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 t...

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Detalles Bibliográficos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Rapid Research Communications
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8344569/
https://www.ncbi.nlm.nih.gov/pubmed/34227657
http://dx.doi.org/10.1093/bjs/znab183
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collection PubMed
description 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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spelling pubmed-83445692021-08-10 Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score Br J Surg Rapid Research Communications 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. Oxford University Press 2021-07-06 /pmc/articles/PMC8344569/ /pubmed/34227657 http://dx.doi.org/10.1093/bjs/znab183 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of BJS Society Ltd. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Rapid Research Communications
Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
title Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
title_full Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
title_fullStr Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
title_full_unstemmed Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
title_short Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
title_sort machine learning risk prediction of mortality for patients undergoing surgery with perioperative sars-cov-2: the covidsurg mortality score
topic Rapid Research Communications
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8344569/
https://www.ncbi.nlm.nih.gov/pubmed/34227657
http://dx.doi.org/10.1093/bjs/znab183
work_keys_str_mv AT machinelearningriskpredictionofmortalityforpatientsundergoingsurgerywithperioperativesarscov2thecovidsurgmortalityscore

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