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

COVIDSurg Collaborative, Alf Dorian Binder

Research output: Journal article (peer-reviewed)Journal article

18 Citations (Scopus)

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.

Original languageEnglish
Article numberznab183
Pages (from-to)1274-1292
Number of pages19
JournalBritish Journal of Surgery
Volume108
Issue number11
DOIs
Publication statusPublished - 01 Jan 2021

Keywords

  • COVID-19/mortality
  • Cohort Studies
  • Datasets as Topic
  • Humans
  • Machine Learning
  • Models, Statistical
  • Risk Assessment
  • SARS-CoV-2
  • Surgical Procedures, Operative/mortality

ASJC Scopus subject areas

  • General Medicine

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