Comparison of Estimated Glomerular Filtration Rates and Albuminuria in Predicting Risk of Coronary Heart Disease in a Population with High Prevalence of Diabetes Mellitus and Renal Disease

摘要

Improved accuracy in predicting coronary heart disease (CHD) risk in persons with diabetes and kidney disease is needed. Addition of albuminuria to established methods of CHD risk calculation was reported in the Strong Heart Study (SHS) cohort. In this article, the addition of estimated glomerular filtration rate (eGFR) is evaluated with data from 4,549 American Indian SHS participants, ages 45–74 years. After adjustment for Framingham CHD risk factors, hazard ratios for eGFR as a predictor of CHD were 1.69 (95% confidence interval: 1.34, 2.13) in women and 1.41 (95% confidence interval: 0.94, 2.13) in men. Models including albuminuria, eGFR, or both scored higher in discriminatory power than models using conventional risk factors alone in women; in men the improvement was seen only for albuminuria and the combination of albuminuria and eGFR. Hosmer–Lemeshow assessments showed good calibration for the models using eGFR alone in both genders, followed by models including albuminuria alone in both genders. Adding eGFR improved the NRI in women (0.085, p=.0004) but not in men (0.010, p=0.1967). NRI and IDI were improved in both genders using both albuminuria and eGFR (NRI: 0.135, p<.0001; IDI: 0.027, p<.0001 in women; NRI: 0.035, p<0.0196; IDI: 0.008 p<0.0156 in men). Therefore, a risk calculator including albuminuria enhances CHD prediction compared with one using only standard risk factors in men and women. Including eGFR alone improves risk prediction in women, but for men it is preferable to have both eGFR and albuminuria. In conclusion, this enhanced calculator should be useful in estimating CHD risk in populations with high prevalence of diabetes and renal disease.