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Pregled bibliografske jedinice broj: 1119595

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


(COVIDSurg Collaborative) Nepogodiev, Dmitri; ...; Gršić, Krešimir; Mihanović, Jakov; ...; Zwittag, Paul et al.
SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study // British journal of surgery, 108 (2021), 9; 1056-1063 doi:10.1093/bjs/znab101 (međunarodna recenzija, članak, ostalo)


CROSBI ID: 1119595 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study
(SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study)

Autori
Nepogodiev, Dmitri ; ... ; Gršić, Krešimir ; Mihanović, Jakov ; ... ; Zwittag, Paul et al.

Kolaboracija
COVIDSurg Collaborative

Izvornik
British journal of surgery (0007-1323) 108 (2021), 9; 1056-1063

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, ostalo

Ključne riječi
SARS-CoV-2 ; vaccination ; safe surgery

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Temeljne medicinske znanosti, Kliničke medicinske znanosti, Javno zdravstvo i zdravstvena zaštita



POVEZANOST RADA


Ustanove:
Klinički bolnički centar Zagreb,
Sveučilište u Zadru,
Opća bolnica Zadar

Profili:

Avatar Url Jakov Mihanović (autor)

Avatar Url Krešimir Gršić (autor)

Citiraj ovu publikaciju:

(COVIDSurg Collaborative) Nepogodiev, Dmitri; ...; Gršić, Krešimir; Mihanović, Jakov; ...; Zwittag, Paul et al.
SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study // British journal of surgery, 108 (2021), 9; 1056-1063 doi:10.1093/bjs/znab101 (međunarodna recenzija, članak, ostalo)
(COVIDSurg Collaborative) (COVIDSurg Collaborative) Nepogodiev, D., ..., Gršić, K., Mihanović, J., ... & Zwittag, P. (2021) SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study. British journal of surgery, 108 (9), 1056-1063 doi:10.1093/bjs/znab101.
@article{article, author = {Nepogodiev, Dmitri and Gr\v{s}i\'{c}, Kre\v{s}imir and Mihanovi\'{c}, Jakov and Zwittag, Paul et al.}, year = {2021}, pages = {1056-1063}, DOI = {10.1093/bjs/znab101}, keywords = {SARS-CoV-2, vaccination, safe surgery}, journal = {British journal of surgery}, doi = {10.1093/bjs/znab101}, volume = {108}, number = {9}, issn = {0007-1323}, title = {SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study}, keyword = {SARS-CoV-2, vaccination, safe surgery} }
@article{article, author = {Nepogodiev, Dmitri and Gr\v{s}i\'{c}, Kre\v{s}imir and Mihanovi\'{c}, Jakov and Zwittag, Paul et al.}, year = {2021}, pages = {1056-1063}, DOI = {10.1093/bjs/znab101}, keywords = {SARS-CoV-2, vaccination, safe surgery}, journal = {British journal of surgery}, doi = {10.1093/bjs/znab101}, volume = {108}, number = {9}, issn = {0007-1323}, title = {SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study}, keyword = {SARS-CoV-2, vaccination, safe surgery} }

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


Citati:





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