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Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score

  • To support the global restart of elective surgery, data from an international prospective cohort study of 8492 patients (69 countries) was analysed using artificial intelligence (machine learning techniques) to develop a predictive score for mortality in surgical patients with SARS-CoV-2. We found that patient rather than operation factors were the best predictors and used these to create the COVIDsurg Mortality Score (https://covidsurgrisk.app). Our data demonstrates that it is safe to restart a wide range of surgical services for selected patients.

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Author:Laura Bravo, Dmitri Nepogodiev, James C. Glasbey, Elizabeth Li, Joana F. F. Simoes, Sivesh K. Kamarajah, Maria Picciochi, Tom E. F. Abbott, Adesoji O. Ademuyiwa, Alexis P. Arnaud, Arnav Agarwal, Amanpreet Brar, Muhammed Elhadi, Dennis Mazingi, Victor Roth Cardoso, Samuel Lawday, Raza Sayyed, Omar M. Omar, Antonio Ramos de la Madina, Luke Slater, Mary Venn, Georgios Gkoutos, Aneel Bhangu
URN:urn:nbn:de:bvb:384-opus4-1239217
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/123921
ISSN:0007-1323OPAC
ISSN:1365-2168OPAC
Parent Title (English):British Journal of Surgery
Publisher:Oxford University Press (OUP)
Contributor(s):Katharina BeyerGND
Type:Article
Language:English
Year of first Publication:2021
Publishing Institution:Universität Augsburg
Release Date:2025/07/29
Volume:108
Issue:11
First Page:1274
Last Page:1292
Note:
Published on behalf of the CVIDSurg Collaborative. Please see the publisher's website for further details.
DOI:https://doi.org/10.1093/bjs/znab183
Institutes:Medizinische Fakultät
Medizinische Fakultät / Universitätsklinikum
Medizinische Fakultät / Lehrstuhl für Allgemein- und Viszeralchirurgie
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)