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

COVIDSurg Collaborative

doi:10.1093/bjs/znab183

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

COVIDSurg Collaborative

Research output: Contribution to journal › Article › Research › peer-review

23 Citations (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.

Original language	English
Pages (from-to)	1274-1292
Number of pages	19
Journal	British Journal of Surgery
Volume	108
Issue number	11
DOIs	https://doi.org/10.1093/bjs/znab183
Publication status	Published - Nov 2021
Externally published	Yes

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10.1093/bjs/znab183Licence: CC BY

Cite this

@article{88a27aeffa8b430e9945e972f3d18f2f,

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

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. ",

author = "Laura Bravo and Dmitri Nepogodiev and Glasbey, \{James C.\} and Elizabeth Li and Simoes, \{Joana F.F.\} and Kamarajah, \{Sivesh K.\} and Maria Picciochi and Abbott, \{Tom E.F.\} and Ademuyiwa, \{Adesoji O.\} and Arnaud, \{Alexis P.\} and Arnav Agarwal and Amanpreet Brar and Muhammed Elhadi and Dennis Mazingi and Cardoso, \{Victor Roth\} and Samuel Lawday and Raza Sayyed and Omar, \{Omar M.\} and \{de la Madina\}, \{Antonio Ramos\} and Luke Slater and Venn, \{Mary L.\} and Georgios Gkoutos and Aneel Bhangu and Andreas Karwath and Kwabena Siaw-Acheampong and Leah Argus and Daoud Chaudhry and Dawson, \{Brett E.\} and Gujjuri, \{Rohan R.\} and Jones, \{Conor S.\} and Chetan Khatri and Keatley, \{James M.\} and Harvinder Mann and Marson, \{Ella J.\} and Mclean, \{Kenneth A.\} and Taylor, \{Elliott H.\} and Abhinav Tiwari and Trout, \{Isobel M.\} and Wilkin, \{Richard J.W.\} and Irida Dajti and Arben Gjata and Luis Boccalatte and Modolo, \{Maria Marta\} and Daniel Cox and Peter Pockney and Philip Townend and Felix Aigner and Irmgard Kronberger and Kamral Hossain and Gabrielle VanRamshorst and Ismail Lawani and Gustavo Ataide and Glauco Baiocchi and Igor Buarque and Muhammad Gohar and Mihail Slavchev and Janet Martin and Maricarmen Olivos and Jose Calvache and Rivera, \{Carlos Jose Perez\} and Hadzibegovic, \{Ana Danic\} and Tomislav Kopjar and Jakov Mihanovic and Jaroslav Klat and Ren{\'e} Novysedlak and Peter Christensen and Alaa El-Hussuna and Sylvia Batista and Eddy Lincango and Emile, \{Sameh H.\} and Mengesha, \{Mengistu Gebreyohanes\} and Samuel Hailu and Hailu Tamiru and Joonas Kauppila and Johanna Laukkarinen and Markus Albertsmeiers and Hans Lederhuber and Markus Loffler and Stephen Tabiri and Symeon Metallidis and Georgios Tsoulfas and Lorena, \{Maria Aguilera\} and Gustavo Grecinos and Tamas Mersich and Daniel Wettstein and Dhruv Ghosh and Gabriele Kembuan and Peiman Brouk and Mohammad Khosravi and Masoud Mozafari and Ahmed Adil and Mohan, \{Helen M.\} and Oded Zmora and Marco Fiore and Gaetano Gallo and Francesco Pata and Gianluca Pellino and Sohei Satoi and Faris Ayasra and Mohammad Chaar and Fakhradiyev, \{Ildar R.\} and Mohammad Jamal and Aiste Gulla and April Roslani and Laura Martinez and \{De La Medina\}, \{Antonio Ramos\} and Oumaima Outani and Pascal Jonker and Schelto Kruijff and Milou Noltes and Pieter Steinkamp and \{van der Plas\}, Willemijn and Babatunde Osinaike and Justina Seyiolajide and Emmanuel Williams and Sofija Pejkova and Augestad, \{Knut Magne\} and Kjetil Soreide and \{Al Balushi\}, Zainab and Ahmad Qureshi and Daraghmeh, \{Mustafa Abu Mohsen\} and Sadi Abukhalaf and Moises Cukier and Hugo Gomez and Sebastian Shu and Ximena Vasquez and Parreno-Sacdalan, \{Marie Dione\} and Piotr Major and Jos{\'e} Azevedo and Miguel Cunha and Irene Santos and Ahmad Zarour and Bonci, \{Eduard Alexandru\} and Ionut Negoi and Sergey Efetov and Andrey Litvin and Faustin Ntirenganya and \{Al Ameer\}, Ehab and Dejan Radenkovic and Xiang, \{Frederick Koh Hong\} and Hoe, \{Chew Min\} and Yong, \{James Ngu Chi\} and Rachel Moore and Ncamsile Nhlabathi and Colino, \{Ruth Blanco\} and Bravo, \{Ana Minaya\} and Ana Minaya-Bravo and Umesh Jayarajah and Dakshitha Wickramasinghe and Mohammed Elmujtaba and William Jebril and Martin Ruteg{\aa}rd and Malin Sund and Arda Isik and Sezai Leventoǧlu and Ruth Benson and Ed Caruna and Sohini Chakrabortee and Andreas Demetriades and Anant Desai and Drake, \{Thomas D.\} and Edwards, \{John G.\} and Evans, \{Jonathan P.\} and Samuel Ford and Christina Fotopoulou and Ewen Griffiths and Peter Hutchinson and Jenkinson, \{Michael D.\} and Tabassum Khan and Stephen Knight and Angelos Kolias and Elaine Leung and Siobhan McKay and Lisa Norman and Riinu Ots and Vidya Raghavan and Andrew Schache and Richard Shaw and Katie Shaw and Neil Smart and Grant Stewart and Sudha Sundar and Dale Vimalchandran and Naomi Wright and Sattar Alshryda and Osaid Alser and Kerry Breen and Ian Ganly and Haytham Kaafarani and Brittany Kendall and Hassan Mashbari and \{Al Naggar\}, Hamza and Valenzuela, \{J. I.\} and Boccalatte, \{L. A.\} and Gemelli, \{N. A.\} and Smith, \{D. E.\} and Dudi-Venkata, \{N. N.\} and Kroon, \{H. M.\} and T. Sammour and M. Roberts and D. Mitchell and K. Lah and A. Pearce and A. Morton and Dawson, \{A. C.\} and A. Drane and C. Sharpin and Nataraja, \{R. M.\} and M. Pacilli and Cox, \{D. R.A.\} and V. Muralidharan and Riddiough, \{G. E.\} and Clarke, \{E. M.\} and W. Jamel and Qin, \{K. R.\} and D. Cope and N. Egoroff and N. Lott and S. Putnis and \{De Robles\}, S. and Z. Ang and M. Mitteregger and S. Uranitsch and M. Stiegler and G. Seitinger and Lumenta, \{D. B.\} and Nischwitz, \{S. P.\} and E. Richtig and M. Pau and P. Srekl-Filzmaier and N. Eibinger and B. Michelitsch and M. Fediuk and A. Papinutti and G. Seidel and J. Kahn and Cohnert, \{T. U.\} and F. Messner and D. {\"O}fner and J. Presl and M. Varga and M. Weitzendorfer and K. Emmanuel and Binder, \{A. D.\} and M. Zimmermann and S. Holawe and E. Nkenke and C. Grimm and T. Richards and \{COVIDSurg Collaborative\}",

note = "Funding Information: This report was funded by a National Institute for Health Research (NIHR) Global Health Research Unit Grant (NIHR 16.136.79), Association of Coloproctology of Great Britain and Ireland, Bowel \& Cancer Research, Bowel Research UK, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, Medtronic, NIHR Academy, The Urology Foundation, Sarcoma UK, Vascular Society for Great Britain and Ireland, Yorkshire Cancer Research, and the MRC Health Data Research UK (HDRUK/CFC/01), an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations, and leading medical research charities. L.B.M. and G.V.G. also acknowledge the Wellcome Trust 4-year studentship programme in mechanisms of inflammatory disease (MIDAS; 215182/Z/19/Z). The funders had no role in study design, data collection, analysis and interpretation, or writing of this report. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the UK Department of Health and Social Care.",

year = "2021",

month = nov,

doi = "10.1093/bjs/znab183",

language = "English",

volume = "108",

pages = "1274--1292",

journal = "British Journal of Surgery",

issn = "0007-1323",

publisher = "Wiley-Blackwell",

number = "11",

}

TY - JOUR

T1 - Machine learning risk prediction of mortality for patients undergoing surgery with perioperative SARS-CoV-2

T2 - the COVIDSurg mortality score

AU - Bravo, Laura

AU - Nepogodiev, Dmitri

AU - Glasbey, James C.

AU - Li, Elizabeth

AU - Simoes, Joana F.F.

AU - Kamarajah, Sivesh K.

AU - Picciochi, Maria

AU - Abbott, Tom E.F.

AU - Ademuyiwa, Adesoji O.

AU - Arnaud, Alexis P.

AU - Agarwal, Arnav

AU - Brar, Amanpreet

AU - Elhadi, Muhammed

AU - Mazingi, Dennis

AU - Cardoso, Victor Roth

AU - Lawday, Samuel

AU - Sayyed, Raza

AU - Omar, Omar M.

AU - de la Madina, Antonio Ramos

AU - Slater, Luke

AU - Venn, Mary L.

AU - Gkoutos, Georgios

AU - Bhangu, Aneel

AU - Karwath, Andreas

AU - Siaw-Acheampong, Kwabena

AU - Argus, Leah

AU - Chaudhry, Daoud

AU - Dawson, Brett E.

AU - Gujjuri, Rohan R.

AU - Jones, Conor S.

AU - Khatri, Chetan

AU - Keatley, James M.

AU - Mann, Harvinder

AU - Marson, Ella J.

AU - Mclean, Kenneth A.

AU - Taylor, Elliott H.

AU - Tiwari, Abhinav

AU - Trout, Isobel M.

AU - Wilkin, Richard J.W.

AU - Dajti, Irida

AU - Gjata, Arben

AU - Boccalatte, Luis

AU - Modolo, Maria Marta

AU - Cox, Daniel

AU - Pockney, Peter

AU - Townend, Philip

AU - Aigner, Felix

AU - Kronberger, Irmgard

AU - Hossain, Kamral

AU - VanRamshorst, Gabrielle

AU - Lawani, Ismail

AU - Ataide, Gustavo

AU - Baiocchi, Glauco

AU - Buarque, Igor

AU - Gohar, Muhammad

AU - Slavchev, Mihail

AU - Martin, Janet

AU - Olivos, Maricarmen

AU - Calvache, Jose

AU - Rivera, Carlos Jose Perez

AU - Hadzibegovic, Ana Danic

AU - Kopjar, Tomislav

AU - Mihanovic, Jakov

AU - Klat, Jaroslav

AU - Novysedlak, René

AU - Christensen, Peter

AU - El-Hussuna, Alaa

AU - Batista, Sylvia

AU - Lincango, Eddy

AU - Emile, Sameh H.

AU - Mengesha, Mengistu Gebreyohanes

AU - Hailu, Samuel

AU - Tamiru, Hailu

AU - Kauppila, Joonas

AU - Laukkarinen, Johanna

AU - Albertsmeiers, Markus

AU - Lederhuber, Hans

AU - Loffler, Markus

AU - Tabiri, Stephen

AU - Metallidis, Symeon

AU - Tsoulfas, Georgios

AU - Lorena, Maria Aguilera

AU - Grecinos, Gustavo

AU - Mersich, Tamas

AU - Wettstein, Daniel

AU - Ghosh, Dhruv

AU - Kembuan, Gabriele

AU - Brouk, Peiman

AU - Khosravi, Mohammad

AU - Mozafari, Masoud

AU - Adil, Ahmed

AU - Mohan, Helen M.

AU - Zmora, Oded

AU - Fiore, Marco

AU - Gallo, Gaetano

AU - Pata, Francesco

AU - Pellino, Gianluca

AU - Satoi, Sohei

AU - Ayasra, Faris

AU - Chaar, Mohammad

AU - Fakhradiyev, Ildar R.

AU - Jamal, Mohammad

AU - Gulla, Aiste

AU - Roslani, April

AU - Martinez, Laura

AU - De La Medina, Antonio Ramos

AU - Outani, Oumaima

AU - Jonker, Pascal

AU - Kruijff, Schelto

AU - Noltes, Milou

AU - Steinkamp, Pieter

AU - van der Plas, Willemijn

AU - Osinaike, Babatunde

AU - Seyiolajide, Justina

AU - Williams, Emmanuel

AU - Pejkova, Sofija

AU - Augestad, Knut Magne

AU - Soreide, Kjetil

AU - Al Balushi, Zainab

AU - Qureshi, Ahmad

AU - Daraghmeh, Mustafa Abu Mohsen

AU - Abukhalaf, Sadi

AU - Cukier, Moises

AU - Gomez, Hugo

AU - Shu, Sebastian

AU - Vasquez, Ximena

AU - Parreno-Sacdalan, Marie Dione

AU - Major, Piotr

AU - Azevedo, José

AU - Cunha, Miguel

AU - Santos, Irene

AU - Zarour, Ahmad

AU - Bonci, Eduard Alexandru

AU - Negoi, Ionut

AU - Efetov, Sergey

AU - Litvin, Andrey

AU - Ntirenganya, Faustin

AU - Al Ameer, Ehab

AU - Radenkovic, Dejan

AU - Xiang, Frederick Koh Hong

AU - Hoe, Chew Min

AU - Yong, James Ngu Chi

AU - Moore, Rachel

AU - Nhlabathi, Ncamsile

AU - Colino, Ruth Blanco

AU - Bravo, Ana Minaya

AU - Minaya-Bravo, Ana

AU - Jayarajah, Umesh

AU - Wickramasinghe, Dakshitha

AU - Elmujtaba, Mohammed

AU - Jebril, William

AU - Rutegård, Martin

AU - Sund, Malin

AU - Isik, Arda

AU - Leventoǧlu, Sezai

AU - Benson, Ruth

AU - Caruna, Ed

AU - Chakrabortee, Sohini

AU - Demetriades, Andreas

AU - Desai, Anant

AU - Drake, Thomas D.

AU - Edwards, John G.

AU - Evans, Jonathan P.

AU - Ford, Samuel

AU - Fotopoulou, Christina

AU - Griffiths, Ewen

AU - Hutchinson, Peter

AU - Jenkinson, Michael D.

AU - Khan, Tabassum

AU - Knight, Stephen

AU - Kolias, Angelos

AU - Leung, Elaine

AU - McKay, Siobhan

AU - Norman, Lisa

AU - Ots, Riinu

AU - Raghavan, Vidya

AU - Schache, Andrew

AU - Shaw, Richard

AU - Shaw, Katie

AU - Smart, Neil

AU - Stewart, Grant

AU - Sundar, Sudha

AU - Vimalchandran, Dale

AU - Wright, Naomi

AU - Alshryda, Sattar

AU - Alser, Osaid

AU - Breen, Kerry

AU - Ganly, Ian

AU - Kaafarani, Haytham

AU - Kendall, Brittany

AU - Mashbari, Hassan

AU - Al Naggar, Hamza

AU - Valenzuela, J. I.

AU - Boccalatte, L. A.

AU - Gemelli, N. A.

AU - Smith, D. E.

AU - Dudi-Venkata, N. N.

AU - Kroon, H. M.

AU - Sammour, T.

AU - Roberts, M.

AU - Mitchell, D.

AU - Lah, K.

AU - Pearce, A.

AU - Morton, A.

AU - Dawson, A. C.

AU - Drane, A.

AU - Sharpin, C.

AU - Nataraja, R. M.

AU - Pacilli, M.

AU - Cox, D. R.A.

AU - Muralidharan, V.

AU - Riddiough, G. E.

AU - Clarke, E. M.

AU - Jamel, W.

AU - Qin, K. R.

AU - Cope, D.

AU - Egoroff, N.

AU - Lott, N.

AU - Putnis, S.

AU - De Robles, S.

AU - Ang, Z.

AU - Mitteregger, M.

AU - Uranitsch, S.

AU - Stiegler, M.

AU - Seitinger, G.

AU - Lumenta, D. B.

AU - Nischwitz, S. P.

AU - Richtig, E.

AU - Pau, M.

AU - Srekl-Filzmaier, P.

AU - Eibinger, N.

AU - Michelitsch, B.

AU - Fediuk, M.

AU - Papinutti, A.

AU - Seidel, G.

AU - Kahn, J.

AU - Cohnert, T. U.

AU - Messner, F.

AU - Öfner, D.

AU - Presl, J.

AU - Varga, M.

AU - Weitzendorfer, M.

AU - Emmanuel, K.

AU - Binder, A. D.

AU - Zimmermann, M.

AU - Holawe, S.

AU - Nkenke, E.

AU - Grimm, C.

AU - Richards, T.

AU - COVIDSurg Collaborative

N1 - Funding Information: This report was funded by a National Institute for Health Research (NIHR) Global Health Research Unit Grant (NIHR 16.136.79), Association of Coloproctology of Great Britain and Ireland, Bowel & Cancer Research, Bowel Research UK, Association of Upper Gastrointestinal Surgeons, British Association of Surgical Oncology, British Gynaecological Cancer Society, European Society of Coloproctology, Medtronic, NIHR Academy, The Urology Foundation, Sarcoma UK, Vascular Society for Great Britain and Ireland, Yorkshire Cancer Research, and the MRC Health Data Research UK (HDRUK/CFC/01), an initiative funded by UK Research and Innovation, Department of Health and Social Care (England) and the devolved administrations, and leading medical research charities. L.B.M. and G.V.G. also acknowledge the Wellcome Trust 4-year studentship programme in mechanisms of inflammatory disease (MIDAS; 215182/Z/19/Z). The funders had no role in study design, data collection, analysis and interpretation, or writing of this report. The views expressed are those of the authors and not necessarily those of the National Health Service, the NIHR, or the UK Department of Health and Social Care.

PY - 2021/11

Y1 - 2021/11

N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/85113431484

U2 - 10.1093/bjs/znab183

DO - 10.1093/bjs/znab183

M3 - Article

C2 - 34227657

AN - SCOPUS:85113431484

SN - 0007-1323

VL - 108

SP - 1274

EP - 1292

JO - British Journal of Surgery

JF - British Journal of Surgery

IS - 11

ER -

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

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