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

Overview

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.

publication date

  • November 11, 2021

Research

keywords

  • COVID-19
  • Models, Statistical
  • Risk Assessment
  • Surgical Procedures, Operative

Identity

PubMed Central ID

  • PMC8344569

Scopus Document Identifier

  • 85121964505

Digital Object Identifier (DOI)

  • 10.1093/bjs/znaa012

PubMed ID

  • 34227657

Additional Document Info

volume

  • 108

issue

  • 11