基于PubMed 数据库的直升机紧急医疗服务 热点的共词聚类分析
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李学兰,E-mail :16426000@qq.com ;Tel :137871076

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Co-word clustering analysis of hotspots in the research of helicopter emergency medical service based on bibliometrics
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    摘要:

    目的 通过文献计量学方法归纳直升机紧急医疗服务研究领域的热点方向。方法 制定检索策 略,搜索PubMed 数据库中近10 年直升机紧急医疗服务相关的研究,将研究的书目信息下载后导入到书目共 现分析系统进行统计分析,并将书目数据中的主题词共现矩阵导入图形聚类工具进行聚类分析。结果 检索 到2 365 篇文献,通过整理,最终得出直升机紧急医疗服务研究的时间分布、国家分布、高频主题词分布,主 题词双向聚类分析共显示出11 个聚类。结论 直升机紧急医疗服务研究热度逐年上升,相关的热点词汇主要 包括:创伤、组织管理、标准、心脏骤停、气管插管、心肌梗死、心肺复苏等。研究热点主要包括:直升机 紧急医疗服务在院外心脏骤停等疾病中应用的可行性;直升机紧急医疗服务救援人员技能培训;直升机紧急 医疗服务气管插管人员技能及插管工具的选择对插管质量的影响;创伤、心肌梗死等疾病直升机紧急医疗服 务的转运效果;直升机紧急医疗服务实施的影响因素;直升机紧急医疗服务相关指南6 个方面。

    Abstract:

    Objective To understand the research progress of international helicopter emergency medical service (HEMS). Methods We searched the studies related to HEMS in PubMed published in recent 10 years. The bibliographic information of the study was downloaded and imported into the Bibliographic Items Co-occurrence Matrix Builder (BICOMB) for classification and statistics, the co-occurrence matrix of subject words of bibliographic data was imported into graph clustering tool (gCLUTO) for clustering analysis. Results The time distribution, country distribution and high-frequency keywords distribution of the research on international HEMS were finally obtained. Two-way clustering analysis of the keywords showed 11 clusters in total, and several research hotspots of HEMS were revealed. Conclusions At present, the hot words related to HEMS mainly include trauma, tissue management, standards, cardiac arrest, endotracheal intubation, myocardial infarction, cardiopulmonary resuscitation, etc. The research focuses mainly include application of HEMS in out-of-hospital cardiac arrest, training of rescue workers’ skills under special circumstances, application of endotracheal intubation in HEMS, the transport efficacy of HEMS in trauma, myocardial infarction and other diseases, the influencing factors of HEMS implementation, and guidelines for HEMS.

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苏盼,李学兰.基于PubMed 数据库的直升机紧急医疗服务 热点的共词聚类分析[J].中国现代医学杂志,2020,(16):89-94

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  • 收稿日期:2020-03-30
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  • 在线发布日期: 2020-08-30
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