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Classical and Novel Biomarkers for Cardiovascular Risk Prediction in the United States

Cardiovascular risk prediction models based on classical risk factors identified in epidemiologic cohort studies are useful in primary prevention of cardiovascular disease in individuals. This article briefly reviews aspects of cardiovascular risk prediction in the United States and efforts to evalu...

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Detalles Bibliográficos
Autor principal: Folsom, Aaron R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japan Epidemiological Association 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3700256/
https://www.ncbi.nlm.nih.gov/pubmed/23604062
http://dx.doi.org/10.2188/jea.JE20120157
Descripción
Sumario:Cardiovascular risk prediction models based on classical risk factors identified in epidemiologic cohort studies are useful in primary prevention of cardiovascular disease in individuals. This article briefly reviews aspects of cardiovascular risk prediction in the United States and efforts to evaluate novel risk factors. Even though many novel risk markers have been found to be associated with cardiovascular disease, few appear to improve risk prediction beyond the powerful, classical risk factors. A recent US consensus panel concluded that clinical measurement of certain novel markers for risk prediction was reasonable, namely, hemoglobin A1c (in all adults), microalbuminuria (in patients with hypertension or diabetes), and C-reactive protein, lipoprotein-associated phospholipase, coronary calcium, carotid intima-media thickness, and ankle/brachial index (in patients deemed to be at intermediate cardiovascular risk, based on traditional risk factors).