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dc.contributor.authorRuwanpathirana, T.
dc.contributor.authorOwen, A.
dc.contributor.authorReid, Christopher
dc.date.accessioned2017-01-30T15:39:23Z
dc.date.available2017-01-30T15:39:23Z
dc.date.created2015-06-18T20:00:25Z
dc.date.issued2015
dc.date.submitted2015-06-19
dc.identifier.citationRuwanpathirana, T. and Owen, A. and Reid, C. 2015. Review on Cardiovascular Risk Prediction. Cardiovascular Therapeutics. 33 (2): pp. 62-70.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/48411
dc.identifier.doi10.1111/1755-5922.12110
dc.description.abstract

The objectives were to review the currently available and widely used cardiovascular risk assessment models and to examine the evidence available on new biomarkers and the nonclinical measures in improving the risk prediction in the population level. Identification of individuals at risk of cardiovascular disease (CVD), to better target prevention and treatment, has become a top research priority. Cardiovascular risk prediction has progressed with the development and refinement of risk prediction models based upon established clinical factors, and the discovery of novel biomarkers, lifestyle, and social factors may offer additional information on the risk of disease. However, a significant proportion of individuals who have a myocardial infarction still are categorized as low risk by many of the available methods. Although novel biomarkers can improve risk prediction, including B-type natriuretic peptides which have shown the best predictive capacity per unit cost, there is concern that the use of risk prediction strategies which rely upon new/or expensive biomarkers could further broaden social inequalities in CVD. In contrast, nonclinical factors such as work stress, social isolation, and early childhood experience also appear to be associated with cardiovascular risk and have the potential to be utilized for the baseline risk stratification at the population level. A stepwise approach of nonclinical methods followed by risk scores consisting of clinical risk factors may offer a better option for initial and subsequent screening, preserving more specialized approaches including novel biomarkers for enhanced risk stratification at population level in a cost-effective manner.

dc.publisherWiley-Blackwell Publishing Ltd.
dc.subjectCost-effectiveness
dc.subjectNovel biomarkers
dc.subjectRisk prediction models
dc.subjectCardiovascular disease
dc.titleReview on Cardiovascular Risk Prediction
dc.typeJournal Article
dcterms.dateSubmitted2015-06-19
dcterms.source.volume33
dcterms.source.number2
dcterms.source.startPage62
dcterms.source.endPage70
dcterms.source.issn1755-5922
dcterms.source.titleCardiovascular Therapeutics
curtin.digitool.pid226959
curtin.pubStatusPublished
curtin.refereedTRUE
curtin.identifier.scriptidPUB-HEA-SPH-KA-88757
curtin.accessStatusFulltext not available


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