Coronary artery calcification and cardiovascular risk prediction

Abstract

Prevention of cardiovascular events starts with predicting one’s cardiovascular risk, to be used as a solid base for the required level of intensity of preventive measures. Hence, the accuracy of our risk prediction is vital. Risk assessment algorithms, based on traditional risk factors, such as the U.S. Framingham Risk Score1 and its European counterpart SCORE (Systemic COronary Risk Evaluation),2 are widely used to estimate absolute 10-year risk of cardiovascular events. Traditional cardiovascular risk factors like age, gender, blood pressure and cholesterol are clearly related to the severity of atherosclerosis, the underlying mechanism of cardiovascular disease (CVD). However, at every level of risk factor exposure, there is substantial variation in the quantity of atherosclerosis. This variation in disease is probably due to interactions between risk factors, duration of exposure to the specific level of the risk factors, genetic disparity and aspects as biological and laboratory variability in the risk factor. Therefore, measuring the amount of atherosclerosis, representing the end result of risk exposures, might be useful to improve CVD risk prediction