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ABSTRACT: Purpose
To identify latent phenotypic subgroups of diabetic macular edema (DME) using artificial intelligence-based OCT metrics and evaluate whether treatment responses to anti-VEGF and dexamethasone (DEX) therapies differ across these phenotypic clusters.Methods
Retrospective study including 114 eyes (82 patients) with treatment-naïve DME. Quantitative OCT metrics, including intraretinal fluid (IRF) and subretinal fluid volumes, IRF % distribution within central 0-1, 1-3, and 3-6 mm, hyperreflective foci counts, and ellipsoid zone (EZ) % disruption, were analyzed before and after treatment.Main outcome measures
Gaussian finite mixture modeling was used to identify distinct DME subgroups. Changes in visual acuity (VA) and OCT parameters following anti-VEGF or DEX th
SUBMITTER: Cicinelli MV
PROVIDER: S-EPMC12686911 | biostudies-literature | 2026 Jan
REPOSITORIES: biostudies-literature