Bibliometric analysis of diabetic retinopathy research using optical coherence tomography (2020-2025): A VOSviewer study
Nazmun Nahar, Hrithik Chowdhury, Iffah N. Madzuki, Projjal Das, Mohamad I. Jamaludin, Kangkan Sharma, Rumpa Ghosh, Abul kalam Azad
Abstract
Diabetic retinopathy (DR) is a major cause of vision loss, and Optical Coherence Tomography (OCT) has become an essential imaging tool for its diagnosis and management. With the growing volume of OCT-related DR research, bibliometric analysis offers valuable insights into global publication trends, collaborative networks, and influential contributors. This study utilizes VOSviewer to map and analyze co-authorship patterns in DR-OCT research from 2020 to 2025. A bibliometric analysis was conducted using the search terms "Diabetic Retinopathy AND Tomography AND Optical Coherence" across six major databases: Web of Science, Scopus, PubMed, Dimensions, Lens.org, and Google Scholar, on April 14, 2025, covering publications from 2020 to 2025. English-language articles and review articles were included. Bibliographic data were exported in CSV format and analyzed using VOSviewer (v1.6.10) to generate visual maps for co-authorship, keyword co-occurrence, citation, co-citation, and bibliographic coupling networks, applying link and total link strength attributes. A total of 1,794 documents were retrieved from Web of Science, 743 from Scopus, and 2,685 from PubMed, with additional records from Dimensions, Lens.org, and Google Scholar. Co-authorship analysis revealed strong collaborative networks, with key contributors including Bandello F., Sivaprasad S, and Sadda SR, as well as institutions such as Sun Yat-sen University, which led in publication output. Citation and co-citation maps identified influential authors, journals (e.g., Ophthalmology, JAMA Ophthalmology), and highly cited works, while bibliographic coupling highlighted thematic similarities across documents and countries. Keyword co-occurrence analysis revealed research trends centered on imaging technologies, artificial intelligence, and diabetic macular edema, reflecting the evolving priorities in diabetic retinopathy research utilizing OCT. This analysis highlights key authors, research clusters, and international collaborations driving advancements in DR research using OCT. The findings provide a comprehensive overview of the current research landscape guiding future studies, collaborations, and policy decisions in the field of diabetic eye care.
Keywords
References
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Submitted date:
10/11/2025
Reviewed date:
11/15/2025
Accepted date:
11/17/2025
