Predicting and measuring mortality risk after transcatheter aortic valve replacement

Tanush Gupta, Denny T. Joseph, Sachin S. Goel, Neal S. Kleiman

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

Introduction: Over the last decade, transcatheter aortic valve replacement (TAVR) has emerged as a treatment option for most patients with severe symptomatic aortic stenosis (AS). With growing indications and exponential increase in the number of TAVR procedures, it is important to be able to accurately predict mortality after TAVR. Areas covered: Herein, we review the surgical and TAVR-specific mortality prediction models (MPMs) and their performance in their original derivation and external validation cohorts. We then discuss the role of other important risk assessment tools such as frailty, echocardiographic parameters, and biomarkers in patients, being considered for TAVR. Expert opinion: Conventional surgical MPMs have suboptimal predictive performance and are mis-calibrated when applied to TAVR populations. Although a number of TAVR-specific MPMs have been developed, their utility is also limited by their modest discriminative ability when applied to populations external to their original derivation cohorts. There is an unmet need for robust TAVR MPMs that accurately predict post TAVR mortality. In the interim, heart teams should utilize the currently available TAVR-specific MPMs in conjunction with other prognostic factors, such as frailty, echocardiographic or computed tomography (CT) imaging parameters, and biomarkers for risk assessment of patients, being considered for TAVR.

Original languageEnglish (US)
Pages (from-to)247-260
Number of pages14
JournalExpert Review of Cardiovascular Therapy
Volume19
Issue number3
DOIs
StatePublished - 2021

Keywords

  • Transcatheter aortic valve replacement
  • aortic stenosis
  • mortality
  • mortality prediction models

ASJC Scopus subject areas

  • Internal Medicine
  • Cardiology and Cardiovascular Medicine

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