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. I., Boccalatte L. A., Gemelli N. A., Smith D. E., Dudi-Venkata N. N., ...Daha Fazla

The British journal of surgery, cilt.108, sa.11, ss.1274-1292, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 108 Sayı: 11
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1093/bjs/znab183
  • Dergi Adı: The British journal of surgery
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Abstracts in Social Gerontology, CAB Abstracts, EMBASE, MEDLINE
  • Sayfa Sayıları: ss.1274-1292
  • İstanbul Üniversitesi Adresli: Evet

Özet

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.