We have located links that may give you full text access.
Validity of Coronary Artery Disease Consortium Models for Predicting Obstructive Coronary Artery Disease & Cardiovascular Events in Patients with Acute Chest Pain Considered for Coronary Computed Tomographic Angiography.
American Journal of Cardiology 2018 October 16
Although the majority of acute chest pain patients are diagnosed with noncardiac chest pain after noninvasive testing, identifying these low-risk patients before testing is challenging. The objective of this study was to validate the coronary artery disease (CAD) consortium models for predicting obstructive CAD and 30-day major adverse cardiovascular events (MACE) in acute chest pain patients considered for coronary computed tomography angiogram, as well as to determine the pretest probability threshold that identifies low-risk patients with <1% MACE. We studied 1,981 patients with no known CAD and negative initial troponin and electrocardiogram. We evaluated CAD consortium models (basic: age, sex, and chest pain type; clinical: basic + diabetes, hypertension, dyslipidemia, and smoking; and clinical + coronary calcium score [CAC] models) for prediction of obstructive CAD (≥50% stenosis on coronary CT angiogram) and 30-day MACE (Acute Myocardial Infarction, revascularization, and mortality). The C-statistic for predicting obstructive CAD was 0.77 (95% confidence interval [CI] 0.73 to 0.77) for the basic, 0.80 (95% CI 0.77 to 0.80) for the clinical, and 0.88 (95% CI 0.85 to 0.88) for the clinical + CAC models. The C-statistic for predicting 30-day MACE was 0.82 (95% CI 0.77 to 0.87) for the basic, 0.84 (95% CI 0.79 to 0.88) for the clinical, and 0.87 (95% CI 0.83 to 0.91) for the clinical + CAC models. In 47.3% of patients for whom the clinical model predicted ≤5% probability for obstructive CAD, the observed 30-day MACE was 0.53% (95% CI 0.07% to 0.999%); in the 66.9% of patients for whom the clinical + CAC model predicted ≤5% probability, the 30-day MACE was 0.75% (95% CI 0.29% to 1.22%). We propose a chest pain evaluation algorithm based on these models that classify 63.3% of patients as low risk with 0.56% (95% CI 0.15% to 0.97%) 30-day MACE. In conclusion, CAD consortium models have excellent diagnostic and prognostic value for acute chest pain patients and can safely identify a significant proportion of low-risk patients by achieving <1% missed 30-day MACE.
Full text links
Related Resources
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app
All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.
By using this service, you agree to our terms of use and privacy policy.
Your Privacy Choices
You can now claim free CME credits for this literature searchClaim now
Get seemless 1-tap access through your institution/university
For the best experience, use the Read mobile app