Identification of persons at high risk of coronary heart disease--a mathematical formula based on biochemical, anthropometric and clinical markers.

A reliable method for identification of the subset of population predisposed to coronary heart disease (CHD) would aid a targetted implementation of intervention strategies. To this end, a mathematical formula was developed based on stepwise linear discriminant analysis. Age, body mass index, the number of associated coronary risk factors and a large number of biochemical markers were analysed by computerised discriminant analysis on a test sample of 203 subjects. Unstandardised canonical discriminant coefficients of statistically significant independent variables were used to derive the total discriminant score or the 'risk score'. The 'low-risk' persons not in need of immediate preventive measures of CHD could be distinguished from the 'high-risk' individuals with an almost 90% correctness. As compared with the existing methods such as clinical evaluation and cardiac stress test, the risk scores derived by the new method, and based chiefly on blood markers besides clinical and anthropometric variables, appeared to correctly predict the future coronary episodes in members of the test sample selected at random. The risk scores were also tested on a new sample of 50 subjects; while low scores were not associated with CHD, high scores in some patients were associated with myocardial ischemia. It appears that the preventive measures of CHD may be directed at people who have no clinical manifestations of CHD, but whose risk scores are greater than 0.1. On the other hand, if the score is less than -1.0, immediate preventive measures may not be necessary. If the score is between -1.0 and 0.1 (borderline), no immediate action may be taken but the score may be determined after six months, and action taken accordingly.