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Coronary Artery Calcium may Help Predict Risk of Heart Disease
Tamar S. Polonsky, from the Northwestern University Feinberg School of Medicine, Chicago, and colleagues conducted the study to determine whether adding CACS to a prediction model based on traditional risk factors improves classification of risk.
CACS was measured by computed tomography (a type of imaging method) in 6,814 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), a population-based cohort without known cardiovascular disease.
Recruitment of participants began in July 2000, with follow-up through May 2008. Five-year risk estimates for new CHD were categorized as 0 percent to less than 3 percent, 3 percent to less than 10 percent, and 10 percent or more using hazards models.
Model 1 incorporated age, race/ethnicity, sex, tobacco use, antihypertensive medication use, systolic blood pressure and total and high-density lipoprotein cholesterol measurements.
Model 2 used these risk factors plus CACS. The researchers calculated the net reclassification improvement using model 2 vs. model 1.
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