Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.

SARS-CoV-2 vaccination modelling for safe surgery to save lives: Data from an international prospective cohort study

Vittorio Aprile;Stefano Berrettini
Membro del Collaboration Group
;
Luca Bruschini
Membro del Collaboration Group
;
Massimo Chiarugi;Federico Coccolini;Giacomo Fiacchini
Membro del Collaboration Group
;
Luca Morelli;Matteo Palmeri;Marco Puccini;Dario Tartaglia
Membro del Collaboration Group
;
2021-01-01

Abstract

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population.
2021
Reuben Abel, Joel; Andreani, Lorenzo; Antonio, D’Arienzo; Aprile, Vittorio; Balestri, Riccardo; Benettini, Giacomo; Berrettini, Stefano; Bruschini, Luca; Chiarugi, Massimo; Coccolini, Federico; Colangeli, Simone; Cremonini, Camilla; Cristofani Mencacci, Lodovica; Dallan, Iacopo; De Santi, Silvia; Di Franco, Gregorio; Di Girolami, Lorena; Fiacchini, Giacomo; Furbetta, Niccolò; Korasidis, Stylianos; Lucchi, Marco; Morandi, Andrea; Morelli, Luca; Musetti, Serena; Maria Neri, Carlo; Palmeri, Matteo; Picariello, Miriana; Porcelli, Francesco; Puccini, Marco; Roffi, Nicolo’; Statuti, Erica; Tartaglia, Dario; Tonelli, Alberto; Vianini, Matteo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1101514
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