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Incorporating Coronary Calcification Into Pre-Test Assessment of the Likelihood of Coronary Artery Disease.

Authors :
Winther S
Schmidt SE
Mayrhofer T
Bøtker HE
Hoffmann U
Douglas PS
Wijns W
Bax J
Nissen L
Lynggaard V
Christiansen JJ
Saraste A
Bøttcher M
Knuuti J
Source :
Journal of the American College of Cardiology [J Am Coll Cardiol] 2020 Nov 24; Vol. 76 (21), pp. 2421-2432.
Publication Year :
2020

Abstract

Background: The prevalence of obstructive coronary artery disease (CAD) in symptomatic patients referred for diagnostic testing has declined, warranting optimization of individualized diagnostic strategies.<br />Objectives: This study sought to present a simple, clinically applicable tool enabling estimation of the likelihood of obstructive CAD by combining a pre-test probability (PTP) model (Diamond-Forrester approach using sex, age, and symptoms) with clinical risk factors and coronary artery calcium score (CACS).<br />Methods: The new tool was developed in a cohort of symptomatic patients (n = 41,177) referred for diagnostic testing. The risk factor-weighted clinical likelihood (RF-CL) was calculated through PTP and risk factors, while the CACS-weighted clinical likelihood (CACS-CL) added CACS. The 2 calculation models were validated in European and North American cohorts (n = 15,411) and compared with a recently updated PTP table.<br />Results: The RF-CL and CACS-CL models predicted the prevalence of obstructive CAD more accurately in the validation cohorts than the PTP model, and markedly increased the area under the receiver-operating characteristic curves of obstructive CAD: for the PTP model, 72 (95% confidence intervals [CI]: 71 to 74); for the RF-CL model, 75 (95% CI: 74 to 76); and for the CACS-CL model, 85 (95% CI: 84 to 86). In total, 38% of the patients in the RF-CL group and 54% in the CACS-CL group were categorized as having a low clinical likelihood of CAD, as compared with 11% with the PTP model.<br />Conclusions: A simple risk factor and CACS-CL tool enables improved prediction and discrimination of patients with suspected obstructive CAD. The tool empowers reclassification of patients to low likelihood of CAD, who need no further testing.<br />Competing Interests: Author Relationship With Industry This work was supported by the Steno Partner Collaboration Unit, Gødstrup Hospital, Herning, Denmark. Drs. Winther, Schmidt, and Bøttcher have received institutional research grant support from Acarix. Dr. Schmidt is a part-time consultant for Acarix. Dr. Schmidt is a minor shareholder of Acarix. Dr. Hoffmann has received institutional research grants on behalf of Massachusetts General Hospital, outside of the submitted work, from KOWA, MedImmune, AstraZeneca, and HeartFlow; and has received consultant fees from DCRI and Recor, outside of the scope of the submitted work. Dr. Wijns has received research grants and honoraria from MicroPort. Dr. Christiansen has served on the Advisory Board for Novo Nordisk. Dr. Saraste has received speaker fees from AstraZeneca, Amgen, Bayer, Novartis, and Abbott; and has served on the Advisory Board for AstraZeneca and Amgen, outside of the submitted work. Dr. Bøttcher has served on the Advisory Board for Novo Nordisk, AstraZeneca, Bayer, Sanofi, and Acarix, outside of submitted work. Dr. Knuuti has received speaker fees from GE Healthcare, Merck, Lundbeck, and Bayer; and has received study protocol consultant fees from GE Healthcare and AstraZeneca, outside of the submitted work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.<br /> (Copyright © 2020 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

Details

Language :
English
ISSN :
1558-3597
Volume :
76
Issue :
21
Database :
MEDLINE
Journal :
Journal of the American College of Cardiology
Publication Type :
Academic Journal
Accession number :
33213720
Full Text :
https://doi.org/10.1016/j.jacc.2020.09.585