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Dajti, I;
Valenzuela, J I;
Boccalatte, L A;
Gemelli, N A;
Smith, D E;
Dudi-Venkata, N N;
Kroon, H M;
Sammour, T;
Roberts, M;
Mitchell, D;
Lah, K;
Pearce, A;
Morton, A;
Dawson, A C;
Drane, A;
Sharpin, C;
Nataraja, R M;
Pacilli, M;
Cox, D R A;
Muralidharan, V;
Riddiough, G E;
Clarke, E M;
Jamel, W;
Qin, K R;
[...]
Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
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- Medientyp: E-Artikel
- Titel: Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
- Beteiligte: Dajti, I; Valenzuela, J I; Boccalatte, L A; Gemelli, N A; Smith, D E; Dudi-Venkata, N N; Kroon, H M; Sammour, T; Roberts, M; Mitchell, D; Lah, K; Pearce, A; Morton, A; Dawson, A C; Drane, A; Sharpin, C; Nataraja, R M; Pacilli, M; Cox, D R A; Muralidharan, V; Riddiough, G E; Clarke, E M; Jamel, W; Qin, K R; [...]
- Erschienen: Oxford University Press (OUP), 2021
- Erschienen in: British Journal of Surgery
- Sprache: Englisch
- DOI: 10.1093/bjs/znab183
- ISSN: 0007-1323; 1365-2168
- Schlagwörter: Surgery
- Entstehung:
- Anmerkungen:
- Beschreibung: <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>