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Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease
Cardiovascular disease (CVD) is the leading cause of death globally. Risk assessment is crucial for identifying at-risk individuals who require immediate attention as well as to guide the intensity of medical therapy to reduce subsequent risk of CVD. In the past decade, many risk prediction models h...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517145/ https://www.ncbi.nlm.nih.gov/pubmed/34660715 http://dx.doi.org/10.3389/fcvm.2021.713191 |
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author | Wong, Yuen-Kwun Tse, Hung-Fat |
author_facet | Wong, Yuen-Kwun Tse, Hung-Fat |
author_sort | Wong, Yuen-Kwun |
collection | PubMed |
description | Cardiovascular disease (CVD) is the leading cause of death globally. Risk assessment is crucial for identifying at-risk individuals who require immediate attention as well as to guide the intensity of medical therapy to reduce subsequent risk of CVD. In the past decade, many risk prediction models have been proposed to estimate the risk of developing CVD. However, in patients with a history of CVD, the current models that based on traditional risk factors provide limited power in predicting recurrent cardiovascular events. Several biomarkers from different pathophysiological pathways have been identified to predict cardiovascular events, and the incorporation of biomarkers into risk assessment may contribute to enhance risk stratification in secondary prevention. This review focuses on biomarkers related to cardiovascular and metabolic diseases, including B-type natriuretic peptide, high-sensitivity cardiac troponin I, adiponectin, adipocyte fatty acid-binding protein, heart-type fatty acid-binding protein, lipocalin-2, fibroblast growth factor 19 and 21, retinol-binding protein 4, plasminogen activator inhibitor-1, 25-hydroxyvitamin D, and proprotein convertase subtilisin/kexin type 9, and discusses the potential utility of these biomarkers in cardiovascular risk prediction among patients with CVD. Many of these biomarkers have shown promise in improving risk prediction of CVD. Further research is needed to assess the validity of biomarker and whether the strategy for incorporating biomarker into clinical practice may help to optimize decision-making and therapeutic management. |
format | Online Article Text |
id | pubmed-8517145 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85171452021-10-16 Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease Wong, Yuen-Kwun Tse, Hung-Fat Front Cardiovasc Med Cardiovascular Medicine Cardiovascular disease (CVD) is the leading cause of death globally. Risk assessment is crucial for identifying at-risk individuals who require immediate attention as well as to guide the intensity of medical therapy to reduce subsequent risk of CVD. In the past decade, many risk prediction models have been proposed to estimate the risk of developing CVD. However, in patients with a history of CVD, the current models that based on traditional risk factors provide limited power in predicting recurrent cardiovascular events. Several biomarkers from different pathophysiological pathways have been identified to predict cardiovascular events, and the incorporation of biomarkers into risk assessment may contribute to enhance risk stratification in secondary prevention. This review focuses on biomarkers related to cardiovascular and metabolic diseases, including B-type natriuretic peptide, high-sensitivity cardiac troponin I, adiponectin, adipocyte fatty acid-binding protein, heart-type fatty acid-binding protein, lipocalin-2, fibroblast growth factor 19 and 21, retinol-binding protein 4, plasminogen activator inhibitor-1, 25-hydroxyvitamin D, and proprotein convertase subtilisin/kexin type 9, and discusses the potential utility of these biomarkers in cardiovascular risk prediction among patients with CVD. Many of these biomarkers have shown promise in improving risk prediction of CVD. Further research is needed to assess the validity of biomarker and whether the strategy for incorporating biomarker into clinical practice may help to optimize decision-making and therapeutic management. Frontiers Media S.A. 2021-10-01 /pmc/articles/PMC8517145/ /pubmed/34660715 http://dx.doi.org/10.3389/fcvm.2021.713191 Text en Copyright © 2021 Wong and Tse. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Wong, Yuen-Kwun Tse, Hung-Fat Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease |
title | Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease |
title_full | Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease |
title_fullStr | Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease |
title_full_unstemmed | Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease |
title_short | Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease |
title_sort | circulating biomarkers for cardiovascular disease risk prediction in patients with cardiovascular disease |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8517145/ https://www.ncbi.nlm.nih.gov/pubmed/34660715 http://dx.doi.org/10.3389/fcvm.2021.713191 |
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