Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients
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Published:2021-01-27
Issue:1
Volume:12
Page:
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ISSN:2041-1723
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Container-title:Nature Communications
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language:en
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Short-container-title:Nat Commun
Author:
Lassau Nathalie, Ammari Samy, Chouzenoux EmilieORCID, Gortais Hugo, Herent PaulORCID, Devilder MatthieuORCID, Soliman Samer, Meyrignac OlivierORCID, Talabard Marie-Pauline, Lamarque Jean-Philippe, Dubois Remy, Loiseau Nicolas, Trichelair Paul, Bendjebbar Etienne, Garcia Gabriel, Balleyguier Corinne, Merad Mansouria, Stoclin Annabelle, Jegou Simon, Griscelli Franck, Tetelboum Nicolas, Li Yingping, Verma SagarORCID, Terris Matthieu, Dardouri Tasnim, Gupta Kavya, Neacsu Ana, Chemouni Frank, Sefta Meriem, Jehanno Paul, Bousaid Imad, Boursin YannickORCID, Planchet Emmanuel, Azoulay Mikael, Dachary Jocelyn, Brulport Fabien, Gonzalez Adrian, Dehaene Olivier, Schiratti Jean-Baptiste, Schutte Kathryn, Pesquet Jean-Christophe, Talbot Hugues, Pronier Elodie, Wainrib Gilles, Clozel ThomasORCID, Barlesi Fabrice, Bellin Marie-France, Blum Michael G. B.ORCID
Abstract
AbstractThe SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from two French hospitals. We train a deep learning model based on CT scans to predict severity. We then construct the multimodal AI-severity score that includes 5 clinical and biological variables (age, sex, oxygenation, urea, platelet) in addition to the deep learning model. We show that neural network analysis of CT-scans brings unique prognosis information, although it is correlated with other markers of severity (oxygenation, LDH, and CRP) explaining the measurable but limited 0.03 increase of AUC obtained when adding CT-scan information to clinical variables. Here, we show that when comparing AI-severity with 11 existing severity scores, we find significantly improved prognosis performance; AI-severity can therefore rapidly become a reference scoring approach.
Publisher
Springer Science and Business Media LLC
Subject
General Physics and Astronomy,General Biochemistry, Genetics and Molecular Biology,General Chemistry
Reference68 articles.
1. Myers, L. C., Parodi, S. M., Escobar, G. J. & Liu, V. X. Characteristics of hospitalized adults with COVID-19 in an integrated health care system in California. JAMA (2020) https://doi.org/10.1001/jama.2020.7202. 2. Docherty, A. B. et al. Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study. BMJ 369, m1985 (2020). 3. Richardson, S. et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City Area. JAMA (2020) https://doi.org/10.1001/jama.2020.6775. 4. Wu, C. et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern. Med. (2020) https://doi.org/10.1001/jamainternmed.2020.0994. 5. Phua, J. et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations. Lancet Respir. Med. 8, 506–517 (2020).
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