> Details

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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  • Media type: E-Article
  • Title: Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
  • Contributor: 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; [...]
  • imprint: Oxford University Press (OUP), 2021
  • Published in: British Journal of Surgery
  • Language: English
  • DOI: 10.1093/bjs/znab183
  • ISSN: 0007-1323; 1365-2168
  • Keywords: Surgery
  • Origination:
  • Footnote:
  • Description: <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>