: 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

Paiella S;Turri G;Rattizzato S;Campagnaro T;Guglielmi A;Pedrazzani C;Ruzzenente A;Poletto E;Conci S;Casetti L;Salvia R;Malleo G;Esposito A;De Pastena M;Bassi C;Tuveri M;Nobile S;Marchegiani G;Bortolasi L
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.
2021
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1085378
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