Zhang Zhongheng, Van Poucke Sven, Goyal Hemant, Rowley Daniel D, Zhong Ming, Liu Nan
Department of Emergency Medicine, Sir Run-Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310016, China.
Department of Anesthesiology, Critical Care, Emergency Medicine and Pain Therapy, Genk, Belgium.
J Thorac Dis. 2018 Apr;10(4):2437-2447. doi: 10.21037/jtd.2018.03.178.
The bibliometric analysis has been performed on several topics in critical care medicine (CCM) focusing on top 100 cited articles, but the analysis on CCM literature as a whole is missing. The present study aimed to perform a complete bibliometric analysis in the field of CCM.
An electronic search of the Scopus database was performed on Feb 13, 2018. The search strategy involved core terms related to CCM. The top 2,000 most cited articles in the field of CCM were included in the analysis. Descriptive statistics on these top-cited articles, country distributions, and journals are reported. Individual author's productivity was assessed with the Lotka's law. Co-occurrence of keywords was visualized with the Fruchterman-Reingold layout. The Walktrap algorithm was employed for clustering analysis.
A total of 2,000 documents were included in the analysis with median citations of 386 times [interquartile range (IQR): 308-562 times]. The most cited article was the original paper that described the Acute Physiology and Chronic Health Evaluation (APACHE) II score. The included articles were published in 411 journals. The median number of documents published in one journal was 1, and the mean number was 4.9, indicating a skewed distribution. The maximum number of publications was 217 in CCM. Author's productivity profile was significantly different from the Lotka's law (P=0.001), with n and C values of 2.8 and 0.52, respectively. Fruchterman-Reingold network plot showed that studies involving human subject were the most common literature type. Sepsis was a major research topic that co-occurred with keywords such as disease severity, nonhuman, risk assessment and practice guideline.
The study performed bibliometric analyses of 2,000 top-cited articles in CCM. The most cited article was the one which developed the APACHE II score. Author's productivity was significantly different from the Lotka's law.
针对重症医学（CCM）的多个主题进行了文献计量分析，重点关注被引次数排名前100的文章，但对CCM文献整体的分析尚付阙如。本研究旨在对CCM领域进行全面的文献计量分析。
于2018年2月13日对Scopus数据库进行电子检索。检索策略涉及与CCM相关的核心术语。CCM领域中被引次数排名前2000的文章纳入分析。报告了这些高被引文章的描述性统计数据、国家分布和期刊情况。采用洛特卡定律评估个体作者的生产力。使用弗鲁彻曼-赖因戈尔德布局对关键词共现情况进行可视化展示。采用沃克特拉普算法进行聚类分析。
共2000篇文献纳入分析，中位被引次数为386次[四分位间距（IQR）：308 - 562次]。被引次数最多的文章是描述急性生理与慢性健康状况评价（APACHE）II评分的原始论文。纳入的文章发表在411种期刊上。一本期刊发表文献的中位数为1篇，平均数为4.9篇，表明分布不均衡。CCM领域发表文献数量最多的为217篇。作者生产力分布与洛特卡定律显著不同（P = 0.001），n值和C值分别为2.8和0.52。弗鲁彻曼-赖因戈尔德网络图显示，涉及人类受试者的研究是最常见的文献类型。脓毒症是一个主要研究主题，与疾病严重程度、非人类、风险评估和实践指南等关键词共同出现。
本研究对CCM领域2000篇高被引文章进行了文献计量分析。被引次数最多的文章是开发APACHE II评分的那篇。作者生产力与洛特卡定律显著不同。
