Literature DB >> 29301713

The Coronary Artery Disease-Reporting and Data System (CAD-RADS): Prognostic and Clinical Implications Associated With Standardized Coronary Computed Tomography Angiography Reporting.

Joe X Xie1, Ricardo C Cury2, Jonathon Leipsic3, Matthew T Crim1, Daniel S Berman4, Heidi Gransar4, Matthew J Budoff5, Stephan Achenbach6, Bríain Ó Hartaigh7, Tracy Q Callister8, Hugo Marques9, Ronen Rubinshtein10, Mouaz H Al-Mallah11, Daniele Andreini12, Gianluca Pontone12, Filippo Cademartiri13, Erica Maffei13, Kavitha Chinnaiyan14, Gilbert Raff14, Martin Hadamitzky15, Joerg Hausleiter16, Gudrun Feuchtner17, Allison Dunning18, Augustin DeLago19, Yong-Jin Kim20, Philipp A Kaufmann21, Todd C Villines22, Benjamin J W Chow23, Niree Hindoyan7, Millie Gomez7, Fay Y Lin7, Erica Jones7, James K Min7, Leslee J Shaw24.   

Abstract

OBJECTIVES: This study sought to assess clinical outcomes associated with the novel Coronary Artery Disease-Reporting and Data System (CAD-RADS) scores used to standardize coronary computed tomography angiography (CTA) reporting and their potential utility in guiding post-coronary CTA care.
BACKGROUND: Clinical decision support is a major focus of health care policies aimed at improving guideline-directed care. Recently, CAD-RADS was developed to standardize coronary CTA reporting and includes clinical recommendations to facilitate patient management after coronary CTA.
METHODS: In the multinational CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry, 5,039 patients without known coronary artery disease (CAD) underwent coronary CTA and were stratified by CAD-RADS scores, which rank CAD stenosis severity as 0 (0%), 1 (1% to 24%), 2 (25% to 49%), 3 (50% to 69%), 4A (70% to 99% in 1 to 2 vessels), 4B (70% to 99% in 3 vessels or ≥50% left main), or 5 (100%). Kaplan-Meier and multivariable Cox models were used to estimate all-cause mortality or myocardial infarction (MI). Receiver-operating characteristic (ROC) curves were used to compare CAD-RADS to the Duke CAD Index and traditional CAD classification. Referrals to invasive coronary angiography (ICA) after coronary CTA were also assessed.
RESULTS: Cumulative 5-year event-free survival ranged from 95.2% to 69.3% for CAD-RADS 0 to 5 (p < 0.0001). Higher scores were associated with elevations in event risk (hazard ratio: 2.46 to 6.09; p < 0.0001). The ROC curve for prediction of death or MI was 0.7052 for CAD-RADS, which was noninferior to the Duke Index (0.7073; p = 0.893) and traditional CAD classification (0.7095; p = 0.783). ICA rates were 13% for CAD-RADS 0 to 2, 66% for CAD-RADS 3, and 84% for CAD-RADS ≥4A. For CAD-RADS 3, 58% of all catheterizations occurred within the first 30 days of follow-up. In a patient subset with available medication data, 57% of CAD-RADS 3 patients who received 30-day ICA were either asymptomatic or not receiving antianginal therapy at baseline, whereas only 32% had angina and were receiving medical therapy.
CONCLUSIONS: CAD-RADS effectively identified patients at risk for adverse events. Frequent ICA use was observed among patients without severe CAD, many of whom were asymptomatic or not taking antianginal drugs. Incorporating CAD-RADS into coronary CTA reports may provide a novel opportunity to promote evidence-based care post-coronary CTA.
Copyright © 2018 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  appropriate use; clinical decision support; coronary computed tomography angiography; prognosis

Mesh:

Year:  2018        PMID: 29301713     DOI: 10.1016/j.jcmg.2017.08.026

Source DB:  PubMed          Journal:  JACC Cardiovasc Imaging        ISSN: 1876-7591


  22 in total

1.  Invasive coronary angiography findings across the CAD-RADS classification spectrum.

Authors:  Gaston A Rodriguez-Granillo; Patricia Carrascosa; Alejandro Goldsmit; Armin Arbab-Zadeh
Journal:  Int J Cardiovasc Imaging       Date:  2019-06-21       Impact factor: 2.357

Review 2.  Emerging Role of Coronary Computed Tomography Angiography in Lipid-Lowering Therapy: a Bridge to Image-Guided Personalized Medicine.

Authors:  Toru Miyoshi; Kazuhiro Osawa; Keishi Ichikawa; Kazuki Suruga; Takashi Miki; Masashi Yoshida; Koji Nakagawa; Hironobu Toda; Kazufumi Nakamura; Hiroshi Morita; Hiroshi Ito
Journal:  Curr Cardiol Rep       Date:  2019-06-21       Impact factor: 2.931

3.  The need for standardization of nuclear cardiology reporting and data system (NCAD-RADS): Learning from coronary artery disease (CAD), breast imaging (BI), liver imaging (LI), and prostate imaging (PI) RADS.

Authors:  Majid Assadi; Erik Velez; Mohammad Hosein Najafi; Ali Gholamrezanezhad
Journal:  J Nucl Cardiol       Date:  2018-10-29       Impact factor: 5.952

4.  Influence of diabetes mellitus on the diagnostic performance of machine learning-based coronary CT angiography-derived fractional flow reserve: a multicenter study.

Authors:  Yi Xue; Min Wen Zheng; Yang Hou; Fan Zhou; Jian Hua Li; Yi Ning Wang; Chun Yu Liu; Chang Sheng Zhou; Jia Yin Zhang; Meng Meng Yu; Bo Zhang; Dai Min Zhang; Yan Yi; Lei Xu; Xiu Hua Hu; Guang Ming Lu; Chun Xiang Tang; Long Jiang Zhang
Journal:  Eur Radiol       Date:  2022-01-12       Impact factor: 5.315

5.  Risk stratification in coronary artery disease using NH3-PET myocardial flow reserve and CAD-RADS on coronary CT angiography.

Authors:  Atsushi Yamamoto; Michinobu Nagao; Kiyoe Ando; Risako Nakao; Kenji Fukushima; Yuka Matsuo; Mitsuru Momose; Shuji Sakai; Nobuhisa Hagiwara
Journal:  Int J Cardiovasc Imaging       Date:  2021-06-11       Impact factor: 2.357

6.  Prognostic Value of Coronary CTA in Stable Chest Pain: CAD-RADS, CAC, and Cardiovascular Events in PROMISE.

Authors:  Daniel O Bittner; Thomas Mayrhofer; Matt Budoff; Balint Szilveszter; Borek Foldyna; Travis R Hallett; Alexander Ivanov; Sumbal Janjua; Nandini M Meyersohn; Pedro V Staziaki; Stephan Achenbach; Maros Ferencik; Pamela S Douglas; Udo Hoffmann; Michael T Lu
Journal:  JACC Cardiovasc Imaging       Date:  2019-11-13

7.  [Radiological imaging to assess individual cardiovascular risk].

Authors:  A D Ordu; K Rippel; L T Garthe; C Scheurig-Münkler; T Kröncke; F Schwarz
Journal:  Radiologe       Date:  2019-01       Impact factor: 0.635

8.  Coronary Artery Disease Reporting and Data System (CAD-RADS) Adoption: Analysis of Local Trends in a Large Academic Medical Center.

Authors:  Angelo K Takigami; Vikas Thondapu; Reece J Goiffon; Jena Depetris; Sumit Gupta; Sherief Garrana; Veniamin Knyazev; Albree Tower-Rader; Michael T Lu; Nandini Meyersohn; Udo Hoffmann; Sandeep Hedgire; Brian Ghoshhajra
Journal:  Radiol Cardiothorac Imaging       Date:  2021-06-24

Review 9.  SCCT 2021 Expert Consensus Document on Coronary Computed Tomographic Angiography: A Report of the Society of Cardiovascular Computed Tomography.

Authors:  Jagat Narula; Y Chandrashekhar; Amir Ahmadi; Suhny Abbara; Daniel S Berman; Ron Blankstein; Jonathon Leipsic; David Newby; Edward D Nicol; Koen Nieman; Leslee Shaw; Todd C Villines; Michelle Williams; Harvey S Hecht
Journal:  J Cardiovasc Comput Tomogr       Date:  2020-11-20

10.  The correlation of deep learning-based CAD-RADS evaluated by coronary computed tomography angiography with breast arterial calcification on mammography.

Authors:  Zengfa Huang; Jianwei Xiao; Yuanliang Xie; Yun Hu; Shutong Zhang; Xiang Li; Zheng Wang; Zuoqin Li; Xiang Wang
Journal:  Sci Rep       Date:  2020-07-13       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.