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Out-of-hospital cardiac arrest in the home: Can area characteristics identify at-risk communities in the Republic of Ireland?
BACKGROUND: Internationally, the majority of out-of-hospital cardiac arrests where resuscitation is attempted (OHCAs) occur in private residential locations i.e. at home. The prospect of survival for this patient group is universally dismal. Understanding of the area-level factors that affect the in...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819205/ https://www.ncbi.nlm.nih.gov/pubmed/29458377 http://dx.doi.org/10.1186/s12942-018-0126-z |
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author | Masterson, Siobhán Teljeur, Conor Cullinan, John Murphy, Andrew W. Deasy, Conor Vellinga, Akke |
author_facet | Masterson, Siobhán Teljeur, Conor Cullinan, John Murphy, Andrew W. Deasy, Conor Vellinga, Akke |
author_sort | Masterson, Siobhán |
collection | PubMed |
description | BACKGROUND: Internationally, the majority of out-of-hospital cardiac arrests where resuscitation is attempted (OHCAs) occur in private residential locations i.e. at home. The prospect of survival for this patient group is universally dismal. Understanding of the area-level factors that affect the incidence of OHCA at home may help national health planners when implementing community resuscitation training and services. METHODS: We performed spatial smoothing using Bayesian conditional autoregression on case data from the Irish OHCA register. We further corrected for correlated findings using area level variables extracted and constructed for national census data. RESULTS: We found that increasing deprivation was associated with increased case incidence. The methodology used also enabled us to identify specific areas with higher than expected case incidence. CONCLUSIONS: Our study demonstrates novel use of Bayesian conditional autoregression in quantifying area level risk of a health event with high mortality across an entire country with a diverse settlement pattern. It adds to the evidence that the likelihood of OHCA resuscitation events is associated with greater deprivation and suggests that area deprivation should be considered when planning resuscitation services. Finally, our study demonstrates the utility of Bayesian conditional autoregression as a methodological approach that could be applied in any country using registry data and area level census data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12942-018-0126-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5819205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58192052018-02-21 Out-of-hospital cardiac arrest in the home: Can area characteristics identify at-risk communities in the Republic of Ireland? Masterson, Siobhán Teljeur, Conor Cullinan, John Murphy, Andrew W. Deasy, Conor Vellinga, Akke Int J Health Geogr Research BACKGROUND: Internationally, the majority of out-of-hospital cardiac arrests where resuscitation is attempted (OHCAs) occur in private residential locations i.e. at home. The prospect of survival for this patient group is universally dismal. Understanding of the area-level factors that affect the incidence of OHCA at home may help national health planners when implementing community resuscitation training and services. METHODS: We performed spatial smoothing using Bayesian conditional autoregression on case data from the Irish OHCA register. We further corrected for correlated findings using area level variables extracted and constructed for national census data. RESULTS: We found that increasing deprivation was associated with increased case incidence. The methodology used also enabled us to identify specific areas with higher than expected case incidence. CONCLUSIONS: Our study demonstrates novel use of Bayesian conditional autoregression in quantifying area level risk of a health event with high mortality across an entire country with a diverse settlement pattern. It adds to the evidence that the likelihood of OHCA resuscitation events is associated with greater deprivation and suggests that area deprivation should be considered when planning resuscitation services. Finally, our study demonstrates the utility of Bayesian conditional autoregression as a methodological approach that could be applied in any country using registry data and area level census data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12942-018-0126-z) contains supplementary material, which is available to authorized users. BioMed Central 2018-02-20 /pmc/articles/PMC5819205/ /pubmed/29458377 http://dx.doi.org/10.1186/s12942-018-0126-z Text en © The Author(s) 2018 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 | Research Masterson, Siobhán Teljeur, Conor Cullinan, John Murphy, Andrew W. Deasy, Conor Vellinga, Akke Out-of-hospital cardiac arrest in the home: Can area characteristics identify at-risk communities in the Republic of Ireland? |
title | Out-of-hospital cardiac arrest in the home: Can area characteristics identify at-risk communities in the Republic of Ireland? |
title_full | Out-of-hospital cardiac arrest in the home: Can area characteristics identify at-risk communities in the Republic of Ireland? |
title_fullStr | Out-of-hospital cardiac arrest in the home: Can area characteristics identify at-risk communities in the Republic of Ireland? |
title_full_unstemmed | Out-of-hospital cardiac arrest in the home: Can area characteristics identify at-risk communities in the Republic of Ireland? |
title_short | Out-of-hospital cardiac arrest in the home: Can area characteristics identify at-risk communities in the Republic of Ireland? |
title_sort | out-of-hospital cardiac arrest in the home: can area characteristics identify at-risk communities in the republic of ireland? |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819205/ https://www.ncbi.nlm.nih.gov/pubmed/29458377 http://dx.doi.org/10.1186/s12942-018-0126-z |
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