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An epidemiological approach to mass casualty incidents in the Principality of Asturias (Spain)

BACKGROUND: Mass Casualty Incidents (MCI) have been rarely studied from epidemiological approaches. The objective of this study is to establish the epidemiological profile of MCI in the autonomous region of the Principality of Asturias (Spain) and analyse ambulance deployment and severity of patient...

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Autores principales: Castro Delgado, Rafael, Naves Gómez, Cecilia, Cuartas Álvarez, Tatiana, Arcos González, Pedro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4765155/
https://www.ncbi.nlm.nih.gov/pubmed/26911474
http://dx.doi.org/10.1186/s13049-016-0211-x
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author Castro Delgado, Rafael
Naves Gómez, Cecilia
Cuartas Álvarez, Tatiana
Arcos González, Pedro
author_facet Castro Delgado, Rafael
Naves Gómez, Cecilia
Cuartas Álvarez, Tatiana
Arcos González, Pedro
author_sort Castro Delgado, Rafael
collection PubMed
description BACKGROUND: Mass Casualty Incidents (MCI) have been rarely studied from epidemiological approaches. The objective of this study is to establish the epidemiological profile of MCI in the autonomous region of the Principality of Asturias (Spain) and analyse ambulance deployment and severity of patients. METHODS: This is a population-based prospective study run in 2014. Inclusion criteria for MCI is “every incident with four or more people affected that requires ambulance mobilisation”. RESULTS: Thirty-nine MCI have been identified in Asturias in 2014. Thirty-one (79 %) were road traffic accidents, three (7.5 %) fires and five (12.8 %) other types. Twenty-one incidents (56.7 %) had four patients, and only three of them (8 %) had seven or more patients. An average of 2.41 ambulances per incident were deployed (standard error = 0.18). Most of the patients per incident were minor injured patients (mean = 4; standard error = 0.2), and 0,26 were severe patients (standard error = 0.08). There was a positive significant correlation (p < 0.01) between the total number of patients and the total number of ambulances deployed and between the total number of patients and Advanced Life Support (ALS) ambulances deployed (p < 0.001). The total number of non-ALS ambulances was not related with the total number of patients. DISCUSSION: Population based research in MCI is essential to define MCI profile. Quantitative definition of MCI, adapted to resources, avoid selection bias and present a more accurate profile of MCI. As espected, road traffic accidents are the most frequent MCI in our region. This aspect is essential to plan training and response to MCI. Analysis of total response to MCI shows that for almost an hour, we should plan extra resources for daily emergencies. This data is an important issue to bear in mind when planning MCI response. The fact that most patients are classified as minor injured and more advanced life support units than needed are deployed shows that analysis of resources deployment and patient severity helps us to better plan future MCI response. CONCLUSIONS: Road traffic accidents with minor injured patients are the most frequent MCI in our region. More advanced life support units than needed have been initially deployed, which might compromise response to daily emergencies during an MCI.
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spelling pubmed-47651552016-02-25 An epidemiological approach to mass casualty incidents in the Principality of Asturias (Spain) Castro Delgado, Rafael Naves Gómez, Cecilia Cuartas Álvarez, Tatiana Arcos González, Pedro Scand J Trauma Resusc Emerg Med Original Research BACKGROUND: Mass Casualty Incidents (MCI) have been rarely studied from epidemiological approaches. The objective of this study is to establish the epidemiological profile of MCI in the autonomous region of the Principality of Asturias (Spain) and analyse ambulance deployment and severity of patients. METHODS: This is a population-based prospective study run in 2014. Inclusion criteria for MCI is “every incident with four or more people affected that requires ambulance mobilisation”. RESULTS: Thirty-nine MCI have been identified in Asturias in 2014. Thirty-one (79 %) were road traffic accidents, three (7.5 %) fires and five (12.8 %) other types. Twenty-one incidents (56.7 %) had four patients, and only three of them (8 %) had seven or more patients. An average of 2.41 ambulances per incident were deployed (standard error = 0.18). Most of the patients per incident were minor injured patients (mean = 4; standard error = 0.2), and 0,26 were severe patients (standard error = 0.08). There was a positive significant correlation (p < 0.01) between the total number of patients and the total number of ambulances deployed and between the total number of patients and Advanced Life Support (ALS) ambulances deployed (p < 0.001). The total number of non-ALS ambulances was not related with the total number of patients. DISCUSSION: Population based research in MCI is essential to define MCI profile. Quantitative definition of MCI, adapted to resources, avoid selection bias and present a more accurate profile of MCI. As espected, road traffic accidents are the most frequent MCI in our region. This aspect is essential to plan training and response to MCI. Analysis of total response to MCI shows that for almost an hour, we should plan extra resources for daily emergencies. This data is an important issue to bear in mind when planning MCI response. The fact that most patients are classified as minor injured and more advanced life support units than needed are deployed shows that analysis of resources deployment and patient severity helps us to better plan future MCI response. CONCLUSIONS: Road traffic accidents with minor injured patients are the most frequent MCI in our region. More advanced life support units than needed have been initially deployed, which might compromise response to daily emergencies during an MCI. BioMed Central 2016-02-24 /pmc/articles/PMC4765155/ /pubmed/26911474 http://dx.doi.org/10.1186/s13049-016-0211-x Text en © Castro Delgado et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Original Research
Castro Delgado, Rafael
Naves Gómez, Cecilia
Cuartas Álvarez, Tatiana
Arcos González, Pedro
An epidemiological approach to mass casualty incidents in the Principality of Asturias (Spain)
title An epidemiological approach to mass casualty incidents in the Principality of Asturias (Spain)
title_full An epidemiological approach to mass casualty incidents in the Principality of Asturias (Spain)
title_fullStr An epidemiological approach to mass casualty incidents in the Principality of Asturias (Spain)
title_full_unstemmed An epidemiological approach to mass casualty incidents in the Principality of Asturias (Spain)
title_short An epidemiological approach to mass casualty incidents in the Principality of Asturias (Spain)
title_sort epidemiological approach to mass casualty incidents in the principality of asturias (spain)
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4765155/
https://www.ncbi.nlm.nih.gov/pubmed/26911474
http://dx.doi.org/10.1186/s13049-016-0211-x
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