Research features between Urology and Nephrology authors in articles regarding UTI related to CKD, HD, PD, and renal transplantation

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標題:	Research features between Urology and Nephrology authors in articles regarding UTI related to CKD, HD, PD, and renal transplantation
作者:	Tan, Keng-Kok Chien, Tsair-Wei Kan, Wei-Chih Wang, Chen-Yu Chou, Willy Wang, Hsien-Yi
貢獻者:	Chi Mei Hospital Chi Mei Hospital Chung Hua University China Medical University Taiwan Chia Nan University of Pharmacy & Science
關鍵字:	urinary-tract-infections chronic kidney-disease top-cited articles peritoneal-dialysis impact factor hemodialysis metaanalysis association index epidemiology
日期:	2022
上傳時間:	2023-12-11 14:02:54 (UTC+8)
出版者:	LIPPINCOTT WILLIAMS & WILKINS
摘要:	Background: A urinary tract infection (UTI) is one of the most common types of infections affecting the urinary tract. When bacteria enter the bladder or kidney and multiply in the urine, a URI can occur. The urethra is shorter in women than in men, which makes it easier for bacteria to reach the bladder or kidneys and cause infection. A comparison of the research differences between Urology and Nephrology (UN) authors regarding UTI pertaining to the 4 areas (i.e., Chronic Kidney Disease, Hemodialysis, Peritoneal Dialysis, and Renal Transplantation [CHPR]) is thus necessary. We propose and verify 2 hypotheses: CHPR-related articles on UTI have equal journal impact factors (JIFs) in research achievements (RAs) and UN authors have similar research features (RFs). Methods: Based on keywords associated with UTI and CHPR in titles, subject areas, and abstracts since 2013, we obtained 1284 abstracts and their associated metadata (e.g., citations, authors, research institutes, departments, countries of origin) from the Web of Science core collection. There were 1030 corresponding and first (co-first) authors with hT-JIF-indices (i.e., JIF was computed using hT-index rather than citations as usual). The following 5 visualizations were used to present the author's RA: radar, Sankey, time-to-event, impact beam plot, and choropleth map. The forest plot was used to distinguish RFs by observing the proportional counts of keyword plus in Web of Science core collection between UN authors. Results: It was observed that CHPR-related articles had unequal JIFs (chi(2) = 13.08, P = .004, df = 3, n = 1030) and UN departments had different RFs (Q = 53.24, df = 29, P = .004). In terms of countries, institutes, departments, and authors, the United States (hT-JIF = 38.30), Mayo Clinic (12.9), Nephrology (19.14), and Diana Karpman (10.34) from Sweden had the highest hT-JIF index. Conclusion: With the aid of visualizations, the hT-JIF-index and keyword plus were demonstrated to assess RAs and distinguish RFs between UN authors. A replication of this study under other topics and in other disciplines is recommended in the future, rather than limiting it to UN authors only, as we did in this study.
關聯:	MEDICINE, v.101, n.CB2, pp.CC2, pp.-,
显示于类别:	[行政單位] 123

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