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Review of "Global research trends in stem cells for tendon from 1991 to 2020: a bibliometric and visualized study"

Published onDec 18, 2021
Review of "Global research trends in stem cells for tendon from 1991 to 2020: a bibliometric and visualized study"
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Global Research Trends in Stem Cells for Tendon from 1991 to 2020: A Bibliometric and Visualized Study
Description

Abstract Background: Tendinopathy is a disabling musculoskeletal disorder affecting the athletic and general populations. There have been increased studies using stem cells in treating tendon diseases. The aim of this bibliometric and visualized study is to comprehensively investigate the current status and global trends of research in stem cells for tendon. Methods: Publications related to stem cells for tendon from 1991 to 2020 were retrieved from Web of Science. The source data were studied and indexed using a bibliometric methodology. VOS viewer software was used to conduct for the visualized study, including bibliographic coupling, co-authorship, co-citation and co-occurrence analysis and to analyze the publication trends of research in stem cells for tendon. Results: In total, 2492 articles were included. Though the relative research interests decline since 2018, the number of publications increased annually worldwide. The United States made the largest contribution to this field, with the most publications, citations and the highest H-index. The most contributive institutions were University of Pittsburgh, Zhejiang University, Shanghai Jiao Tong University and Chinese University of Hong Kong. The Journal of Orthopaedic Research published the most relative articles. Studies could be classified into five clusters: “animal study”, “tissue engineering”, “clinical study”, “mechanism research” and “stem cells research”, which show a trend of balanced development in this field. Conclusions: The number of publications on stem cells in treating tendon diseases may have reached a platform based on current global trends. The United States made the largest contribution to this field. In addition, according to the inherent changes of hotspots in each cluster and the possibilities of cross-research, the research in stem cells for tendon may exist a balanced development trend.

This paper presents a bibliometric analysis of research on “stem cells for tendon”. I need to emphasize that I have no expertise in this research field. In this review I will focus on the bibliometric aspects of the paper. My comments are listed below.

 

Many of the figures in the paper are hard to read because the font size is too small. A (much) larger font size needs to be used. The VOSviewer visualizations need to be enlarged. Also, to make the VOSviewer visualizations easier to read, I recommend to reduce the number of lines shown in the visualizations. VOSviewer has an option for reducing the number of lines. The authors may also consider making interactive VOSviewer visualizations available online. Links to the online visualizations can then be included in the paper to enable readers to explore the visualizations in their web browser. The ‘Share’ button in VOSviewer can be used to make visualizations available online.

 

The paper includes too many VOSviewer visualizations. My suggestion is to choose the most relevant visualizations and to present only those visualizations in the paper.

 

“the first-rank database for bibliometrics”: Web of Science is indeed a prominent database for bibliometric analysis. However, I don’t think it should be called the “the first-rank database for bibliometrics”. There are several other prominent databases as well.

 

“Two authors (HB Long and ZY Yuan) independently screened and extracted the data entry and collection”: What kind of screening was performed? Can the results of this screening be shared with the reader?

 

I doubt whether the relative research interest (RRI) has much relevance. My understanding is that RRI is calculated by dividing the number of publications included in the analysis by the total number of publications in Web of Science in a particular year. I don’t think the total number of publications in Web of Science is a very relevant benchmark, since this includes publications in fields that have nothing to do with the research area studied in the paper (astronomy, sociology, philosophy, etc.).

 

Most bibliometricians prefer to interpret citations as a measure of scientific impact rather than a measure of quality.

 

“Fig. 2B showed the average citation frequency of top 20 countries.”: This analysis is of little use, since the authors don’t correct for the fact that older publications on average have received more citations than recent publications. My suggestion is to remove the analysis from the paper or to normalize the citation counts for publication year. Bibliometricians typically normalize citation counts for publication year by dividing the number of citations of a publication by the average number of citations of all publications in the same research area and the same year.

 

The analysis of authors might suffer from problems caused by different authors having the same last name and the same initials. If this problem indeed affects the analysis (which is most likely for general names such as ‘CHEN X’), this needs to be acknowledged as a limitation of the analysis.

 

The discussion section repeats a lot of information that was already shared with the reader in the results section. My suggestion is to shorten the discussion section to avoid this repetition.

 

“a platform of studies on this field might be published in the next few years”: I don’t understand this sentence.

 

Make sure to write the names of databases and tools in the correct way, for instance:

‘Social Science Citation Index’ should be ‘Social Sciences Citation Index’

‘VOS viewer’ should be ‘VOSviewer’

‘Pubmed’ should be ‘PubMed’

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