Algorithm for predicting CHD death risk in Turkish adults: conventional factors contribute only moderately in women

Objective: To assist the management strategy of individuals, we determined an algorithm for predicting the risk of coronary heart disease (CHD) death in Turkish adults with a high prevalence of metabolic syndrome (MetS). Methods: The risk of CHD death was estimated in 3054 middle-aged adults, followed over 9.08 +/- 4.2 years. Cox proportional hazard regression was used to predict risk. Discrimination was assessed using C-statistics. Results: CHD death was identified in 233 subjects. In multivariable analysis, the serum high-density lipoprotein-cholesterol (HDL-C) level was not predictive in men and the non-HDL-C level was not predictive in women. Age, presence of diabetes, systolic blood pressure >= 160 mm Hg, smoking habit, and low physical activity were predictors in both sexes. The exclusion of coronary disease at baseline did not change the risk estimates materially. Using an algorithm of the 7 stated variables, individuals in the highest category of risk score showed a 19- to 50-fold higher spread in the absolute risk of death from CHD than those in the second lowest category. C-index of the model using age alone was as high as 0.774 in men and 0.836 in women (p<0.001 each), while the incorporation of 6 conventional risk factors contributed to a C-index of 0.058 in males and 0.042 in females. Conclusion: In a middle-aged population with prevalent MetS, men disclosed anticipated risk parameters (except for high HDL-C levels) as determinants of the risk of CHD death. On the other hand, serum non-HDL-C levels and moderate systolic hypertension were not relevant in women. The moderate contribution of conventional risk factors (beyond age) to the estimation of the risk of CHD death in women is consistent with the operation of autoimmune activation.