Using the Alluvial diagram to display variable characteristics for COVID-19 patients and research achievements on the topic of COVID-19, epidemiology, pathogenesis, and vaccine (CEPV): Bibliometric analysis.

BACKGROUND: An Alluvial diagram illustrates the flow of values from one set to another. Edges (or links/connections) are the connections between nodes (or actors/ vertices). There has been an increase in the use of Alluvial deposits in medical research in recent years. However, there was no illustration of such research on the way to draw the Alluvial for the readers. Our objective was to demonstrate how to draw the Alluvial in Microsoft Excel by using 2 examples, including variable characteristics for COVID-19 patients and research achievements (RAs) on the topic of COVID-19, epidemiology, pathogenesis, and vaccine (CEPV), and provide an easy and friendly method of drawing the Alluvial in MS Excel. METHODS: Blood samples were collected and analyzed from 485 infected individuals in Wuhan, China. An operational decision tree and 2 Alluvial diagrams were shown to be capable of identifying variable characteristics in COVID-19 patients. A second example is the 100 top-cited articles downloaded from the Web of Science core collection (WoSCC) on the CEPV topic. On the Alluvial diagram, the mean citations (=citations/publications) and x-index were used to identify the top 5 members with the highest RAs in each entity (country, institute, journal, and research area). Two examples (i.e., blood samples taken from 485 infected individuals in Wuhan, China, and 100 top-cited articles on the CEPV topic) were illustrated and compared with traditional visualizations without flow relationships between nodes. RESULTS: The top members in entities with the x-index are U Arab Emirates (242), Jama-J. Am. Med. Assoc. (27.18), Lancet (58.34), San Francisco Va Med (178), and Chaolin Huang (189) in countries, institutes, departments, and authors, respectively. The most cited article with 1315 citations was written by Huang and his colleagues and published by Lancet in 2021. CONCLUSION: This study generates several Alluvial diagrams as demonstrations. The tutorial material and MP4 video provided in the Excel module allow readers to draw the Alluvial on their own in an easy and friendly manner.

Using Rasch KIDMAP to identify whether China dominates the research area of computer science (CS) based on the specialization index of article citations: Bibliometric analysis.

BACKGROUND: Scientific comparative advantage is measured by using a specialization index (SI) of article citations. The profile data have been published in the literature. However, no such research has been conducted to determine which countries dominate the field of computer science (CS) (subject category [SC]) using the SI. A KIDMAP in the Rasch model has been applied to the display of individual student performance in school. Based on the SI of article citations, we used KIDMAP to determine whether China dominates the field of CS. METHODS: The data were derived from published research in the Web of Science, which included 199 countries and 254 subject categories (SC, between 2010 and 2019). A total of 96 SC related to biomedicine were extracted. We examined 7 factors associated with CS using exploratory factor analysis. Based on the SI in CS under the Rasch model, 1-dimensional SCs on CS were displayed on Wright Maps and KIDMAPs. An analysis of the dominance of CS in China was presented on the basis of a scatter plot. RESULTS: Our findings indicate that (1) CS domains are divided into 2 groups (traditional and advanced domains); (2) no evidence has been found that China dominates CS; based on SI indicators, China was ranked third with --2.62 and 0.79 logits after Taiwan and Slovenia (-(-2.62 and 9.24 logits in Factors 1 and 2) in the period from 2010 to 2019. CONCLUSIONS: There is insufficient evidence to demonstrate that China has a dominant role over other countries/regions despite ranking third in CS. In future studies, it is recommended to include a KIDMAP visual to assess dominant roles in other areas of research, rather than to confine ourselves to CS as we did in this study.

Necrotizing Fasciitis Caused by Inconspicuous Infection of Aeromonas hydrophila in an Immunocompromised Host.

We present a case of serious necrotizing fasciitis due to Aeromonas hydrophila without a suggestive history of routes of pathogen invasion in a 60-year-old male. Despite prompt broad-spectrum antibiotic and extensive surgical therapies, the patient died within 72 hours following initial presentation. Our experience suggests clinicians be highly alert to the disease when an immunocompromised patient featured fulminant soft-tissue infection in the endemic area.