Prognosis of Severe Low-Flow, Low-Gradient Aortic Stenosis by Stroke Volume Index and Transvalvular Flow Rate.


Journal

JACC. Cardiovascular imaging
ISSN: 1876-7591
Titre abrégé: JACC Cardiovasc Imaging
Pays: United States
ID NLM: 101467978

Informations de publication

Date de publication:
05 2021
Historique:
received: 17 08 2020
revised: 10 12 2020
accepted: 21 12 2020
pubmed: 22 3 2021
medline: 28 8 2021
entrez: 21 3 2021
Statut: ppublish

Résumé

This study determined whether flow state classified by stroke volume index (SVi) or transvalvular flow rate (FR) improved risk stratification of all-cause mortality, hospitalization due to heart failure, and aortic valvular interventions for patients with severe aortic stenosis (AS). SVi is a widely accepted classification for flow state in severe low-flow, low-gradient (LFLG) AS. Recent studies suggest that FR more closely approximates true AS severity and provides more useful prognostication than SVi. Patients with severe AS over a 7-year period were subclassified by echocardiographic parameters. LFLG-AS was defined as severe AS (aortic valve area index [AVAi]: <0.6 cm Among 621 consecutive patients with severe AS, the proportions of patients classified as LFLG-AS were different between SVi and FR (p < 0.001). Classification using SVi, FR, and LVEF was a strong predictor of the composite endpoint at the 2-year follow-up. The addition of SVi to the echocardiographic and clinical model provided significant improvement in reclassification (net reclassification improvement: 0.089; 95% confidence interval [CI]: 0.045 to 0.133; p = 0.04), whereas addition of FR did not (net reclassification improvement: 0.061; 95% CI: 0.016 to 0.106; p = 0.17). C-statistics indicated improved risk discrimination when AVAi, LVEF, and SVi or FR were added as predictive variables to the clinical model (p = 0.006). Low SVi or FR was associated with adverse cardiovascular events and showed improvement in discrimination, but only SVi, not FR, significantly improved risk reclassification compared to other conventional clinical and echocardiographic predictors. This suggests that FR is not superior to SVi in distinguishing true severe from pseudosevere forms of AS and identification of patients with LFLG-AS who have worse outcomes.

Sections du résumé

OBJECTIVES
This study determined whether flow state classified by stroke volume index (SVi) or transvalvular flow rate (FR) improved risk stratification of all-cause mortality, hospitalization due to heart failure, and aortic valvular interventions for patients with severe aortic stenosis (AS).
BACKGROUND
SVi is a widely accepted classification for flow state in severe low-flow, low-gradient (LFLG) AS. Recent studies suggest that FR more closely approximates true AS severity and provides more useful prognostication than SVi.
METHODS
Patients with severe AS over a 7-year period were subclassified by echocardiographic parameters. LFLG-AS was defined as severe AS (aortic valve area index [AVAi]: <0.6 cm
RESULTS
Among 621 consecutive patients with severe AS, the proportions of patients classified as LFLG-AS were different between SVi and FR (p < 0.001). Classification using SVi, FR, and LVEF was a strong predictor of the composite endpoint at the 2-year follow-up. The addition of SVi to the echocardiographic and clinical model provided significant improvement in reclassification (net reclassification improvement: 0.089; 95% confidence interval [CI]: 0.045 to 0.133; p = 0.04), whereas addition of FR did not (net reclassification improvement: 0.061; 95% CI: 0.016 to 0.106; p = 0.17). C-statistics indicated improved risk discrimination when AVAi, LVEF, and SVi or FR were added as predictive variables to the clinical model (p = 0.006).
CONCLUSIONS
Low SVi or FR was associated with adverse cardiovascular events and showed improvement in discrimination, but only SVi, not FR, significantly improved risk reclassification compared to other conventional clinical and echocardiographic predictors. This suggests that FR is not superior to SVi in distinguishing true severe from pseudosevere forms of AS and identification of patients with LFLG-AS who have worse outcomes.

Identifiants

pubmed: 33744157
pii: S1936-878X(21)00065-6
doi: 10.1016/j.jcmg.2020.12.029
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

915-927

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Funding Support and Author Disclosures This work has been supported in part by a partnership grant (1149692) from the National Health and Medical Research Council, Canberra. Dr. Sen was supported by scholarships from the National Heart Foundation of Australia (identification: 102578), National Health and Medical Research Council of Australia (identification: 1191044), Baker Heart and Diabetes Institute (Bright Sparks), and the Australian Government Research Training Program. Dr. Stub is supported by a fellowship from the National Heart Foundation, Canberra. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Auteurs

Jonathan Sen (J)

Baker Heart and Diabetes Institute, Melbourne, Australia; Department of Medicine, University of Melbourne, Melbourne, Australia; Western Health, Melbourne, Australia.

Quan Huynh (Q)

Baker Heart and Diabetes Institute, Melbourne, Australia; Monash University Alfred Health, Melbourne, Australia.

Dion Stub (D)

Baker Heart and Diabetes Institute, Melbourne, Australia; Western Health, Melbourne, Australia; Monash University Alfred Health, Melbourne, Australia.

Christopher Neil (C)

Baker Heart and Diabetes Institute, Melbourne, Australia; Department of Medicine, University of Melbourne, Melbourne, Australia; Western Health, Melbourne, Australia.

Thomas H Marwick (TH)

Baker Heart and Diabetes Institute, Melbourne, Australia; Department of Medicine, University of Melbourne, Melbourne, Australia; Western Health, Melbourne, Australia; Monash University Alfred Health, Melbourne, Australia. Electronic address: Tom.marwick@baker.edu.au.

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