Change in left atrial function and volume predicts incident heart failure with preserved and reduced ejection fraction: Multi-Ethnic Study of Atherosclerosis.

heart failure left atrium

Journal

European heart journal. Cardiovascular Imaging
ISSN: 2047-2412
Titre abrégé: Eur Heart J Cardiovasc Imaging
Pays: England
ID NLM: 101573788

Informations de publication

Date de publication:
17 Jun 2024
Historique:
received: 14 03 2024
revised: 12 05 2024
accepted: 22 05 2024
medline: 17 6 2024
pubmed: 17 6 2024
entrez: 17 6 2024
Statut: aheadofprint

Résumé

The role of change in left atrial (LA) parameters prior to the onset of heart failure (HF) remains unclear. We used cardiac magnetic resonance (CMR) imaging to investigate the relationship between longitudinal change in LA function and incident HF in a multi-ethnic population with subclinical cardiovascular disease (CVD). In this prospective multi-ethnic cohort study, 2470 participants (60 ± 9 years, 47% males), free at baseline of clinical CVD, had LA volume and function assessed via multimodality tissue tracking on CMR imaging at baseline (2000-02) and a second study 9.4 ± 0.6 years later. Free of HF, 73 participants developed incident HF [HF with preserved ejection fraction (HFpEF), n = 39; reduced ejection fraction (HFrEF), n = 34] 7.1 ± 2.1 years after the second study. An annual decrease of 1 SD unit in peak LA strain (ΔLASmax) was most strongly associated with the risk of HFpEF [subdistribution hazard ratios (HR) = 2.56, 95% confidence interval (CI) (1.34-4.90), P = 0.004] and improved model reclassification and discrimination in predicting HFpEF [C-statistic = 0.84, 95% CI (0.79-0.90); net reclassification index (NRI) = 0.34, P = 0.01; and integrated discrimination index (IDI) = 0.02, P = 0.02], whilst an annual decrease of 1 mL/m2 of pre-atrial indexed LA volumes (ΔLAVipreA) was most strongly associated with the risk of HFrEF [subdistribution HR = 1.88, 95% CI (1.44-2.45), P < 0.001] and improved model reclassification and discrimination in predicting HFrEF [C-statistic = 0.81, 95% CI (0.72-0.90); NRI = 0.31, P = 0.03; and IDI = 0.01, P = 0.50] after adjusting for event-specific risk factors and baseline LA measures. ΔLASmax and ΔLAVipreA were associated with and incrementally predictive of HFpEF and HFrEF, after adjusting for risk factors and baseline LA measures in this population of subclinical CVD.

Identifiants

pubmed: 38885142
pii: 7695192
doi: 10.1093/ehjci/jeae138
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : NHLBI NIH HHS
ID : UL1-TR-000040
Pays : United States
Organisme : NCATS NIH HHS
Pays : United States

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.

Déclaration de conflit d'intérêts

Conflict of interest: None declared.

Auteurs

Daniel J Lim (DJ)

School of Medicine, Johns Hopkins University, Baltimore MD, USA.

Vinithra Varadarajan (V)

School of Medicine, Johns Hopkins University, Baltimore MD, USA.

Thiago Quinaglia (T)

School of Medicine, Johns Hopkins University, Baltimore MD, USA.

Theo Pezel (T)

School of Medicine, Johns Hopkins University, Baltimore MD, USA.

Colin Wu (C)

Office of Biostatistics Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA.

Chikara Noda (C)

School of Medicine, Johns Hopkins University, Baltimore MD, USA.

Susan R Heckbert (SR)

Department of Epidemiology, University of Washington, Seattle, WA, USA.

David Bluemke (D)

Department of Radiology, University of Wisconsin-Madison, WI, USA.

Bharath Ambale-Venkatesh (B)

School of Medicine, Johns Hopkins University, Baltimore MD, USA.

Joao A C Lima (JAC)

School of Medicine, Johns Hopkins University, Baltimore MD, USA.

Classifications MeSH