Can a composite index predict ischaemic heart disease risk?

Abstract

INTRODUCTION: Ischaemic heart diseases (IHD) are the leading cause of death worldwide and it accounts for 12.2% of the total deaths globally. Although the individual risk factors of IHD are well understood, the possibility of predicting the risk of IHD of an individual at a given time is less understood. Aims: To develop an index to predict the risk of IHD based on individual biological parameters. Methods: Secondary data of 217 individuals were analysed. Multivariate and logistic regression techniques were used to construct a composite index (CI) based on standardised measurements of lipid profile, fasting blood sugar, systolic and diastolic blood pressure. Two sample ttest and 95% confidence interval based on composite index scores were used to compare the two groups and define a cutoff point. Results: Mean [±SE] of the CI scores for undiagnosed and diagnosed IHD individuals were 0.013 [+0.014] and -0.1 [±0.041] respectively. The mean scores of the two groups were significantly different (p=0.008) and the confidence intervals for undiagnosed and diagnosed groups were -0.181 to -0.019 &-0.016 to 0.042 respectively. Accordingly, cut off point was estimated as - 0.018. CONCLUSIONS: The CI score can be used to distinguish those who are at risk from those who are risk free. Since the CI is based on several variables, the tests are more powerful compared to those based on individual variables. The CI approach has to be evaluated in several other study settings for verification. With some detailed studies, working cut off point can be established.