Evaluating the Coronary Artery Disease Consortium Model and the Coronary Artery Calcium Score in Predicting

Lohendran Baskaran1,2, Yu Pei Neo2, Jing Kai Lee2

  • 1Department of Cardiology National Heart Centre Singapore.

Insights

Coronary artery calcium (CAC) scoring significantly improves the prediction of obstructive coronary artery disease (CAD) in Asian populations when added to clinical risk models. Local calibration enhances model performance for better diagnostic accuracy.

Area of Science:

  • Cardiology
  • Medical Imaging
  • Preventive Medicine

Background:

  • Pretest probability scores for obstructive coronary artery disease (CAD) vary by population.
  • Previous studies on coronary artery calcium (CAC) additive value were mainly in Western populations.
  • This study evaluates the CAD Consortium (CAD2) model in a Singaporean Asian cohort.

Purpose of the Study:

  • To assess the CAD2 model's utility in predicting obstructive CAD in a mixed Asian cohort with stable chest pain.
  • To determine the incremental value of CAC scoring in enhancing obstructive CAD prediction.
  • To compare the performance of CAD2 and locally calibrated models.

Main Methods:

  • Retrospective analysis of 522 patients undergoing cardiac computed tomography for chest pain.
  • Comparison of the CAD2 clinical model (age, sex, symptoms, risk factors) with the CAD2 extended model (including CAC).
  • Evaluation of locally calibrated "local assessment of the heart" models against CAD2 models.

Main Results:

  • The CAD2 clinical model achieved an AUC of 0.718.
  • Incorporating CAC score improved AUC to 0.896 for CAD2 models.
  • Locally calibrated models showed superior discriminative performance compared to CAD2 models (P<0.05).

Conclusions:

  • The CAD2 model is validated in a symptomatic Asian population.
  • Local calibration of risk models enhances predictive performance.
  • CAC scoring offers significant incremental value for predicting obstructive CAD.

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