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优化远程通信员对院外心脏骤停的识别:一项范围综述。

Optimising telecommunicator recognition of out-of-hospital cardiac arrest: A scoping review.

作者信息

Juul Grabmayr Anne, Dicker Bridget, Dassanayake Vihara, Bray Janet, Vaillancourt Christian, Dainty Katie N, Olasveengen Theresa, Malta Hansen Carolina

机构信息

Emergency Medical Services Capital Region of Denmark - University of Copenhagen, Ballerup, Denmark.

Department of Clinical Medicine, University of Copenhagen, Denmark.

出版信息

Resusc Plus. 2024 Aug 30;20:100754. doi: 10.1016/j.resplu.2024.100754. eCollection 2024 Dec.

DOI:10.1016/j.resplu.2024.100754
PMID:39282502
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11402211/
Abstract

AIM

To summarize existing literature and identify knowledge gaps regarding barriers and enablers of telecommunicators' recognition of out-of-hospital cardiac arrest (OHCA).

METHODS

This scoping review was undertaken by an International Liaison Committee on Resuscitation (ILCOR) Basic Life Support scoping review team and guided by the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR). Studies were eligible for inclusion if they were peer-reviewed and explored barriers and enablers of telecommunicator recognition of OHCA. We searched Ovid MEDLINE® and Embase and included articles from database inception till June 18th, 2024.

RESULTS

We screened 9,244 studies and included 62 eligible studies on telecommunicator recognition of OHCA. The studies ranged in methodology. The majority were observational studies of emergency calls. The barriers most frequently described to OHCA recognition were breathing status and agonal breathing. The most frequently tested enabler for recognition was a variety of dispatch protocols focusing on breathing assessment. Only one randomized controlled trial (RCT) was identified, which found no difference in OHCA recognition with the addition of machine learning alerting telecommunicators in suspected OHCA cases.

CONCLUSION

Most studies were observational, assessed barriers to recognition of OHCA and compared different dispatch protocols. Only one RCT was identified. Randomized trials should be conducted to inform how to improve telecommunicator recognition of OHCA, including recognition of pediatric OHCAs and assessment of dispatch protocols.

摘要

目的

总结现有文献,确定关于电信急救人员识别院外心脏骤停(OHCA)的障碍和促进因素方面的知识空白。

方法

本范围综述由国际复苏联合委员会(ILCOR)基础生命支持范围综述小组进行,并遵循系统评价和Meta分析扩展版的首选报告项目(PRISMA-ScR)的指导。如果研究经过同行评审且探讨了电信急救人员识别OHCA的障碍和促进因素,则有资格纳入。我们检索了Ovid MEDLINE®和Embase,并纳入了从数据库建立到2024年6月18日的文章。

结果

我们筛选了9244项研究,纳入了62项关于电信急救人员识别OHCA的合格研究。这些研究方法各异。大多数是对紧急呼叫的观察性研究。OHCA识别中最常描述的障碍是呼吸状态和濒死呼吸。最常测试的识别促进因素是各种侧重于呼吸评估的调度协议。仅识别出一项随机对照试验(RCT),该试验发现在疑似OHCA病例中添加机器学习警报电信急救人员后,OHCA识别率没有差异。

结论

大多数研究是观察性的,评估了OHCA识别的障碍,并比较了不同的调度协议。仅识别出一项RCT。应进行随机试验,以告知如何改善电信急救人员对OHCA的识别,包括对儿童OHCA的识别以及对调度协议的评估。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f535/11402211/c03b8358e74c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f535/11402211/c03b8358e74c/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f535/11402211/c03b8358e74c/gr1.jpg

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When the machine is wrong. Characteristics of true and false predictions of Out-of-Hospital Cardiac arrests in emergency calls using a machine-learning model.
当机器出现错误时。使用机器学习模型对紧急呼叫中的院外心脏骤停进行真假预测的特征。
Resuscitation. 2023 Feb;183:109689. doi: 10.1016/j.resuscitation.2023.109689. Epub 2023 Jan 9.
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Evaluation of National Institutes of Health cardiac arrest research based on "chain of survival" links.基于“生存链”环节对美国国立卫生研究院心脏骤停研究的评估。
Acad Emerg Med. 2022 Nov;29(11):1381-1382. doi: 10.1111/acem.14569. Epub 2022 Aug 13.
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