Long-Term Epidemiologic Prediction of Coronary Disease

Abstract

Atherosclerotic cardiovascular disease is a complex problem involving lipid deposition, pressure, rheologic forces, carbohydrate tolerance and thrombogenesis. The major contributors identified through epidemiologic research include atherogenic personal attributes, living habits which promote them, signs of a compromised coronary circulation and host susceptibility to these risk factors. Of the atherogenic risk attributes, such as blood lipids, blood pressure, glucose tolerance and fibrinogen, each independently contributes to risk, and the risk associated with any one is compounded by the presence of the others. The risk associated with hypertension, hyperlipidemia or diabetes varies widely depending on the level of associated risk factors. Also, at a given level of total cholesterol, risk is greatly affected by the total/HDL cholesterol ratio, which provides a practical means for assessing the two-way traffic of cholesterol. In addition, living habits, such as cigarette smoking or lack of exercise, can independently affect the risk associated with any of the atherogenic traits. These living habits, obesity and diet can also affect the level of atherogenic risk factors and must be taken into account in assessing risk and implementing preventive measures. Finally, preclinical indicators of silent myocardial ischemia greatly augment the risk associated with a poor cardiovascular risk profile. Hence, ECG left ventricular hypertrophy, blocked intraventricular conduction, repolarization abnormalities and abnormal response to exercise on monitoring must be taken into consideration. Optimal risk predictions require a quantitative synthesis of risk factors into a composite estimate. Handbooks, hand calculators and PC software have been devised for office use based on multiple logistic risk formulations. These have been shown to accurately predict disease risk in a variety of American population samples, in elderly as well as young coronary candidates. Preventive management as well as risk estimation should be multifactorial if optimal results are to be achieved. Preventive strategies should include public health measures to alter the ecology so as to shift the distribution of risk factors to a more favorable level, health education to enable people to protect their own health and preventive medicine for high-risk candidates. Greater skill must be developed to carry out such interventions. In selecting drugs to correct hypertension, diabetes and lipid disorders, it is important to choose agents which do not adversely affect the composite risk profile.