Bibliometric Analysis of Renal Fibrosis in Diabetic Kidney Disease From 1985 to 2020 - Zhang, Yuqing; Jin, De; Duan, Yingying; Zhang, Yuehong; Duan, Liyun; Lian, Fengmei; Tong, Xiaolin (Frontiers in Public Health, 2022)
Background: Diabetic renal fibrosis (DRF) is an irreversible renal pathological change in the end-stage of diabetic kidney disease (DKD), which plays a significant role in the development and deterioration of the disease. However, data for bibliometric analysis of renal fibrosis in DKD is currently missing. This study aimed to provide a comprehensive and visualized view of DRF research and lay the foundation for further studies. Materials and Methods: Firstly, the data was collected from the Web of Science Core Collection (WoSCC) database. Secondly, the Web of Science analytic tool was performed to analyze publication years, authors, countries/regions, organizations, and citation frequency. Finally, CiteSpace was employed to construct a visualization bibliometric network to reveal the emerging trends and hotspots of DRF. Results: A total of 3,821 publications from 1985 to 2020 were included in this study. The number of publications has maintained a growth trend since 2003. Cooper, M.E. is the most prolific author in this field, and the American Journal of Physiology-Renal Physiology ranking as first place compared with other journals. In terms of the number of publications, China contributed the most to DRF. Monash University is the organization that published the most papers. The top 5 clusters of keyword co-appearance are “chronic kidney disease”, “primary biliary cirrhosis”, “receptor”, “TGF-beta”, “renal tubulointerstitium”. The top 5 clusters of reference co-citation are “microRNAs”, “bone morphogenetic protein”, “hypertrophy”, “glomerulosclerosis”, “diabetic kidney disease”. The strongest citation burst of keyword is “diabetic kidney disease” and the strongest burst of cited reference is “Meng XM, 2016”. Conclusions: The present study analyzed the research hotspots, frontiers, and development trend of DRF and have important implications for future research.