测因素尚未得到很好的研究。我们试图描述医疗保险受益人TAVR后的5年预后,并评估人口统计学、合并症、程序因素、虚弱和社会脆弱性在确定晚期死亡风险方面的增量预测价值。方法我们研究了医疗保险和医疗补助服务收费中心MedPAR数据库,该数据库包括2017年至2022年期间接受TAVR的年龄≥65岁的患者。主要终点为5年死亡率。构建序列多变量Cox模型,逐步调整人口统计学、合并症、手术和医院特征、虚弱和社会脆弱性。采用c统计和综合判别改进(IDI)对模型性能进行评估。结果共纳入TAVR患者371248例。仅包括人口统计学因素(年龄、性别和种族)的基线模型产生了适度的模型性能(C = 0.589)。纳入合并症大大提高了模型的辨别性(C = 0.684; IDI +6.9%, p < 0.001),增加医院和程序特征获得了额外的收益(C = 0.695; IDI +0.9%, p < 0.001)。最终模型综合了脆弱性和社会脆弱性,预测准确率最高(C = 0.705; IDI +1.0%, p < 0.001)。结论在这个庞大的国家队列中,虚弱和社会脆弱性显著提高了TAVR术后长期死亡率的风险预测。我们得出结论,社会人口学和虚弱相关因素是预测TAVR后5年死亡率的重要组成部分。