Global Research Trends on the Link Between the Microbiome and COPD: A Bibliometric Analysis

微生物群 慢性阻塞性肺病 医学 恶化 文献计量学 肺病 梅德林 图书馆学 免疫学 生物信息学 内科学 生物 生物化学 计算机科学
作者
Daohong Chen,Qian Zeng,Lu Liu,Ziyang Zhou,Wenchuan Qi,Shuguang Yu,Ling Zhao
出处
期刊:International Journal of Chronic Obstructive Pulmonary Disease [Dove Medical Press]
卷期号:Volume 18: 765-783 被引量:1
标识
DOI:10.2147/copd.s405310
摘要

The pathogenesis of chronic obstructive pulmonary disease (COPD) has been studied in relation to the microbiome, providing space for more targeted interventions and new treatments. Numerous papers on the COPD microbiome have been reported in the last 10 years, yet few publications have used bibliometric methods to evaluate this area.We searched the Web of Science Core Collection for all original research articles in the field of COPD microbiome from January 2011 to August 2022 and used CiteSpace for visual analysis.A total of 505 relevant publications were obtained, and the number of global publications in this field is steadily increasing every year, with China and the USA occupying the first two spots in international publications. Imperial College London and the University of Leicester produced the most publications. Brightling C from the UK was the most prolific writer, while Huang Y and Sze M from the USA were first and second among the authors cited. The American Journal of Respiratory and Critical Care Medicine had the highest frequency of citations. The top 10 institutions, cited authors and journals are mostly from the UK and the US. In the ranking of citations, the first article was a paper published by Sze M on changes in the lung tissue's microbiota in COPD patients. The keywords "exacerbation", "gut microbiota", "lung microbiome", "airway microbiome", "bacterial colonization", and "inflammation" were identified as cutting-edge research projects for 2011-2022.Based on the visualization results, in the future, we can use the gut-lung axis as the starting point to explore the immunoinflammatory mechanism of COPD, and study how to predict the effects of different treatments of COPD by identifying the microbiota, and how to achieve the optimal enrichment of beneficial bacteria and the optimal consumption of harmful bacteria to improve COPD.
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