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

Bravo, Laura; Nepogodiev, Dmitri; Glasbey, James C.; Li, Elizabeth; Simoes, Joana F. F.; Kamarajah, Sivesh K.; Picciochi, Maria; Abbott, Tom E. F.; Ademuyiwa, Adesoji O.; Arnaud, Alexis P.; Agarwal, Arnav; Brar, Amanpreet; Elhadi, Muhammed; Mazingi, Dennis; Cardoso, Victor Roth; Lawday, Samuel; Sayyed, Raza; Omar, Omar M.; Ramos de la Madina, Antonio; Slater, Luke; Venn, Mary; Gkoutos, Georgios; Bhangu, Aneel; Karwath, Andreas; Siaw-Acheampong, Kwabena; Argus, Leah; Chaudhry, Daoud; Dawson, Brett E.; Glasbey, James C.; Gujjuri, Rohan R.; Jones, Conor S.; Khatri, Chetan; Keatley, James M.; Mann, Harvinder; Marson, Ella J.; Mclean, Kenneth A.; Taylor, Elliott H.; Tiwari, Abhinav; Simoes, Joana F. F.; Trout, Isobel M.; Venn, Mary L.; Wilkin, Richard J. W.; Dajti, Irida; Gjata, Arben; Boccalatte, Luis; Marta Modolo, Maria; Cox, Daniel; Pockney, Peter; Townend, Philip; Aigner, Felix; Kronberger, Irmgard; Hossain, Kamral; VanRamshorst, Gabrielle; Lawani, Ismail; Ataide, Gustavo; Baiocchi, Glauco; Buarque, Igor; Gohar, Muhammad; Slavchev, Mihail; Agarwal, Arnav; Martin, Janet; Olivos, Maricarmen; Calvache, Jose; Perez Rivera, Carlos Jose; Hadzibegovic, Ana Danic; Kopjar, Tomislav; Mihanovic, Jakov; Klat, Jaroslav; Novysedlak, Rene; Christensen, Peter; El-Hussuna, Alaa; Batista, Sylvia; Lincango, Eddy; Emile, Sameh H.; Mengesha, Mengistu Gebreyohanes; Hailu, Samuel; Tamiru, Hailu; Kauppila, Joonas; Laukkarinen, Johanna; Arnaud, Alexis; Albertsmeiers, Markus; Lederhuber, Hans; Loffler, Markus; Tabiri, Stephen; Metallidis, Symeon; Tsoulfas, Georgios; Aguilera Lorena, Maria; Grecinos, Gustavo; Mersich, Tamas; Wettstein, Daniel; Ghosh, Dhruv; Kembuan, Gabriele; Brouk, Peiman; Khosravi, Mohammad; Mozafari, Masoud; Adil, Ahmed; Mohan, Helen M.; Zmora, Oded; Fiore, Marco; Gallo, Gaetano; Pata, Francesco; Pellino, Gianluca; Satoi, Sohei; Ayasra, Faris; Chaar, Mohammad; Fakhradiyev, Ildar R.; Jamal, Mohammad; Gulla, Aiste; Roslani, April; Martinez, Laura; Ramos De La Medina, Antonio; Outani, Oumaima; Jonker, Pascal; Kruijff, Schelto; Noltes, Milou; Steinkamp, Pieter; Plas, Willemijn van der; Ademuyiwa, Adesoji; Osinaike, Babatunde; Seyiolajide, Justina; Williams, Emmanuel; Pejkova, Sofija; Augestad, Knut Magne; Soreide, Kjetil; Al Balushi, Zainab; Qureshi, Ahmad; Daraghmeh, Mustafa Abu Mohsen; Abukhalaf, Sadi; Cukier, Moises; Gomez, Hugo; Shu, Sebastian; Vasquez, Ximena; Dione Parreno-Sacdalan, Marie; Major, Piotr; Azevedo, Jose; Cunha, Miguel; Santos, Irene; Zarour, Ahmad; Bonci, Eduard-Alexandru; Negoi, Ionut; Efetov, Sergey; Litvin, Andrey; Ntirenganya, Faustin; Al Ameer, Ehab; Radenkovic, Dejan; Xiang, Frederick Koh Hong; Hoe, Chew Min; Yong, James Ngu Chi and Moore, Rachel (2021): Y Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2: the COVIDSurg mortality score. In: British Journal of Surgery, Vol. 108, No. 11: pp. 1274-1292

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.

• Item Type: Journal article
• Faculties: Medicine
• Subjects: 600 Technology > 610 Medicine and health
• ISSN: 0007-1323
• Language: English