Dey, Damini
Gaur, Sara
Ovrehus, Kristian A.
Slomka, Piotr J.
Betancur, Julian
Goeller, Markus
Hell, Michaela M.
Gransar, Heidi
Berman, Daniel S.
Achenbach, Stephan
Botker, Hans Erik
Jensen, Jesper Moller
Lassen, Jens Flensted
Norgaard, Bjarne Linde
Funding for this research was provided by:
National Heart, Lung, and Blood Institute (R01HL133616)
Bundesministerium für Bildung und Forschung (01EX1012B)
Article History
Received: 23 September 2017
Revised: 20 November 2017
Accepted: 29 November 2017
First Online: 19 January 2018
Compliance with ethical standards
:
: The scientific guarantor of this publication is Dr. Damini Dey (Associate Professor, Cedars-Sinai Medical Center).
: The authors of this manuscript declare relationships with the following companies: None.Dr. Piotr Slomka, Dr. Daniel S Berman and Dr. Damini Dey received software royalties from Cedars-Sinai Medical Center and hold a patent.
: One of the co-authors (Heidi Gransar, MS) is an experienced biostatistician and she provided her expertise for this study.
: Written informed consent was obtained from all subjects (patients) in this study.
: Institutional review board approval was obtained.
: This study is a new post hoc analysis comprising all 254 patients from the prospective, multicentre NXT trial (NCT01757678). The original study has been previously described (Norgaard et al. J Am Coll Cardiology 2014 [21]). While the patient cohort is the same, there was no overlap with this study which evaluates objective machine learning integration of quantitative coronary CT angiography to predict ischaemia.
: <i>•</i> prospective study<i>•</i> post hoc analysis<i>•</i> multicentre study