PURPOSE: To determine whether stress-rest myocardial perfusion single-photon emission (MPS) computed tomography improves coronary heart disease (CHD) risk classification in diabetic patients. METHODS: In 822 consecutive diabetic patients, risk estimates for a CHD event were categorized as 0% to <3%, 3% to <5%, and ≥5% per year using Cox proportional hazards models. Model 1 used traditional CHD risk factors and electrocardiography (ECG) stress test data and model 2 used these variables plus MPS imaging data. We calculated the net reclassification improvement (NRI) and compared the distribution of risk using model 2 vs. model 1. CHD death, myocardial infarction and unstable angina requiring coronary revascularization were the outcome measures. RESULTS: During follow-up (58 ± 11 months), 148 events occurred. Model 2 improved risk prediction compared to model 1 (NRI 0.25, 95% confidence interval, CI, 0.15-0.34; p < 0.001). Overall, 301 patients were reclassified to a higher risk category, with an event rate of 28%, and 26 to a lower risk category, with an event rate of 15%. Among patients at 3% to <5% risk, 53% were reclassified at higher risk and 25% at lower risk (NRI 0.42, 95% CI 0.07-0.76; p < 0.05). The cost per NRI was $880.80 for MPS imaging as compared to an outpatient visit with an ECG stress test. CONCLUSION: The addition of MPS imaging data to a prediction model based on traditional risk factors and ECG stress test data significantly improved CHD risk classification in patients with diabetes.
PURPOSE: To determine whether stress-rest myocardial perfusion single-photon emission (MPS) computed tomography improves coronary heart disease (CHD) risk classification in diabeticpatients. METHODS: In 822 consecutive diabeticpatients, risk estimates for a CHD event were categorized as 0% to <3%, 3% to <5%, and ≥5% per year using Cox proportional hazards models. Model 1 used traditional CHD risk factors and electrocardiography (ECG) stress test data and model 2 used these variables plus MPS imaging data. We calculated the net reclassification improvement (NRI) and compared the distribution of risk using model 2 vs. model 1. CHD death, myocardial infarction and unstable angina requiring coronary revascularization were the outcome measures. RESULTS: During follow-up (58 ± 11 months), 148 events occurred. Model 2 improved risk prediction compared to model 1 (NRI 0.25, 95% confidence interval, CI, 0.15-0.34; p < 0.001). Overall, 301 patients were reclassified to a higher risk category, with an event rate of 28%, and 26 to a lower risk category, with an event rate of 15%. Among patients at 3% to <5% risk, 53% were reclassified at higher risk and 25% at lower risk (NRI 0.42, 95% CI 0.07-0.76; p < 0.05). The cost per NRI was $880.80 for MPS imaging as compared to an outpatient visit with an ECG stress test. CONCLUSION: The addition of MPS imaging data to a prediction model based on traditional risk factors and ECG stress test data significantly improved CHD risk classification in patients with diabetes.
Authors: Manuel D Cerqueira; Neil J Weissman; Vasken Dilsizian; Alice K Jacobs; Sanjiv Kaul; Warren K Laskey; Dudley J Pennell; John A Rumberger; Thomas Ryan; Mario S Verani Journal: Circulation Date: 2002-01-29 Impact factor: 29.690
Authors: Tamar S Polonsky; Robyn L McClelland; Neal W Jorgensen; Diane E Bild; Gregory L Burke; Alan D Guerci; Philip Greenland Journal: JAMA Date: 2010-04-28 Impact factor: 56.272
Authors: R Hachamovitch; D S Berman; L J Shaw; H Kiat; I Cohen; J A Cabico; J Friedman; G A Diamond Journal: Circulation Date: 1998-02-17 Impact factor: 29.690