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Study Demonstrates the Viability of Coronary Artery Calcification Testing in Asymptomatic Patients

By MedImaging International staff writers
Posted on 13 Jul 2015
The results of a cohort study that investigated the ability of Computed Tomography (CT) Coronary Artery Calcification (CAC) scores to predict mortality in people with no symptoms of coronary artery disease have been published.

The researchers, from Emory University School of Medicine (Atlanta, Georgia), Weill Cornell Medical College (New York, NY; USA), Johns Hopkins Ciccarone Center for the Prevention of Heart Disease (Baltimore, MD), Cedars-Sinai Medical Center (Cedars, USA‎), Harbor–UCLA Medical Center (Los Angeles, CA; USA), and Tennessee Heart and Vascular Institute (Hendersonville, TN, USA), published the results in the July, 7, 2015, issue of the Annals of Internal Medicine. The researchers found a strong relation between near-term adverse clinical outcomes, and the CAC score, during a follow-up period of 15 years. The study group consisted of 9,715 asymptomatic patients. The researchers collected data about binary risk factors, coronary artery calcification, and mortality, and used uni- and multi-variable Cox proportional hazards models to compare the distribution of surviving study participants. The researchers also calculated the net reclassification improvement statistic.

The resulting Cox models, adjusted for risk factors for coronary artery disease, showed that the CAC score was highly predictive of all-cause mortality. Mortality rates during 15 years of follow up were 3% to 28% for CAC scores from 0 to 1,000 or higher, while the relative hazard for all-cause mortality ranged from 1.68 for a CAC score of 1 to 10, to 6.26 for a CAC score of 1,000 or more. The categorical net reclassification improvement score was 0.21.

The researchers concluded that the extent of CAC, in a large group of asymptomatic patients, could accurately predict their 15-year mortality. The study demonstrated that CAC and other biomarkers can be used to accurately predict patient outcomes.

Related Links:

Emory University School of Medicine
Weill Cornell Medical College
Cedars-Sinai Medical Center



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