Plasma biomarkers associated with adverse outcomes in patients with calcific aortic stenosis

AimsEnhanced risk stratification of patients with aortic stenosis (AS) is necessary to identify patients at high risk for adverse outcomes, and may allow for better management of patient subgroups at high risk of myocardial damage. The objective of this study was to identify plasma biomarkers and mu...

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Bibliographic Details
Published in:European journal of heart failure 2021-12, Vol.23 (12), p.2021-2032
Main Authors: Vidula, Mahesh K., Orlenko, Alena, Zhao, Lei, Salvador, Lisa, Small, Aeron M., Horton, Edward, Cohen, Jordana B., Adusumalli, Srinath, Denduluri, Srinivas, Kobayashi, Taisei, Hyman, Matthew, Fiorilli, Paul, Magro, Caroline, Singh, Bibi, Pourmussa, Bianca, Greczylo, Candy, Basso, Michael, Ebert, Christina, Yarde, Melissa, Li, Zhuyin, Cvijic, Mary Ellen, Wang, Zhaoqing, Walsh, Alice, Maranville, Joseph, Kick, Ellen, Luettgen, Joseph, Adam, Leonard, Schafer, Peter, Ramirez‐Valle, Francisco, Seiffert, Dietmar, Moore, Jason H., Gordon, David, Chirinos, Julio A.
Format: Article
Language:English
Subjects:
Aortic stenosis
Aortic Valve Stenosis
Biomarkers
Calcification
Calcinosis
Heart Failure
Humans
Inflammation
Machine learning
Natriuretic Peptide, Brain
Peptide Fragments
Prognosis
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Summary:AimsEnhanced risk stratification of patients with aortic stenosis (AS) is necessary to identify patients at high risk for adverse outcomes, and may allow for better management of patient subgroups at high risk of myocardial damage. The objective of this study was to identify plasma biomarkers and multimarker profiles associated with adverse outcomes in AS. Methods and resultsWe studied 708 patients with calcific AS and measured 49 biomarkers using a Luminex platform. We studied the correlation between biomarkers and the risk of (i) death and (ii) death or heart failure‐related hospital admission (DHFA). We also utilized machine‐learning methods (a tree‐based pipeline optimizer platform) to develop multimarker models associated with the risk of death and DHFA. In this cohort with a median follow‐up of 2.8 years, multiple biomarkers were significantly predictive of death in analyses adjusted for clinical confounders, including tumour necrosis factor (TNF)‐α [hazard ratio (HR) 1.28, P 
ISSN:1388-9842
1879-0844
DOI:10.1002/ejhf.2361