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Published on: August 9, 2024
Clinical risk factors alone are inadequate for predicting significant coronary artery disease
Frederick K Korley1, Constantine Gatsonis2, Bradley S Snyder3
1Department of Emergency Medicine, University of Michigan Medical School, Ann Arbor, MI, United States.
Insights
Clinical risk factors alone are insufficient for identifying patients with significant coronary artery disease (CAD) among those with suspected acute coronary syndrome (ACS). Coronary artery calcium scoring offers superior prediction of CAD.
Area of Science:
- Cardiology
- Medical Imaging
- Diagnostic Accuracy
Background:
- Accurate identification of significant coronary artery disease (CAD) in patients with suspected acute coronary syndrome (ACS) is crucial for timely intervention.
- Existing clinical risk factors have limitations in predicting the presence of undiagnosed significant CAD.
- Computed Tomography Angiography (CTA) is utilized for ruling out ACS.
Purpose of the Study:
- To develop and validate a predictive model for identifying patients with suspected ACS who have undiagnosed significant CAD.
- To compare the predictive performance of clinical risk factors against coronary artery calcium (CAC) scoring for significant CAD.
Main Methods:
- Secondary analysis of a randomized control trial (RCT) involving patients randomized to a CTA arm.
- Model derivation using a training dataset (2/3) and internal validation (IV) using a test dataset (1/3) from the RCT.
- External validation (EV) using CTA data from emergency department patients at a separate center. Significant CAD defined as ≥50% stenosis.
Main Results:
- Significant CAD prevalence was 11.2% in the derivation cohort and 8.2% in the EV cohort.
- A logistic regression model incorporating age, sex, tobacco use, diabetes, and race showed moderate predictive ability (ROC AUC 0.72 IV, 0.76 EV).
- Coronary artery calcium scoring demonstrated superior accuracy (ROC AUC 0.85 IV, 0.92 EV) compared to clinical risk factors alone.
Conclusions:
- Clinical risk factors, individually or combined, are inadequate for accurately identifying suspected ACS patients with significant undiagnosed CAD.
- Coronary artery calcium scoring is a more effective predictor of significant CAD than clinical risk factors in this patient population.
- Further research may explore integrating CAC scores into risk stratification protocols for suspected ACS.
Objective:
We sought to derive and validate a model for identifying suspected ACS patients harboring undiagnosed significant coronary artery disease (CAD).
Methods:
This was a secondary analysis of data from a randomized control trial (RCT). Patients randomized to the CTA arm of an RCT examining a CTA-based strategy for ruling-out acute coronary syndrome (ACS) constitute the derivation cohort, which was randomly divided into a training dataset (2/3, used for model derivation) and a test dataset (1/3, used for internal validation (IV)). ED patients from a different center receiving CTA to evaluate for suspected ACS constitute the external validation (EV) cohort. Primary outcome was CTA-assessed significant CAD (stenosis of ≥50% in a major coronary artery).
Results:
In the derivation cohort, 11.2% (76/679) of subjects had CTA-assessed significant CAD, and in the EV cohort, 8.2% of subjects (87/1056) had CTA-assessed significant CAD. Age was the strongest predictor of significant CAD among the clinical risk factors examined. Predictor variables included in the derived logistic regression model were: age, sex, tobacco use, diabetes, and race. This model exhibited an area under the receiver operating characteristic curve (ROC AUC) of 0.72 (95% CI: 0.61-0.83) based on IV, and 0.76 (95% CI: 0.70, 0.82) based on EV. The derived random forest model based on clinical risk factors yielded improved but not sufficient discrimination of significant CAD (ROC AUC = 0.76 [95% CI: 0.67-0.85] based on IV). Coronary artery calcium score was a more accurate predictor of significant CAD than any combination of clinical risk factors (ROC AUC = 0.85 [95% CI: 0.76-0.94] based on IV; ROC AUC = 0.92 [95% CI: 0.88-0.95] based on EV).
Conclusions:
Clinical risk factors, either individually or in combination, are insufficient for accurately identifying suspected ACS patients harboring undiagnosed significant coronary artery disease.
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