Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score


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Dajti I., Valenzuela J., Boccalatte L. A. , Gemelli N. A. , Smith D. E. , Dudi-Venkata N. N. , ...More

BRITISH JOURNAL OF SURGERY, vol.108, no.11, pp.1274-1292, 2021 (Peer-Reviewed Journal) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 108 Issue: 11
  • Publication Date: 2021
  • Doi Number: 10.1093/bjs/znab183
  • Journal Name: BRITISH JOURNAL OF SURGERY
  • Journal Indexes: Science Citation Index Expanded, Scopus, Academic Search Premier, Abstracts in Social Gerontology, CAB Abstracts, EMBASE, MEDLINE
  • Page Numbers: pp.1274-1292

Abstract

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.