Predicting and measuring mortality risk after transcatheter aortic valve replacement

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.

Medienart:

E-Artikel

Erscheinungsjahr:

2021

Erschienen:

2021

Enthalten in:

Zur Gesamtaufnahme - volume:19

Enthalten in:

Expert review of cardiovascular therapy - 19(2021), 3 vom: 19. März, Seite 247-260

Sprache:

Englisch

Beteiligte Personen:

Gupta, Tanush [VerfasserIn]
Joseph, Denny T [VerfasserIn]
Goel, Sachin S [VerfasserIn]
Kleiman, Neal S [VerfasserIn]

Links:

Volltext

Themen:

Aortic stenosis
Journal Article
Mortality
Mortality prediction models
Review
Transcatheter aortic valve replacement

Anmerkungen:

Date Completed 04.05.2021

Date Revised 04.05.2021

published: Print-Electronic

Citation Status MEDLINE

doi:

10.1080/14779072.2021.1888715

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM321205162