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Published on: January 28, 2020
Circulating Biomarkers for Cardiovascular Disease Risk Prediction in Patients With Cardiovascular Disease
Yuen-Kwun Wong1, Hung-Fat Tse1,2,3,4
1Department of Medicine, The University of Hong Kong, Queen Mary Hospital, Hong Kong, China.
Insights
Biomarkers show promise for predicting recurrent cardiovascular events (CVD) in patients with existing CVD. Incorporating these novel markers may improve risk assessment and guide treatment strategies for secondary prevention.
Area of Science:
- Biochemistry
- Cardiology
- Metabolic Diseases
Background:
- Cardiovascular disease (CVD) is a leading global cause of mortality.
- Current CVD risk prediction models have limited accuracy for recurrent events in patients with established CVD.
- Novel biomarkers may enhance risk stratification in secondary CVD prevention.
Purpose of the Study:
- To review biomarkers associated with cardiovascular and metabolic diseases.
- To discuss the potential utility of these biomarkers in predicting recurrent CVD events.
- To explore the role of biomarkers in optimizing clinical decision-making for CVD patients.
Main Methods:
- Literature review of biomarkers related to cardiovascular and metabolic pathways.
- Analysis of studies investigating biomarker utility in CVD risk prediction.
- Focus on biomarkers including B-type natriuretic peptide, cardiac troponin I, adiponectin, and others.
Main Results:
- Several biomarkers demonstrate potential for improving CVD risk prediction.
- Biomarkers from diverse pathophysiological pathways show promise.
- Biomarker incorporation may enhance risk stratification in secondary prevention.
Conclusions:
- Biomarkers offer potential to improve cardiovascular risk prediction in patients with existing CVD.
- Further research is essential to validate biomarkers and their clinical utility.
- Integrating biomarkers may optimize therapeutic management and decision-making in CVD care.
Abstract:
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.
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