Abstract

Thanks to Namin Wei et al for publishing an interesting and well-written bibliometric review about familial hypercholesterolemia1. The authors analyzed and discussed 1617 research documents. It is apparent from the review (and also mentioned in limitation section) that only Web of Science (WoS) was used for data retrieval. Since Scopus is perhaps the largest database in the world, therefore I used it in the present letter. They used CiteSpace and VOSviewer for data analysis. While, i employed R-Studio (Bibliometrix/Biblioshiny) program. Similarly some bibliometric details were lacking (in the earlier paper) and I tried to address in the present letter. For disambiguation I used the same search string i.e. "Familial Hypercholesterolemia" OR "familial hyperlipidemia" OR "familial dyslipidemias" in title-abs-key, and retrieved the data in BibTex format on Oct 27, 2022. The search period was the same i.e. between January 1, 2011 and December, 2021. Based on Scopus record 5537 documents with 115777 total citations and 132 h-index are published. These documents comprised of articles (n=3135), reviews (n=1355), editorials (n=339), notes (n=260), letters (n=229), book chapters (n=72), short surveys (n=58), conference papers (n=50), errata (n=34), data papers (n=2), books (n=1), retracted, and one (n=1), and one undefined document. In all publications 17660 authors have contributed. For the first time, I applied the Lotka law which describes the "n" documents, written by the "n" authors. For example, 13075 authors published only one research document. Similarly 2125, 880, 458, and 278 authors published two, three, four and five research documents, respectively. By applying R Studio, i also decoded some relevant information for example; the authors of single-authored documents were 544, the authors of multi-authored documents were 17116, single-authored documents were 845, documents per author were 0.314, authors per document were 3.19, co-authors per documents were 6.31 and the collaboration index was 3.65.In the same vein, Namin Wei et al presented the top ten authors. For the purpose, they used only two indicators i.e. total number of publications and h-index. However exploring the productivity or influence of the authors is a complex issue. Similarly h-index has its own disadvantages for example it does not cover the length of the service of a particular researcher. Therefore I tried to provide numerical details about m-index and g-index along with total number of publications, citations, and h-index. Based on the number of publications, the data for the top ten authors, universities, countries is presented in supplementary table 1. I also presented the top ten sources with total number of publications, citations, and year of publications in supplementary table 1. While, the list of 17660 authors, 17271 departments, 6746 universities, 111 countries, 1376 journals, and 5537 documents with publications or citations details can be provided on demand. It can be concluded that Namin Wei et al performed bibliometric analysis of 1617 research documents and I did it for 5537 documents. It is apparent from the Scopus data that the number of per publications increased from 2011 to 2021 (except a decrease in 2019). The highest documents were published by the University of Western Australia (n=228), followed by Amsterdam UMC - University of Amsterdam (n=225) and Royal Perth Hospital (n=210). It was also noted that 21 countries (13 from Europe, 3 from Asia, 2 from North America, Australia, Brazil and South Africa) have published at least 100 documents. The present letter identified the most productive researchers, universities and countries, which may foster the international collaboration and exchange. One of the limitations of the present letter is the spelling or common mistakes in authors, and specially institutes or department's names were not addressed. This may alter the citation and ranking details. I also did not perform the co-words analysis which may help in depicting the research focus of these 5537 publications.

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