Year: 2012
Type: dissertation
Abstract: Prevention of cardiovascular events starts with predicting one’s cardiovascular risk, \nto be used as a solid base for the required level of intensity of preventive measures. \nHence, the accuracy of our risk prediction is vital. Risk assessment algorithms, based \non traditional risk factors, such as the U.S. Framingham Risk Score1 and its European \ncounterpart SCORE (Systemic COronary Risk Evaluation),2 are widely used to estimate \nabsolute 10-year risk of cardiovascular events. Traditional cardiovascular risk factors \nlike age, gender, blood pressure and cholesterol are clearly related to the severity of \natherosclerosis, the underlying mechanism of cardiovascular disease (CVD). However, \nat every level of risk factor exposure, there is substantial variation in the quantity of \natherosclerosis. This variation in disease is probably due to interactions between risk \nfactors, duration of exposure to the specific level of the risk factors, genetic disparity and \naspects as biological and laboratory variability in the risk factor. Therefore, measuring \nthe amount of atherosclerosis, representing the end result of risk exposures, might be \nuseful to improve CVD risk prediction.
Author: Suzette E. Elias-Smale
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2169611199