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. 2006 Jun 27;113(25):2897-905.
doi: 10.1161/CIRCULATIONAHA.105.593178. Epub 2006 Jun 12.

Prediction of coronary heart disease in a population with high prevalence of diabetes and albuminuria: the Strong Heart Study

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Prediction of coronary heart disease in a population with high prevalence of diabetes and albuminuria: the Strong Heart Study

Elisa T Lee et al. Circulation. .

Abstract

Background: The present article presents equations for the prediction of coronary heart disease (CHD) in a population with high rates of diabetes and albuminuria, derived from data collected in the Strong Heart Study, a longitudinal study of cardiovascular disease in 13 American Indian tribes and communities in Arizona, North and South Dakota, and Oklahoma.

Methods and results: Participants of the Strong Heart Study were examined initially in 1989-1991 and were monitored with additional examinations and mortality and morbidity surveillance. CHD outcome data through December 2001 showed that age, gender, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein cholesterol, smoking, diabetes, hypertension, and albuminuria were significant CHD risk factors. Hazard ratios for ages 65 to 75 years, hypertension, LDL cholesterol > or = 160 mg/dL, diabetes, and macroalbuminuria were 2.58, 2.01, 2.44, 1.66, and 2.11 in men and 2.03, 1.69, 2.17, 2.26, and 2.69 in women, compared with ages 45 to 54 years, normal blood pressure, LDL cholesterol <100 mg/dL, no diabetes, and no albuminuria. Prediction equations for CHD and a risk calculator were derived by gender with the use of Cox proportional hazards model and the significant risk factors. The equations provided good discrimination ability, as indicated by a c statistic of 0.70 for men and 0.73 for women. Results from bootstrapping methods indicated good internal validation and calibration.

Conclusions: A "risk calculator" has been developed and placed on the Strong Heart Study Web site, which provides predicted risk of CHD in 10 years with input of these risk factors. This may be valuable for diverse populations with high rates of diabetes and albuminuria.

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