DOI: 10.4103/ijo.ijo_399_23 ISSN: 0301-4738

Bibliometric and visualized analysis of diabetic macular edema

Jin Wei, Yiyang Shu, Yimin Wang, Haiyun Liu
  • Ophthalmology


Our aim was to identify recent research trends on diabetic macular edema (DME) and focus on publications from different countries, institutions, and authors.


We retrieved and analyzed data from January 1, 2003 to December 31, 2022 on the DME research field from the Web of Science Core Collection (WoSCC) database. Microsoft Excel and VOSviewer were applied to perform visualization analysis and evaluate the trends.


A total of 4482 publications were identified, and the annual global publications increased steadily, from 36 to 390, during this period. The United States (1339 publications, 71,754 citations), Johns Hopkins University (176 publications, 17,015 citations), and Bressler NM (76 publications, 9621 citations) were the most influential and productive countries, institutions, and authors, respectively. The top 100 keywords were classified into five clusters: (1) therapy and adverse effects of DME; (2) clinical biomarkers of DME; (3) mechanistic research on DME; (4) improving bioavailability and efficacy; and (5) early diagnosis of diabetic complications. “Diabetic macular edema,” “retinopathy,” “ranibizumab,” and “optical coherence tomography angiography” were the most frequent keywords. Regarding the average appearing years (AAYs) of the keywords, “deep learning” (AAY:2020.83), “optical coherence tomography angiography” (AAY:2019.59), “intravitreal Aflibercept” (AAY:2019.29), and “dexamethasone implant” (AAY:2019.20) were recognized as the hotspots of the DME research area in the short run.


In the past two decades, the United States was in master status in DME research. Although intravitreal drug injection has been the mainstream therapy for a long time, the effectiveness of different drugs, such as dexamethasone, new solutions for drug delivery, such as intravitreal implantation, and more accurate tools for the classification and follow-up of DME patients, such as deep learning systems, are still research hotspots.

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