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The bigger picture: The history of antibiotics and antimicrobial resistance displayed by scientometric data

机译:更大的图景:科学计量数据显示的抗生素和抗菌素耐药性历史

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Monitoring the rapid global spread of antimicrobial resistance requires an over-regional and fast surveillance tool. Data from major surveillance studies based on aggregated results of selected sentinel laboratories or retrospective strain collections are not available for the whole scientific community and are limited by time and region. Thus, we tested an alternative approach to monitor resistance trends by automated semantic and scientometric analysis of all (>100000) related PubMed entries. A semantic search was done using 'Gene Ontology' and MeSH vocabulary and additional search terms for further data refinement. Data extraction was performed using the semantic search engine 'GoPubMed'. The timely relationship between introduction of novel β-lactam antibiotic classes into the market and emergence of respective resistance was investigated using nearly 22 300 publications over the last 70 years. Further analysis was done with around 54 000 publications related to 'infectious diseases' and an additional 50 000 publications related to 'antimicrobial resistance' to estimate current trends in publication interest regarding resistance development since 1940. Scientometric results were compared with data from the major surveillance network EARS-Net. Furthermore, the relationship between micro-organism, year and antibiotic market introduction was investigated for eight key antibiotics using nearly 37 500 publications. Owing to influencing factors such as availability of alternative antibiotics, scientometric analysis correlated only partly with resistance development. However, it provides a fast, reliable and global overview of the clinical and public health importance of a specific resistance including the period of the 1940s-1980s, when resistance surveillance studies were not yet established.
机译:监测抗菌素耐药性在全球范围内的快速传播需要一个跨区域的快速监测工具。基于选定前哨实验室或回顾性菌株收集的汇总结果的主要监视研究数据,并非整个科学界都能获得,并且受到时间和地区的限制。因此,我们测试了通过对所有(> 100000)相关PubMed条目进行自动语义和科学计量分析来监视耐药性趋势的替代方法。使用“基因本体”和MeSH词汇以及其他搜索词进行语义搜索,以进一步完善数据。使用语义搜索引擎“ GoPubMed”执行数据提取。在过去70年中,使用近22 300种出版物调查了新型β-内酰胺类抗生素投放市场与相应耐药性出现之间的及时关系。对与“传染病”有关的约54 000种出版物和与“抗药性”有关的另外5万种出版物进行了进一步分析,以估计自1940年以来有关耐药性发展的出版物兴趣的当前趋势。将科学计量学的结果与主要监测的数据进行了比较。网络EARS-Net。此外,使用近37 500种出版物研究了8种主要抗生素的微生物,年份和抗生素市场引入之间的关系。由于诸如替代抗生素的可获得性等影响因素,科学计量分析仅部分与耐药性发展相关。但是,它提供了快速,可靠和全面的特定耐药性在临床和公共卫生重要性方面的概述,包括1940年代至1980年代,当时还没有建立耐药性监测研究。

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