A simple coronary CT angiography-based jeopardy score for the identification of extensive coronary artery disease: Validation against invasive coronary angiography.

Coronary CTA Coronary artery disease Invasive coronary angiography Jeopardy score Validation study

Journal

Diagnostic and interventional imaging
ISSN: 2211-5684
Titre abrégé: Diagn Interv Imaging
Pays: France
ID NLM: 101568499

Informations de publication

Date de publication:
24 Nov 2023
Historique:
received: 22 08 2023
revised: 03 11 2023
accepted: 08 11 2023
medline: 26 11 2023
pubmed: 26 11 2023
entrez: 25 11 2023
Statut: aheadofprint

Résumé

The invasive British Cardiovascular Intervention Society Jeopardy Score (iBCIS-JS) is a simple angiographic scoring system, enabling quantification of the extent of jeopardized myocardium related to clinically significant coronary artery disease (CAD). The purpose of this study was to develop and validate the coronary CT angiography-based BCIS-JS (CT-BCIS-JS) against the iBCIS-JS in patients with suspected or stable CAD. Patients who underwent coronary CT angiography followed by invasive coronary angiography, within 90 days were retrospectively included. CT-BCIS-JS and iBCIS-JS were calculated, with a score ≥ 6 indicating extensive CAD. Correlation between the CT-BCIS-JS and iBCIS-JS was searched for using Spearman's coefficient, and agreement with weighted Kappa (κ) analyses. A total of 122 patients were included. There were 102 men and 20 women with a median age of 62 years (Q1, Q3: 54, 68; age range: 19-83 years). No differences in median CT-BCIS-JS (4; Q1, Q3: 0, 8) and median iBCIS-JS (4; Q1, Q3: 0, 8) were found (P = 0.18). Extensive CAD was identified in 53 (43.4%) and 52 (42.6%) patients using CT-BCIS-JS and iBCIS-JS, respectively (P = 0.88). CT-based and iBCIS-JS showed excellent correlation (r = 0.98; P < 0.001) and almost perfect agreement (κ = 0.93; 95% confidence interval: 0.90-0.97). Agreement for identification of an iBCIS-JS ≥ 6 was almost perfect (κ = 0.94; 95 % confidence interval: 0.87-0.99). The CT-BCIS-JS represents a feasible, and accurate method for quantification of CAD, with capabilities not different from those of iBCIS-JS. It enables simple, non-invasive identification of patients with anatomically extensive CAD.

Identifiants

pubmed: 38007373
pii: S2211-5684(23)00217-6
doi: 10.1016/j.diii.2023.11.001
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2023 The Author(s). Published by Elsevier Masson SAS.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest AC has consultancy agreements with Medyria and Nanoflex. DCB reports payments from Amgen, Pfizer and Philips Healthcare, and research support from Philips Healthcare, Spectrum Dynamics and MIM Software Inc. BS has been supported by the H.H. Sheikh Khalifa bin Hamad Al-Thani Research Programme; BS has received grants to the institution from the OPO Foundation, the Iten-Kohaut Foundation, the German Center for Cardiovascular Research (DZHK), the German Heart Research Foundation, the B. Braun Foundation, Boston Scientific, and Edwards Lifesciences. The University Hospital of Zurich holds a research agreement with GE Healthcare. All other authors report no personal conflicts of interests in relation with this study.

Auteurs

Jan A Schaab (JA)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Alessandro Candreva (A)

Department of Cardiology, University Heart Center, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Alexia Rossi (A)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Susanne Markendorf (S)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Dominik Sager (D)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Michael Messerli (M)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Aju P Pazhenkottil (AP)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland; Department of Cardiology, University Heart Center, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Dominik C Benz (DC)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland; Department of Cardiology, University Heart Center, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Philipp A Kaufmann (PA)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Ronny R Buechel (RR)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Barbara E Stähli (BE)

Department of Cardiology, University Heart Center, University Hospital Zurich, CH-8091 Zurich, Switzerland.

Andreas A Giannopoulos (AA)

Department of Nuclear Medicine, Cardiac Imaging, University Hospital Zurich, CH-8091 Zurich, Switzerland. Electronic address: andreas.giannopoulos@usz.ch.

Classifications MeSH