Predictive models of cardiovascular risk
Journal Title: Revista Cuarzo - Year 2016, Vol 22, Issue 2
Abstract
Predictive models estimate the likelihood of developing a cardiovascular event (CVD), are developed based on spe-cifi c population factors and have been internally validated by measuring their discrimination and calibration, in order to support primary and secondary intervention, nonetheless, if it is necessary to make them in a different population, an external validation must be performed. Several controversies surround these models, on the use of diabetes and the use in the Colombian population. Pos-tures have been considered about considering diabetes as a cardiovascular risk equivalent, assessing these patients as well as providing a separate approach; and there are even studies that defend different positions, is an issue that is still controversial and among the international guides. On the other hand, studies have been carried out in the Colombian population using the same historical cohort, one comparing Framingham and PROCAM and another SCORE, ACC / AHA and adjusted Framingham; The fi rst study determined that there was better calibration and discrimination while Framingham overestimated the risk, and the latter concluded that ACC / AHA is better than SCORE, but estimates the risk and in fact not one correctly estimates it. In spite of this, the guides favor the use of the adjusted Framingham. This refl ects the need to delve into research on cardiovascular risk, especially in our environment, to provide a suc-cessful approach to the Colombian population, reducing CVD, improving the quality of life of the patient and reducing the costs of the health system.
Authors and Affiliations
Burgos Martínez, E. , Ramírez, A. , & Villamil, E.
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Predictive models of cardiovascular risk
Predictive models estimate the likelihood of developing a cardiovascular event (CVD), are developed based on spe-cifi c population factors and have been internally validated by measuring their discrimination and calibrat...
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