Biomarker Profiling for Risk of Future Heart Failure (HFpEF) Development

Overview

Journal J Transl Med

Publisher Biomed Central

Specialties Biomedical Engineering
General Medicine

Date 2021 Feb 10

PMID 33563287

Citations 20

Authors

Chris J Watson

Joe Gallagher

Mark Wilkinson

Adam Russell-Hallinan

Isaac Tea

Stephanie James

James OReilly

Eoin OConnell

Shuaiwei Zhou

Mark Ledwidge

Ken McDonald

Affiliations

Soon will be listed here.

Abstract

Background: The purpose of this study was to investigate the utility of BNP, hsTroponin-I, interleukin-6, sST2, and galectin-3 in predicting the future development of new onset heart failure with preserved ejection fraction (HFpEF) in asymptomatic patients at-risk for HF.

Methods: This is a retrospective analysis of the longitudinal STOP-HF study of thirty patients who developed HFpEF matched to a cohort that did not develop HFpEF (n = 60) over a similar time period. Biomarker candidates were quantified at two time points prior to initial HFpEF diagnosis.

Results: HsTroponin-I and BNP at baseline and follow-up were statistically significant predictors of future new onset HFpEF, as was galectin-3 at follow-up and concentration change over time. Interleukin-6 and sST2 were not predictive of future development of new onset HFpEF in this study. Unadjusted biomarker combinations of hsTroponin-I, BNP, and galectin-3 could significantly predict future HFpEF using both baseline (AUC 0.82 [0.73,0.92]) and follow-up data (AUC 0.86 [0.79,0.94]). A relative-risk matrix was developed to categorize the relative-risk of new onset of HFpEF based on biomarker threshold levels.

Conclusion: We provided evidence for the utility of BNP, hsTroponin-I, and Galectin-3 in the prediction of future HFpEF in asymptomatic event-free populations with cardiovascular disease risk factors.

Citing Articles

Biomarkers in Heart Failure with Preserved Ejection Fraction: A Perpetually Evolving Frontier.

Vrabie A, Totolici S, Delcea C, Badila E J Clin Med. 2024; 13(16).

PMID: 39200768 PMC: 11355893. DOI: 10.3390/jcm13164627.

Understanding Galectin-3's Role in Diastolic Dysfunction: A Contemporary Perspective.

Hao W, Cheng C, Liu J, Chen H, Chen J, Cheng T Life (Basel). 2024; 14(7).

PMID: 39063659 PMC: 11277993. DOI: 10.3390/life14070906.

Artificial Intelligence Enabled Prediction of Heart Failure Risk from Single-lead Electrocardiograms.

Dhingra L, Aminorroaya A, Pedroso A, Khunte A, Sangha V, McIntyre D medRxiv. 2024; .

PMID: 38854022 PMC: 11160804. DOI: 10.1101/2024.05.27.24307952.

Scalable Risk Stratification for Heart Failure Using Artificial Intelligence applied to 12-lead Electrocardiographic Images: A Multinational Study.

Dhingra L, Aminorroaya A, Sangha V, Pedroso Camargos A, Asselbergs F, Brant L medRxiv. 2024; .

PMID: 38633808 PMC: 11023679. DOI: 10.1101/2024.04.02.24305232.

Relationship between high sensitivity troponin I and clinical outcomes in non-acute coronary syndrome (non-ACS) acute heart failure patients - a one-year follow-up study.

Kumar D, Muneer D, Qureshi D Indian Heart J. 2024; 76(2):139-145.

PMID: 38599282 PMC: 11143518. DOI: 10.1016/j.ihj.2024.04.003.

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