dc.contributor.author | RUBIO-PALAU, JOSEP | |
dc.contributor.author | COVIDSurg Collaborative | |
dc.date.accessioned | 2022-10-21T07:48:37Z | |
dc.date.available | 2022-10-21T07:48:37Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | COVIDSurg Collaborative. Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score. British Journal of Surgery, 2021, 108(11), p. 1274-1292. Disponible en: <https://academic.oup.com/bjs/article/108/11/1274/6316029>. Fecha de acceso: 21 oct. 2022. DOI: 10.1093/bjs/znab183 | ca |
dc.identifier.issn | 0007-1323 | ca |
dc.identifier.uri | http://hdl.handle.net/20.500.12328/3462 | |
dc.description.abstract | Since the beginning of the COVID-19 pandemic tens of millions of operations have been cancelled1 as a result of excessive postoperative pulmonary complications (51.2 per cent) and mortality rates (23.8 per cent) in patients with perioperative SARS-CoV-2 infection2. There is an urgent need to restart surgery safely in order to minimize the impact of untreated non-communicable disease. As rates of SARS-CoV-2 infection in elective surgery patients range from 1–9 per cent3–8, vaccination is expected to take years to implement globally9 and preoperative screening is likely to lead to increasing numbers of SARS-CoV-2-positive patients, perioperative SARS-CoV-2 infection will remain a challenge for the foreseeable future. To inform consent and shared decision-making, a robust, globally applicable score is needed to predict individualized mortality risk for patients with perioperative SARS-CoV-2 infection. The authors aimed to develop and validate a machine learning-based risk score to predict postoperative mortality risk in patients with perioperative SARS-CoV-2 infection. | en |
dc.format.extent | 19 | ca |
dc.language.iso | eng | ca |
dc.publisher | Oxford University Press | ca |
dc.relation.ispartof | British Journal of Surgery | ca |
dc.relation.ispartofseries | 108 | |
dc.relation.uri | https://academic.oup.com/bjs/article/108/11/1274/6316029 | ca |
dc.rights | © 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. | en |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject.other | Cures perioperatòries | ca |
dc.subject.other | Procediments quirúrgics | ca |
dc.subject.other | Operatius | ca |
dc.subject.other | Mortalitat | ca |
dc.subject.other | Aprenentatge automàtic | ca |
dc.subject.other | Sars-cov-2 | ca |
dc.subject.other | Cuidado perioperatorio | es |
dc.subject.other | Procedimientos quirúrgicos | es |
dc.subject.other | Operativo | es |
dc.subject.other | Mortalidad | es |
dc.subject.other | Aprendizaje automático | es |
dc.subject.other | Sars-cov-2 | es |
dc.subject.other | Perioperative care | en |
dc.subject.other | Surgical procedures | en |
dc.subject.other | Operative | en |
dc.subject.other | Mortality | en |
dc.subject.other | Machine learning | en |
dc.subject.other | Sars-cov-2 | en |
dc.title | Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score | en |
dc.type | info:eu-repo/semantics/article | ca |
dc.description.version | info:eu-repo/semantics/publishedVersion | ca |
dc.rights.accessLevel | info:eu-repo/semantics/openAccess | |
dc.embargo.terms | cap | ca |
dc.subject.udc | 61 | ca |
dc.subject.udc | 616.9 | ca |
dc.identifier.doi | https://dx.doi.org/10.1093/bjs/znab183 | ca |