Echocardiographic derived forward left ventricular output improves risk prediction in systolic heart failure.

Cardiac Index Cardiac Output Ejection Fraction Heart Failure LVOT-VTI Stroke Volume Systolic Function

Journal

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography
ISSN: 1097-6795
Titre abrégé: J Am Soc Echocardiogr
Pays: United States
ID NLM: 8801388

Informations de publication

Date de publication:
26 Jun 2024
Historique:
received: 16 03 2024
revised: 30 05 2024
accepted: 05 06 2024
medline: 29 6 2024
pubmed: 29 6 2024
entrez: 28 6 2024
Statut: aheadofprint

Résumé

Though widely used to classify heart failure (HF) patients, the prognostic role of left ventricular ejection fraction (LVEF) is debated. We hypothesized that the echocardiographic measures of forward LV output, being more representative of cardiac hemodynamics, may improve risk prediction in a large cohort of HF patients with systolic dysfunction. Consecutive stable HF patients with LVEF <50% on guideline-recommended therapies undergoing an echocardiography including the evaluation of forward LV output (i.e., LV outflow tract velocity-time integral [LVOT-VTI], stroke volume index [SVi], and cardiac index [CI]) over a 6-year period, were selected and followed-up for the endpoint of cardiac and all-cause death. Among the 1,509 patients analyzed (71±12 years, 75% males, LVEF 35±9%), 328 (22%) died during a median 28-month (14-40) follow-up, 165 (11%) of which for cardiac causes. At multivariable regression analysis, LVOT-VTI (<0.001), SVi (p<0.001), and CI (p<0.001), but not LVEF (p>0.05), predicted cardiac and all-cause death. The optimal prognostic cut-offs for LVOT-VTI, SVi, and CI were 15 cm, 38 mL/m The echocardiographic evaluation of forward LV output improves risk prediction in HF patients across a wide LVEF spectrum over other well-established clinical, biohumoral, and echocardiographic prognostic markers.

Sections du résumé

BACKGROUND AND AIMS OBJECTIVE
Though widely used to classify heart failure (HF) patients, the prognostic role of left ventricular ejection fraction (LVEF) is debated. We hypothesized that the echocardiographic measures of forward LV output, being more representative of cardiac hemodynamics, may improve risk prediction in a large cohort of HF patients with systolic dysfunction.
METHODS METHODS
Consecutive stable HF patients with LVEF <50% on guideline-recommended therapies undergoing an echocardiography including the evaluation of forward LV output (i.e., LV outflow tract velocity-time integral [LVOT-VTI], stroke volume index [SVi], and cardiac index [CI]) over a 6-year period, were selected and followed-up for the endpoint of cardiac and all-cause death.
RESULTS RESULTS
Among the 1,509 patients analyzed (71±12 years, 75% males, LVEF 35±9%), 328 (22%) died during a median 28-month (14-40) follow-up, 165 (11%) of which for cardiac causes. At multivariable regression analysis, LVOT-VTI (<0.001), SVi (p<0.001), and CI (p<0.001), but not LVEF (p>0.05), predicted cardiac and all-cause death. The optimal prognostic cut-offs for LVOT-VTI, SVi, and CI were 15 cm, 38 mL/m
CONCLUSION CONCLUSIONS
The echocardiographic evaluation of forward LV output improves risk prediction in HF patients across a wide LVEF spectrum over other well-established clinical, biohumoral, and echocardiographic prognostic markers.

Identifiants

pubmed: 38942218
pii: S0894-7317(24)00321-3
doi: 10.1016/j.echo.2024.06.008
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024. Published by Elsevier Inc.

Auteurs

Francesco Gentile (F)

Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Pisa, Italy.

Paolo Sciarrone (P)

Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Giorgia Panichella (G)

Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Pisa, Italy.

Lorenzo Bazan (L)

Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Pisa, Italy.

Vladyslav Chubuchny (V)

Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Francesco Buoncristiani (F)

Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Simone Gasparini (S)

Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Pisa, Italy.

Claudia Taddei (C)

Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Elisa Poggianti (E)

Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Iacopo Fabiani (I)

Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Alberto Aimo (A)

Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Christina Petersen (C)

Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Claudio Passino (C)

Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Michele Emdin (M)

Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy.

Alberto Giannoni (A)

Health Science Interdisciplinary Center, Scuola Superiore Sant'Anna, Pisa, Italy; Fondazione Toscana Gabriele Monasterio, Pisa, Italy. Electronic address: a.giannoni@santannapisa.it.

Classifications MeSH