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Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study

BACKGROUND: In armed conflicts, civilian health care struggles to cope. Being able to predict what resources are needed is therefore vital. The International Committee of the Red Cross (ICRC) implemented in the 1990s the Red Cross Wound Score (RCWS) for assessment of penetrating injuries. It is unkn...

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Autores principales: Muhrbeck, Måns, Osman, Zaher, von Schreeb, Johan, Wladis, Andreas, Andersson, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359038/
https://www.ncbi.nlm.nih.gov/pubmed/34380419
http://dx.doi.org/10.1186/s12873-021-00488-2
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author Muhrbeck, Måns
Osman, Zaher
von Schreeb, Johan
Wladis, Andreas
Andersson, Peter
author_facet Muhrbeck, Måns
Osman, Zaher
von Schreeb, Johan
Wladis, Andreas
Andersson, Peter
author_sort Muhrbeck, Måns
collection PubMed
description BACKGROUND: In armed conflicts, civilian health care struggles to cope. Being able to predict what resources are needed is therefore vital. The International Committee of the Red Cross (ICRC) implemented in the 1990s the Red Cross Wound Score (RCWS) for assessment of penetrating injuries. It is unknown to what extent RCWS or the established trauma scores Kampala trauma Score (KTS) and revised trauma score (RTS) can be used to predict surgical resource consumption and in-hospital mortality in resource-scarce conflict settings. METHODS: A retrospective study of routinely collected data on weapon-injured adults admitted to ICRC’s hospitals in Peshawar, 2009–2012 and Goma, 2012–2014. High resource consumption was defined as ≥3 surgical procedures or ≥ 3 blood-transfusions or amputation. The relationship between RCWS, KTS, RTS and resource consumption, in-hospital mortality was evaluated with logistic regression and adjusted area under receiver operating characteristic curves (AUC). The impact of missing data was assessed with imputation. Model fit was compared with Akaike Information Criterion (AIC). RESULTS: A total of 1564 patients were included, of these 834 patients had complete data. For high surgical resource consumption AUC was significantly higher for RCWS (0.76, 95% CI 0.74–0.78) than for KTS (0.53, 95% CI 0.50–0.56) and RTS (0.51, 95% CI 0.48–0.54) for all patients. Additionally, RCWS had lower AIC, indicating a better model fit. For in-hospital mortality AUC was significantly higher for RCWS (0.83, 95% CI 0.79–0.88) than for KTS (0.71, 95% CI 0.65–0.76) and RTS (0.70, 95% CI 0.63–0.76) for all patients, but not for patients with complete data. CONCLUSION: RCWS appears to predict surgical resource consumption better than KTS and RTS. RCWS may be a promising tool for planning and monitoring surgical care in resource-scarce conflict settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12873-021-00488-2.
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spelling pubmed-83590382021-08-16 Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study Muhrbeck, Måns Osman, Zaher von Schreeb, Johan Wladis, Andreas Andersson, Peter BMC Emerg Med Research Article BACKGROUND: In armed conflicts, civilian health care struggles to cope. Being able to predict what resources are needed is therefore vital. The International Committee of the Red Cross (ICRC) implemented in the 1990s the Red Cross Wound Score (RCWS) for assessment of penetrating injuries. It is unknown to what extent RCWS or the established trauma scores Kampala trauma Score (KTS) and revised trauma score (RTS) can be used to predict surgical resource consumption and in-hospital mortality in resource-scarce conflict settings. METHODS: A retrospective study of routinely collected data on weapon-injured adults admitted to ICRC’s hospitals in Peshawar, 2009–2012 and Goma, 2012–2014. High resource consumption was defined as ≥3 surgical procedures or ≥ 3 blood-transfusions or amputation. The relationship between RCWS, KTS, RTS and resource consumption, in-hospital mortality was evaluated with logistic regression and adjusted area under receiver operating characteristic curves (AUC). The impact of missing data was assessed with imputation. Model fit was compared with Akaike Information Criterion (AIC). RESULTS: A total of 1564 patients were included, of these 834 patients had complete data. For high surgical resource consumption AUC was significantly higher for RCWS (0.76, 95% CI 0.74–0.78) than for KTS (0.53, 95% CI 0.50–0.56) and RTS (0.51, 95% CI 0.48–0.54) for all patients. Additionally, RCWS had lower AIC, indicating a better model fit. For in-hospital mortality AUC was significantly higher for RCWS (0.83, 95% CI 0.79–0.88) than for KTS (0.71, 95% CI 0.65–0.76) and RTS (0.70, 95% CI 0.63–0.76) for all patients, but not for patients with complete data. CONCLUSION: RCWS appears to predict surgical resource consumption better than KTS and RTS. RCWS may be a promising tool for planning and monitoring surgical care in resource-scarce conflict settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12873-021-00488-2. BioMed Central 2021-08-11 /pmc/articles/PMC8359038/ /pubmed/34380419 http://dx.doi.org/10.1186/s12873-021-00488-2 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Muhrbeck, Måns
Osman, Zaher
von Schreeb, Johan
Wladis, Andreas
Andersson, Peter
Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study
title Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study
title_full Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study
title_fullStr Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study
title_full_unstemmed Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study
title_short Predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study
title_sort predicting surgical resource consumption and in-hospital mortality in resource-scarce conflict settings: a retrospective study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359038/
https://www.ncbi.nlm.nih.gov/pubmed/34380419
http://dx.doi.org/10.1186/s12873-021-00488-2
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