BACKGROUND: Coronary artery calcium (CAC) scoring is increasingly being used after myocardial perfusion imaging (MPI) to detect preclinical coronary artery disease (CAD). However, there are few data to support this approach. METHODS AND RESULTS: We reviewed 200 consecutive patients without known CAD who were referred for CAC scoring shortly after nonischemic MPI. Of these, 13 (6.5%) had CAC scores greater than 400, indicating significant CAD; 22 (11%) had CAC scores of 101 to 400; 27 had CAC scores of 11 to 100; and the remainder (n = 138) has CAC scores of 1 to 10. Traditional risk factors and patient characteristics were not significant predictors of CAC scores of 101 or greater. However, age and the Framingham risk score were predictors of CAC scores greater than 0. At follow-up, significantly more patients with CAC scores of 101 or greater had been given the advice to take lipid-lowering medication and aspirin compared with those with CAC scores of 0. CONCLUSIONS: Of patients referred for CAC scoring after nonischemic MPI, 17.5% were identified as having CAD based on a CAC score greater than 100, allowing intervention with aggressive medical therapy. Patients who were reclassified were not easily identifiable by traditional risk factors, but Framingham risk score did predict the presence of CAC. Clinicians modified medical therapy based on the results of CAC scoring.
BACKGROUND: Coronary artery calcium (CAC) scoring is increasingly being used after myocardial perfusion imaging (MPI) to detect preclinical coronary artery disease (CAD). However, there are few data to support this approach. METHODS AND RESULTS: We reviewed 200 consecutive patients without known CAD who were referred for CAC scoring shortly after nonischemic MPI. Of these, 13 (6.5%) had CAC scores greater than 400, indicating significant CAD; 22 (11%) had CAC scores of 101 to 400; 27 had CAC scores of 11 to 100; and the remainder (n = 138) has CAC scores of 1 to 10. Traditional risk factors and patient characteristics were not significant predictors of CAC scores of 101 or greater. However, age and the Framingham risk score were predictors of CAC scores greater than 0. At follow-up, significantly more patients with CAC scores of 101 or greater had been given the advice to take lipid-lowering medication and aspirin compared with those with CAC scores of 0. CONCLUSIONS: Of patients referred for CAC scoring after nonischemic MPI, 17.5% were identified as having CAD based on a CAC score greater than 100, allowing intervention with aggressive medical therapy. Patients who were reclassified were not easily identifiable by traditional risk factors, but Framingham risk score did predict the presence of CAC. Clinicians modified medical therapy based on the results of CAC scoring.
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