ArticleFrontiers in cell and developmental biology2025
Comparative analysis of retinal vascular structural parameters in populations with different glucose metabolism status based on color fundus photography and artificial intelligence.
Article in Frontiers in cell and developmental biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Vitreoretinal disease detection using artificial intelligence: a systematic review and meta-analysis.International ophthalmology · 2026Pooled it
- Macular Choriocapillaris and Retinal Microvascular Alterations Across the Prediabetes-Early Type 2 Diabetes Continuum.Investigative ophthalmology & visual science · 2026Article
- Artificial intelligence assisted quantitative analysis of fundus structural and vascular alterations reveals fundus tessellation as a robust biomarker of myopia severity.Frontiers in cell and developmental biology · 2026Article
- Artificial intelligence-based quantitative analysis of interocular retinal vascular differences in school-age children with mild to moderate anisometropia.Frontiers in medicine · 2026Article
- Deep learning-driven approach for cataract management: towards precise identification and predictive analytics.Frontiers in cell and developmental biology · 2025Review
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Measure and analyze retinal vascular parameters in individuals with varying glucose metabolism, explore preclinical retinal microstructure changes related to diabetic retinopathy (DR), and assess glucose metabolism's impact on retinal structure. Methods: The study employed a cross-sectional design encompassing a 4-year period from 2020 to 2024. Fundus photographs from 320 individuals (2020-2024) were categorized into non-diabetes, pre-diabetes, type 2 diabetes mellitus (T2DM) without DR, and T2DM with mild-to-moderate non-proliferative DR (NPDR) groups. An artificial intelligence (AI)-based automatic measurement system was used to quantify retinal blood vessels in the fundus color photographic images, enabling inter-group parameter comparison and analysis of significant differences. Results: Between January 2020 and June 2024, fundus color photographs were collected from 320 individuals and categorized into four groups: non-diabetes (n = 54), pre-diabetes (n = 71), T2DM without overt DR (n = 144), and T2DM with mild-to-moderate NPDR (n = 51). In pairwise comparisons among individuals with pre-diabetes, T2DM without DR, and T2DM with mild-to-moderate NPDR. Fasting blood glucose (FBG), glycated hemoglobin (HbA1c), systolic blood pressure (SBP), and diastolic blood pressure (DBP) were significantly different ( Conclusion: In individuals diagnosed with T2DM, specific retinal vascular parameters, such as branch_avg_v and vessel_density, demonstrate a significant correlation with mild-to-moderate NPDR. These parameters hold promise as preclinical biomarkers for detecting vascular abnormalities associated with DR.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.