4.6 Article

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

期刊

BRITISH JOURNAL OF SURGERY
卷 108, 期 11, 页码 1274-1292

出版社

OXFORD UNIV PRESS
DOI: 10.1093/bjs/znab183

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  1. National Institute for Health Research (NIHR) Global Health Research Unit [NIHR 16.136.79]
  2. Association of Coloproctology of Great Britain and Ireland
  3. Bowel AMP
  4. Cancer Research
  5. Bowel Research UK
  6. Association of Upper Gastrointestinal Surgeons
  7. British Association of Surgical Oncology
  8. British Gynaecological Cancer Society
  9. European Society of Coloproctology
  10. Medtronic
  11. NIHR Academy
  12. Urology Foundation
  13. Sarcoma UK
  14. Vascular Society for Great Britain and Ireland
  15. Yorkshire Cancer Research
  16. MRC Health Data Research UK by UK Research and Innovation, Department of Health and Social Care (England) [HDRUK/CFC/01]
  17. Wellcome Trust [215182/Z/19/Z]

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The study analyzed data from 8492 patients in 69 countries to develop the COVIDsurg Mortality Score, demonstrating the safety of restarting a wide range of surgical services for selected patients.
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.

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