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澳大利亚昆士兰州院外心脏骤停风险的时空变化。

Spatiotemporal variation in the risk of out-of-hospital cardiac arrests in Queensland, Australia.

作者信息

Doan Tan N, Wilson Daniel, Rashford Stephen, Ball Stephen, Bosley Emma

机构信息

Queensland Ambulance Service, Queensland Government Department of Health, Brisbane, Queensland, Australia.

Department of Medicine at The Royal Melbourne Hospital, University of Melbourne, Melbourne, Victoria, Australia.

出版信息

Resusc Plus. 2021 Sep 21;8:100166. doi: 10.1016/j.resplu.2021.100166. eCollection 2021 Dec.

Abstract

BACKGROUND

Spatiotemporal analysis of out-of-hospital cardiac arrest (OHCA) risk is essential to design targeted public health strategies. Such information is lacking in the state of Queensland and Australia more broadly.

METHODS

We developed a spatiotemporal Bayesian model accounting for spatial and temporal dimensions, space-time interactions, and demographic factors. The model was fit to data of all OHCA cases attended by paramedics in Queensland between January 2007 and December 2019. Parameter inference was performed using the integrated nested Laplace approximation method. We estimated and thematically mapped area-year risk of OHCA occurrence for all 78 local government areas (LGAs) in Queensland.

RESULTS

We observed spatial variability in OHCA risk among the LGAs. Areas in the north half of the state and two areas in the south exhibited the highest risk; whereas OHCA risk was lowest in the west and south west parts of the state. Demographic factors did not have significant impact on the heterogeneity of risk between the LGAs. An overall trend of modestly decreasing risk of OHCA was found.

CONCLUSIONS

This study identified areas of high OHCA risk in Queensland, providing valuable information to guide public health policy and optimise resource allocation. Further research is needed to investigate the specifics of the areas that may explain their risk profile.

摘要

背景

院外心脏骤停(OHCA)风险的时空分析对于制定有针对性的公共卫生策略至关重要。在昆士兰州乃至整个澳大利亚,此类信息都很缺乏。

方法

我们开发了一个时空贝叶斯模型,该模型考虑了空间和时间维度、时空交互作用以及人口统计学因素。该模型适用于2007年1月至2019年12月昆士兰州护理人员处理的所有OHCA病例的数据。使用集成嵌套拉普拉斯近似方法进行参数推断。我们估计并按主题绘制了昆士兰州所有78个地方政府区域(LGA)OHCA发生的区域年风险。

结果

我们观察到各地方政府区域间OHCA风险存在空间变异性。该州北半部的区域和南部的两个区域风险最高;而该州西部和西南部的OHCA风险最低。人口统计学因素对各地方政府区域间风险的异质性没有显著影响。发现OHCA风险总体呈适度下降趋势。

结论

本研究确定了昆士兰州OHCA高风险区域,为指导公共卫生政策和优化资源分配提供了有价值的信息。需要进一步研究以调查这些区域可能解释其风险概况的具体情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e8c0/8463902/1c8fab070ae5/gr1.jpg

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