Evaluating the American Heart Association/American College of Cardiology Guideline—Recommended and Contemporary Pretest Probability Models in a Mixed Asian Cohort: The Contribution of Coronary Artery Calcium

Author:

Baskaran Lohendran123ORCID,Yan Linxuan2,Tan Chun S.1ORCID,Ho Woon W.1,Tan Swee Y.12,Williams Michelle C.4ORCID,Han Donghee5ORCID,Nakanishi Rine6ORCID,Cerci Rodrigo J.7ORCID,Ng Ming‐Yen8ORCID,Shaw Leslee J.9ORCID,Chua Terrance S. J.12,Douglas Pamela10ORCID,Winther Simon11

Affiliation:

1. Department of Cardiology National Heart Centre Singapore Singapore Singapore

2. Duke‐NUS Medical School National University of Singapore Singapore Singapore

3. CVS.AI National Heart Research Institute of Singapore Singapore Singapore

4. University of Edinburgh/British Heart Foundation Centre for Cardiovascular Science Edinburgh UK

5. Department of Imaging Cedars‐Sinai Medical Center Los Angeles CA USA

6. Department of Cardiovascular Medicine, Toho University Graduate School of Medicine Toho University Omori Medical Center Tokyo Japan

7. Quanta Diagnostico por Imagem Curitiba Brazil

8. Department of Diagnostic Radiology, School of Clinical Medicine, Li Ka Shing Faculty of Medicine The University of Hong Kong Pok Fu Lam Hong Kong

9. Icahn School of Medicine at Mount Sinai Blavatnik Family Women’s Health Research Institute New York NY USA

10. Division of Cardiology Duke University School of Medicine Durham NC USA

11. Department of Cardiology Gødstrup Hospital Herning Denmark

Abstract

Background Most pretest probability (PTP) tools for obstructive coronary artery disease (CAD) were Western ‐developed. The most appropriate PTP models and the contribution of coronary artery calcium score (CACS) in Asian populations remain unknown. In a mixed Asian cohort, we compare 5 PTP models: local assessment of the heart (LAH), CAD Consortium (CAD2), risk factor‐weighted clinical likelihood, the American Heart Association/American College of Cardiology and the European Society of Cardiology PTP and 3 extended versions of these models that incorporated CACS: LAH (CACS) , CAD2 (CACS) , and the CACS‐clinical likelihood. Methods and Results The study cohort included 771 patients referred for stable chest pain. Obstructive CAD prevalence was 27.5%. Calibration, area under the receiver‐operating characteristic curves (AUC) and net reclassification index were evaluated. LAH clinical had the best calibration (χ 2 5.8; P =0.12). For CACS models, LAH (CACS) showed least deviation between observed and expected cases (χ 2 37.5; P <0.001). There was no difference in AUCs between the LAH clinical (AUC, 0.73 [95% CI, 0.69–0.77]), CAD2 clinical (AUC, 0.72 [95% CI, 0.68–0.76]), risk factor‐weighted clinical likelihood (AUC, 0.73 [95% CI: 0.69–0.76) and European Society of Cardiology PTP (AUC, 0.71 [95% CI, 0.67–0.75]). CACS improved discrimination and reclassification of the LAH (CACS) (AUC, 0.88; net reclassification index, 0.46), CAD2 (CACS) (AUC, 0.87; net reclassification index, 0.29) and CACS‐CL (AUC, 0.87; net reclassification index, 0.25). Conclusions In a mixed Asian cohort, Asian‐derived LAH models had similar discriminatory performance but better calibration and risk categorization for clinically relevant PTP cutoffs. Incorporating CACS improved discrimination and reclassification. These results support the use of population‐matched, CACS‐inclusive PTP tools for the prediction of obstructive CAD.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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