: 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.
Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score / Bravo, L., Nepogodiev, D., Glasbey, J.c., Li, E., Simoes, J., Kamarajah, S.k., Picciochi, M., Abbott, T., Ademuyiwa, A.o., Arnaud, A.p., Agarwal, A., Brar, A., Elhadi, M., Mazingi, D., Cardoso, V.r., Lawday, S., Sayyed, R., Omar, O.m., De La Madina, A.r., Slater, L., et al.. - In: BRITISH JOURNAL OF SURGERY. - ISSN 0007-1323. - 108:11(2021), pp. znab183.1274-znab183.1292. [10.1093/bjs/znab183]
Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score
Annicchiarico AMembro del Collaboration Group
;
2021-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
