Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score.
dc.contributor.author | COVIDSurg Collaborative | |
dc.date.accessioned | 2022-03-20T02:01:48Z | |
dc.date.available | 2022-03-20T02:01:48Z | |
dc.date.issued | 2021-11 | |
dc.date.updated | 2022-03-20T02:01:48Z | |
dc.description.abstract | <jats:p>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.</jats:p> | |
dc.identifier | 6316029 | |
dc.identifier.issn | 0007-1323 | |
dc.identifier.issn | 1365-2168 | |
dc.identifier.uri | ||
dc.language | eng | |
dc.publisher | Oxford University Press (OUP) | |
dc.relation.ispartof | The British journal of surgery | |
dc.relation.isversionof | 10.1093/bjs/znab183 | |
dc.subject | COVIDSurg Collaborative | |
dc.subject | Humans | |
dc.subject | Surgical Procedures, Operative | |
dc.subject | Models, Statistical | |
dc.subject | Risk Assessment | |
dc.subject | Cohort Studies | |
dc.subject | Datasets as Topic | |
dc.subject | Machine Learning | |
dc.subject | COVID-19 | |
dc.subject | SARS-CoV-2 | |
dc.title | Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score. | |
dc.type | Journal article | |
pubs.begin-page | 1274 | |
pubs.end-page | 1292 | |
pubs.issue | 11 | |
pubs.organisational-group | Duke | |
pubs.organisational-group | School of Medicine | |
pubs.organisational-group | Staff | |
pubs.organisational-group | Clinical Science Departments | |
pubs.organisational-group | Orthopaedics | |
pubs.organisational-group | Surgery | |
pubs.publication-status | Published | |
pubs.volume | 108 |
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