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Interobserver variability in the classification of congenital coronary abnormalities: A substudy of the anomalous connections of the coronary arteries registry

Athanasios Koutsoukis1, Xavier Halna du Fretay2, Patrick Dupouy3, Phalla Ou4, Jean-Pierre Laissy4, Jean-Michel Juliard5, Fabien Hyafil6, Pierre Aubry5

1 Department of Cardiology, Guy’s and St. Thomas’ NHS Foundation Trust, London, United Kingdom
2 Department of Cardiology, Foch Hospital, Suresnes, France
3 Interventional Imaging Cardiovascular Unit, Hôpital Privé d’Antony, Antony, France
4 Department of Radiology, Bichat-Claude Bernard Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France
5 Department of Cardiology, Bichat-Claude Bernard Hospital, Assistance Publique-Hôpitaux de Paris, Département Hospitalo- Universitaire FIRE, Université Paris Diderot Sorbonne Paris-Cité, Paris, France
6 Department of Nuclear Medicine, BichatClaude Bernard Hospital, Assistance Publique-Hôpitaux de Paris, Paris, France

* Corresponding Author: Dr Pierre Aubry, Département de Cardiologie, Groupe Hospitalier BichatClaude Bernard, 46 rue Huchard, 75018 Paris, France. Email: email

Congenital Heart Disease 2017, 12(6), 726-732. https://doi.org/10.1111/chd.12504

Abstract

Objective: The diagnosis of anomalous connections of the coronary arteries (ANOCOR) requires an appropriate identification for the management of the patients involved. We studied the observer variability in the description and classification of ANOCOR between a nonexpert group of physicians and a group of expert physicians, using the ANOCOR cohort.
Patients and design: Consecutive patients identified by 71 referring cardiologists were included in the ANOCOR cohort. Anomalous connection was diagnosed by invasive and/or computed tomography coronary angiography. Angiographic images were reviewed by an angiographic committee with experience in this field. Both investigators and angiographic committee filled out a questionnaire to classify each anomaly with the type of coronary artery involved, the site of anomalous connection, and the initial course. Observer variability between investigators and angiographic committee was assessed by К statistics. Anomalous connection with a preaortic course was defined as at-risk.
Results: Among 472 patients of the ANOCOR cohort, 496 abnormalities were identified with a preaortic course present in 31%. The agreement for the type of artery was excellent (К = 0.92, 95% CI = 0.86-0.98, P < .05), while the agreement for the site of anomalous connection was moderate (К = 0.50, 95% CI = 0.42-0.58, P < .05), and the agreement for the initial course was only fair (К = 0.32, 95% CI = 0.28-0.37, P < .05). Observer agreement for the identification of at-risk forms was moderate (К = 0.497, 95% CI = 0.40-0.59, P< .05).
Conclusions: Observer variability in the assessment of anomalous connection of the coronary arteries between nonexperienced and experienced physicians can be significant. We found that expert physicians provide a more robust classification in comparison with nonexpert physicians. Therefore, referral to physicians with a relevant experience should be considered, especially if an anomaly at-risk is suspected.

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APA Style
Koutsoukis, A., Fretay, X.H.D., Dupouy, P., Ou, P., Laissy, J. et al. (2017). Interobserver variability in the classification of congenital coronary abnormalities: A substudy of the anomalous connections of the coronary arteries registry. Congenital Heart Disease, 12(6), 726-732. https://doi.org/10.1111/chd.12504
Vancouver Style
Koutsoukis A, Fretay XHD, Dupouy P, Ou P, Laissy J, Juliard J, et al. Interobserver variability in the classification of congenital coronary abnormalities: A substudy of the anomalous connections of the coronary arteries registry. Congeni Heart Dis. 2017;12(6):726-732 https://doi.org/10.1111/chd.12504
IEEE Style
A. Koutsoukis et al., “Interobserver variability in the classification of congenital coronary abnormalities: A substudy of the anomalous connections of the coronary arteries registry,” Congeni. Heart Dis., vol. 12, no. 6, pp. 726-732, 2017. https://doi.org/10.1111/chd.12504



cc Copyright © 2017 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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