Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 666

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Global guidance for surgical care during the COVID-19 pandemic

Open access
COVIDSurg Collaborative, Bhangu, Aneel, Lawani, Ismail, Ng-Kamstra, Joshua S, Wang, Yanfeng, Chan, Albert, Futaba, Kaori, Ng, Simon, Ebele, Emery, Lederhuber, Hans, Tabiri, Stephen, Ghosh, Dhruv, Gallo, Gaetano, Pata, Francesco, Di Saverio, Salomone, Spinelli, Antonino, Medina, Antonio Ramos-De, Ademuyiwa, Adesoji O, Akinbode, Gbemisola, Ingabire, J C Allen, Ntirenganya, Faustin, Kamara, Thaim B, Goh, Minghui, Moore, Rachel, Kim, Hye Jin, Lee, Suk-Hwan, Minaya-Bravo, Ana, Abbott, Tom, Chakrabortee, Sohini, Denning, Max, Fitzgerald, J Edward, Glasbey, James, Griffiths, Ewen, Halkias, Constantine, Harrison, Ewen M, Jones, Conor S, Kinross, James, Lawday, Samuel, Li, Elizabeth, Markar, Sheraz, Morton, Dion G, Nepogodiev, Dmitri, Pinkney, Thomas D, Simoes, Joana, Warren, Oliver, Wong, Danny J N, Bankhead-Kendall, Brittany, Breen, Kerry A, Davidson, Giana H, Kaafarani, Haytham, Keller, Deborah S, Mazingi, Dennis, Kamarajah, Sivesh K, Blackwell, Sue, Dames, Nicola·2020·British Journal of Surgery
DOI 10.1002/bjs.11646
Open this paper in CoChat — free account

Abstract

Background: Surgeons urgently need guidance on how to deliver surgical services safely and effectively during the COVID-19 pandemic. The aim was to identify the key domains that should be considered when developing pandemic preparedness plans for surgical services. Methods: A scoping search was conducted to identify published articles relating to management of surgical patients during pandemics. Key informant interviews were conducted with surgeons and anaesthetists with direct experience of working during infectious disease outbreaks, in order to identify key challenges and solutions to delivering effective surgical services during the COVID-19 pandemic. Results: Thirteen articles were identified from the scoping search, and surgeons and anaesthetists representing 11 territories were interviewed. To mount an effective response to COVID-19, a pandemic response plan for surgical services should be developed in advance. Key domains that should be included are: provision of staff training (such as patient transfers, donning and doffing personal protection equipment, recognizing and managing COVID-19 infection); support for the overall hospital response to COVID-19 (reduction in non-urgent activities such as clinics, endoscopy, non-urgent elective surgery); establishment of a team-based approach for running emergency services; and recognition and management of COVID-19 infection in patients treated as an emergency and those who have had surgery. A backlog of procedures after the end of the COVID-19 pandemic is inevitable, and hospitals should plan how to address this effectively to ensure that patients having elective treatment have the best possible outcomes. Conclusion: Hospitals should prepare detailed context-specific pandemic preparedness plans addressing the identified domains. Specific guidance should be updated continuously to reflect emerging evidence during the COVID-19 pandemic.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/bjs.11646

Cites

14 of 14 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 666

Metadata

Authors
Collaborative, C., Bhangu, A., Lawani, I., Ng-Kamstra, J. S., Wang, Y., Chan, A., Futaba, K., Ng, S., Ebele, E., Lederhuber, H., Tabiri, S., Ghosh, D., Gallo, G., Pata, F., Di Saverio, S., Spinelli, A., Medina, A. R.-D., Ademuyiwa, A. O., Akinbode, G., Ingabire, J. C. A., Ntirenganya, F., Kamara, T. B., Goh, M., Moore, R., Kim, H. J., Lee, S.-H., Minaya-Bravo, A., Abbott, T., Chakrabortee, S., Denning, M., Fitzgerald, J. E., Glasbey, J., Griffiths, E., Halkias, C., Harrison, E. M., Jones, C. S., Kinross, J., Lawday, S., Li, E., Markar, S., Morton, D. G., Nepogodiev, D., Pinkney, T. D., Simoes, J., Warren, O., Wong, D. J. N., Bankhead-Kendall, B., Breen, K. A., Davidson, G. H., Kaafarani, H., Keller, D. S., Mazingi, D., Kamarajah, S. K., Blackwell, S., & Dames, N.
Venue
British Journal of Surgery
Publisher
Oxford University Press (OUP)
Published
2020-04-15
Volume
107
Issue
9
Pages
1097-1103
ISSN
  • 0007-1323 (ISSN-L)
  • 1365-2168
DOI
10.1002/bjs.11646
OpenAlex
W3016066708
Cited by
666
References
14
FWCI
49.16
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.