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Approach for a Clinically Useful Comprehensive Classification of Vascular and Neural Aspects of Diabetic Retinal Disease

Overview
Specialty Ophthalmology
Date 2018 Jan 27
PMID 29372250
Citations 40
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Abstract

The Early Treatment Diabetic Retinopathy Study (ETDRS) and other standardized classification schemes have laid a foundation for tremendous advances in the understanding and management of diabetic retinopathy (DR). However, technological advances in optics and image analysis, especially optical coherence tomography (OCT), OCT angiography (OCTa), and ultra-widefield imaging, as well as new discoveries in diabetic retinal neuropathy (DRN), are exposing the limitations of ETDRS and other classification systems to completely characterize retinal changes in diabetes, which we term diabetic retinal disease (DRD). While it may be most straightforward to add axes to existing classification schemes, as diabetic macular edema (DME) was added as an axis to earlier DR classifications, doing so may make these classifications increasingly complicated and thus clinically intractable. Therefore, we propose future research efforts to develop a new, comprehensive, and clinically useful classification system that will identify multimodal biomarkers to reflect the complex pathophysiology of DRD and accelerate the development of therapies to prevent vision-threatening DRD.

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References
1.
Bursell S, Cavallerano J, Cavallerano A, Clermont A, Aiello L, Aiello L . Stereo nonmydriatic digital-video color retinal imaging compared with Early Treatment Diabetic Retinopathy Study seven standard field 35-mm stereo color photos for determining level of diabetic retinopathy. Ophthalmology. 2001; 108(3):572-85. DOI: 10.1016/s0161-6420(00)00604-7. View

2.
Moran C, Beare R, Phan T, Starkstein S, Bruce D, Romina M . Neuroimaging and its Relevance to Understanding Pathways Linking Diabetes and Cognitive Dysfunction. J Alzheimers Dis. 2017; 59(2):405-419. DOI: 10.3233/JAD-161166. View

3.
COGAN D, Toussaint D, Kuwabara T . Retinal vascular patterns. IV. Diabetic retinopathy. Arch Ophthalmol. 1961; 66:366-78. DOI: 10.1001/archopht.1961.00960010368014. View

4.
Hammes H, Lin J, Renner O, Shani M, Lundqvist A, Betsholtz C . Pericytes and the pathogenesis of diabetic retinopathy. Diabetes. 2002; 51(10):3107-12. DOI: 10.2337/diabetes.51.10.3107. View

5.
Martin D, Maguire M . Treatment choice for diabetic macular edema. N Engl J Med. 2015; 372(13):1260-1. DOI: 10.1056/NEJMe1500351. View