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A New Approach to Staging Diabetic Eye Disease: Staging of Diabetic Retinal Neurodegeneration and Diabetic Macular Edema

The goal of this review was to summarize the current level of evidence on biomarkers to quantify diabetic retinal neurodegeneration (DRN) and diabetic macular edema (DME). With advances in retinal diagnostics, we have more data on patients with diabetes than ever before. However, the staging system...

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Bibliographic Details
Published in:Ophthalmology science (Online) 2024-05, Vol.4 (3), p.100420
Main Authors: Channa, Roomasa, Wolf, Risa M, Simo, Rafael, Brigell, Mitchell, Fort, Patrice, Curcio, Christine, Lynch, Stephanie, Verbraak, Frank, Abramoff, Michael D
Format: Article
Language:English
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Summary:The goal of this review was to summarize the current level of evidence on biomarkers to quantify diabetic retinal neurodegeneration (DRN) and diabetic macular edema (DME). With advances in retinal diagnostics, we have more data on patients with diabetes than ever before. However, the staging system for diabetic retinal disease is still based only on color fundus photographs and we do not have clear guidelines on how to incorporate data from the relatively newer modalities into clinical practice. In this review, we use a Delphi process with experts to identify the most promising modalities to identify DRN and DME. These included microperimetry, full-field flash electroretinogram, spectral-domain OCT, adaptive optics, and OCT angiography. We then used a previously published method of determining the evidence level to complete detailed evidence grids for each modality. Our results showed that among the modalities evaluated, the level of evidence to quantify DRN and DME was highest for OCT (level 1) and lowest for adaptive optics (level 4). For most of the modalities evaluated, prospective studies are needed to elucidate their role in the management and outcomes of diabetic retinal diseases. Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
ISSN:2666-9145
2666-9145
DOI:10.1016/j.xops.2023.100420