1.Bibliometric analysis of diabetic retinopathy therapy based on Web of Science database
Shulei MAN ; Yifan ZHANG ; Hanyue XU ; Qing CHEN ; Ming ZHANG
Chinese Journal of Ocular Fundus Diseases 2023;39(3):238-248
Objective:To analyze the trend, hotspots and frontiers of diabetic retinopathy (DR) therapy by bibliometric method.Methods:Data were taken from the Web of Science website of Science Citation Index. Articles from 2017 to 2021, which were related to the therapy of diabetic retinopathy (DR), were included. The bibliometric analysis softwares, VOSviewer and CiteSpace were used to generate and analyze visual representations of the complex data input, including high-frequency keywords, keywords with the strongest citation bursts and co-occurrence networks of keywords.Results:A total of 3,845 articles were included. The amounts of papers published from 2017 to 2021 is 633, 651, 708, 893, and 960 respectively, increasing over years. Chinese scholars published the most articles, followed by the United States. The number of articles funded by the National Natural Science Foundation of China ranks third. There were 47 high-frequency keywords clustered into DR treatment, pathogenesis of DR, diagnosis of DR, Oxidative stress, diabetic macular edema (DME), type 2 diabetes, optical coherence tomography and deep learning. Those keywords were research hotspots and new keywords were constantly emerging. Among the top 11 burst words, the burst values of "intravitreal bevacizumab", "vascular endothelial growth factor (VEGF)", "choroidal neovascularization", "inhibition", and "receptors" were all over 10. Highly cited references showed a significant clustering tendency, which were treatment of DME, review of DR, clinical research of anti-VEGF drug therapy.Conclusions:The amount of paper related to DR therapy is on the rise; the specific treatment methods for the pathogenesis of DR are constantly research hotspots. In addition, formulating treatment strategies to reduce macular edema and other complications of diabetes, applying optical coherence tomography, deep learning and other technologies to improve the efficiency of DR diagnosis and treatment, improve targeted drug delivery systems, and finding new target points were research frontiers.