Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
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.
COVID-19/mortality, Cohort Studies, Datasets as Topic, Humans, Machine Learning, Models, Statistical, Risk Assessment, SARS-CoV-2, Surgical Procedures, Operative/mortality
1274-1292
Hamady, Zaed Z.R.
545a1c81-276e-4341-a420-aa10aa5d8ca8
Hamady, Zaed Z.R.
545a1c81-276e-4341-a420-aa10aa5d8ca8
COVIDSurg Collaborative
(2021)
Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score.
The British journal of surgery, 108 (11), .
(doi:10.1093/bjs/znab183).
Abstract
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.
Text
znab183
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More information
Accepted/In Press date: 26 April 2021
e-pub ahead of print date: 6 July 2021
Keywords:
COVID-19/mortality, Cohort Studies, Datasets as Topic, Humans, Machine Learning, Models, Statistical, Risk Assessment, SARS-CoV-2, Surgical Procedures, Operative/mortality
Identifiers
Local EPrints ID: 485359
URI: http://eprints.soton.ac.uk/id/eprint/485359
ISSN: 0007-1323
PURE UUID: 4e12d605-18a5-4717-9e32-336134496073
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Date deposited: 05 Dec 2023 17:36
Last modified: 18 Mar 2024 04:05
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Author:
Zaed Z.R. Hamady
Corporate Author: COVIDSurg Collaborative
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