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采用共词聚类法分析近6年《中国小儿急救医学》杂志研究热点

Hot spots analysis of Chinese Pediatric Emergency Medicine based on co-words cluster analysis
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摘要 目的研究《中国小儿急救医学》近年发表文献的研究热点。方法选取万方数据库收录的《中国小儿急救医学》2006年至2011年发表的论文为基本数据来源,挑选有关键词的1194篇文献,从中逐一抽出4054个关键词。采用书目共现分析系统对关键词进行词频统计和共现分析,利用SPSS11.5软件对共词矩阵进行聚类分析。结果新生儿、早产儿、手足口病、机械通气、脓毒症、先天性心脏病是排在前10位的高频关键词。聚类分析关系图显示,《中国小儿急救医学》近6年发表文章的研究热点主要集中在以下8个方面:手足口病、脓毒性休克的预后影响因素、急性肺损伤和急性呼吸窘迫综合征、新生儿窒息导致的缺氧缺血性脑病、早产儿疾病、婴幼儿先天性心脏病合并重症肺炎及心力衰竭的治疗、儿童重症监护病房内获得性感染的病原菌及耐药性分析、脓毒症。结论通过关键词共词聚类分析法,探明了我刊近6年发表论文的主体研究规律和方向。 Objective To investigate the literature research focus of Chinese Pediatric Emergency Medicine. Methods The papers published in Chinese Pediatric Emergency Medicine from 2006 to 2011 and indexed by wanfang database served as the basic data sources. Four thousands and fifty-four keywords were collected from 1194 literature. Keyword frequency statistics and the co-occurrence analysis were made by u- sing bibliographic item co-occurrence matrix builder, and cluster analysis was made using SPSS 11.5 soft- ware. Results Newborns,premature,hand,foot and mouth disease,mechanical ventilation,sepsis,congenital heart disease was the top 10 high-frequency keywords. Cluster analysis diagram showed the research focus from articles published in Chinese Pediatric Emergency Medicine for the past six years, which included: (1) hand,foot and mouth disease; (2) prognostic factors for septic shock; (3) acute lung injury and acute respiratory distress syndrome; (4) neonatal asphyxia induced hypoxic-ischemic encephalopathy; ( 5 ) the dis- ease of premature infants ; (6) the treatment of congenital heart disease complicated with severe pneumonia and heart failure ; (7) the pathogens and drug resistance analysis of pediatric intensive care unit-acquired infection ; ( 8 ) sepsis. Conclusion The main study law and direction of Chinese Pediatric Emergency Medicine in the past six years are proved by keyword co-words cluster analysis.
出处 《中国小儿急救医学》 CAS 2013年第3期295-298,共4页 Chinese Pediatric Emergency Medicine
关键词 关键词 共词聚类分析 研究热点 Keywords Co-words cluster analysis Research focus
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