ArticleJournal of personalized medicine2021
Characterization of Risk Profiles for Diabetic Retinopathy Progression.
Article in Journal of personalized medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07417410 (Analysis of DR Progression to Identify Risks and Need for Treatment), which is not on this map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Analysis of DR Progression to Identify Risks and Need for Treatment
Who cites it
6 citing papers in PubMed, 15 citations in OpenAlex.
- One-Year Progression of Capillary Nonperfusion in Nonproliferative Diabetic Retinopathy Using Noninvasive Imaging: The CHART Study.Translational vision science & technology · 2026Observational
- Characterization and Automatic Discrimination between Predominant Hypoperfusion and Hyperperfusion Stages of NPDR.Journal of personalized medicine · 2024Article
- Comparison of Widefield OCT Angiography Features Between Severe Non-Proliferative and Proliferative Diabetic Retinopathy.Ophthalmology and therapy · 2024Article
- Different Risk Profiles for Progression of Nonproliferative Diabetic Retinopathy: A 2-Year Study.Ophthalmology and therapy · 2023Article
- Age-Related Macular Degeneration and Diabetic Retinopathy.Journal of personalized medicine · 2022Article
- Association between Neurodegeneration and Macular Perfusion in the Progression of Diabetic Retinopathy: A 3-Year Longitudinal Study.Ophthalmologica. Journal international d'ophtalmologie. International journal of ophthalmology. Zeitschrift fur Augenheilkunde · 2022Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetic retinopathy (DR) is a frequent complication of diabetes and, through its vision-threatening complications, i.e., macular edema and proliferative retinopathy, may lead to blindness. It is, therefore, of major relevance to identify the presence of retinopathy in diabetic patients and, when present, to identify the eyes that have the greatest risk of progression and greatest potential to benefit from treatment. In the present paper, we suggest the development of a simple to use alternative to the Early Treatment Diabetic Retinopathy Study (ETDRS) grading system, establishing disease severity as a necessary step to further evaluate and categorize the different risk factors involved in the progression of diabetic retinopathy. It needs to be validated against the ETDRS classification and, ideally, should be able to be performed automatically using data directly from the examination equipment without the influence of subjective individual interpretation. We performed the characterization of 105 eyes from 105 patients previously classified by ETDRS level by a Reading Centre using a set of rules generated by a decision tree having as possible inputs a set of metrics automatically extracted from Swept-source Optical Coherence Tomography (SS-OCTA) and Spectral Domain- OCT (SD-OCT) measured at different localizations of the retina. When the most relevant metrics were used to derive the rules to perform the organization of the full pathological dataset, taking into account the different ETDRS grades, a global accuracy equal to 0.8 was obtained. In summary, it is now possible to envision an automated classification of DR progression using noninvasive methods of examination, OCT, and SS-OCTA. Using this classification to establish the severity grade of DR, at the time of the ophthalmological examination, it is then possible to identify the risk of progression in severity and the development of vision-threatening complications based on the predominant phenotype.
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Registered trials
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