Global trends and performances in diabetic retinopathy studies: A bibliometric analysis

Abstract

ObjectiveThe objective of this study is to conduct a comprehensive bibliometric analysis to identify and evaluate global trends in diabetic retinopathy (DR) research and visualize the focus and frontiers of this field.MethodsDiabetic retinopathy-related publications from the establishment of the Web of Science (WOS) through 1 November 2022 were retrieved for qualitative and quantitative analyses. This study analyzed annual publication counts, prolific countries, institutions, journals, and the top 10 most cited literature. The findings were presented through descriptive statistics. VOSviewer 1.6.17 was used to exhibit keywords with high frequency and national cooperation networks, while CiteSpace 5.5.R2 displayed the timeline and burst keywords for each term.ResultsA total of 10,709 references were analyzed, and the number of publications continuously increased over the investigated period. America had the highest h-index and citation frequency, contributing to the most influence. China was the most prolific country, producing 3,168 articles. The University of London had the highest productivity. The top three productive journals were from America, and Investigative Ophthalmology Visual Science had the highest number of publications. The article from Gulshan et al. (2016; co-citation counts, 2,897) served as the representative and symbolic reference. The main research topics in this area were incidence, pathogenesis, treatment, and artificial intelligence (AI). Deep learning, models, biomarkers, and optical coherence tomography angiography (OCTA) of DR were frontier hotspots.ConclusionBibliometric analysis in this study provided valuable insights into global trends in DR research frontiers. Four key study directions and three research frontiers were extracted from the extensive DR-related literature. As the incidence of DR continues to increase, DR prevention and treatment have become a pressing public health concern and a significant area of research interest. In addition, the development of AI technologies and telemedicine has emerged as promising research frontiers for balancing the number of doctors and patients.

A multidomain bio-inspired feature extraction and selection model for diabetic retinopathy severity classification: an ensemble learning approach

“…It is also estimated that the number of DR patients worldwide is predicted to rise from 103.12 million to 160.5 million between 2020 and 2045, with 44.82 million individuals reporting visual issues. This establishes the role of DR in the potential development of a huge global, economic, and public health problem 2 . According to the International Diabetes Federation (IDF) 3 , a total of 537 million individuals in the world between the ages of 20 and 79 make up 10% of the world's population are estimated to have diabetes mellitus in 2021.…”

Bibliometric and visualized analysis of DME from 2012 to 2022

“…Previous studies on DR had shown that the development and validation of deep learning algorithms have made major breakthroughs in the early diagnosis of DR, and were also at the forefront of current DR Research. [ 49 ] It showed the importance of deep learning and AI in ophthalmology research, and the integration of multiple disciplines can better promote the development of ophthalmology.…”

Stachydrine Relieved the Inflammation and Promoted the Autophagy in Diabetes Retinopathy Through Activating the AMPK/SIRT1 Signaling Pathway

“… 26 It is estimated that the number of DR patients will increase to 247.3 million by 2030. 27 At present, more and more studies are aimed at finding new targets for DR drug therapy, and further exploring the therapeutic effects and mechanisms of new drugs. 28 , 29 Here, we demonstrated that STA effectively relieved the inflammation and promoted the autophagy in DR progression in vivo and in vitro through activating the AMPK/SIRT1 signaling pathway.…”