A Narrative Review of the Role of Blood Biomarkers in the Risk Prediction of Cardiovascular Diseases

Résumé fourni par la source

Cardiovascular disease (CVD) is a global health crisis and a leading cause of morbidities and mortalities. Biomarkers whose evaluation would allow the detection of CVD at an early stage of development are actively sought. Biomarkers are objectively measured as indicators of health, disease, or response to an exposure or intervention, including therapeutic interventions. Hence, this review aims to identify biomarkers that can help predict CVD risk in the healthy population. This helps with risk prediction and is crucial for advancing preventive cardiology and improving clinical outcomes in a wide range of patient populations. Biomarkers such as atherogenic lipoproteins, fibrinogen, homocysteine, and thyroid-stimulating hormone (TSH) have been linked to CVD risk factors, including dyslipidemia, hypertension, diabetes, and obesity. When combined with conventional biomarkers, inflammatory markers such as C-reactive protein (CRP) can enhance risk prediction. However, biomarkers such as high-sensitivity troponin T (hsTnT) and N-terminal proBNP (NT-proBNP) are widely used as diagnostic biomarkers for heart failure (HF) and cardiac dysfunction, as they are released only after one to two hours of cardiovascular event occurrence. Myeloperoxidase (MPO) and procalcitonin (PCT) have developed into promising new biomarkers for the early detection of systemic bacterial infections as inflammatory markers, which are better diagnostic tools than screening. Combining biomarkers can improve test accuracy, but the best combinations for diagnosis or prognosis must be identified.

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