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

COVIDSurg Collaborative, Alf Dorian Binder

Publikation: Beitrag in Fachzeitschrift (peer-reviewed)Artikel in Fachzeitschrift

16 Zitate (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.

OriginalspracheEnglisch
Aufsatznummerznab183
Seiten (von - bis)1274-1292
Seitenumfang19
FachzeitschriftBritish Journal of Surgery
Jahrgang108
Ausgabenummer11
DOIs
PublikationsstatusVeröffentlicht - 01 Jan. 2021

ASJC Scopus Sachgebiete

  • Allgemeine Medizin

Fingerprint

Untersuchen Sie die Forschungsthemen von „Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren