![]() Objective To determine whether baseline or early change in the novel spectral domain–optical coherence tomography (SD-OCT) parameter disorganization of the retinal inner layers (DRIL) is predictive of VA in eyes with center-involved DME.ĭesign, Setting, and Participants At a tertiary care referral center for diabetic eye disease, a retrospective, longitudinal cohort study obtained demographics, VA, and SD-OCT images from baseline, 4-month, and 8-month visits in 96 participants (120 eyes) with diabetes mellitus and baseline center-involved DME (SD-OCT central subfield thickness, ≥320 µm for men and ≥305 µm for women). Importance Biomarkers that predict future visual acuity (VA) in eyes with baseline diabetic macular edema (DME) would substantively improve risk assessment, management decisions, and selection of eyes for clinical studies targeting DME. Shared Decision Making and Communication.Scientific Discovery and the Future of Medicine.Health Care Economics, Insurance, Payment.Clinical Implications of Basic Neuroscience.Challenges in Clinical Electrocardiography.Avg DRIL indicates the average DRIL extent in the 1-mm foveal area of 7 central B-scans COSTs, cone outer segment tips SRF, subretinal fluid and Δ, change. Variables in the predictive model included changes in DRIL extent, external limiting disruption, and VA during the first 4 months after baseline. ![]() ![]() D, Scatterplot of actual change in logMAR VA during 8 months vs predicted change in logMAR VA during 8 months. Independent variables included in B and C were those that were statistically significant in bivariate linear regression. C, Change in logMAR VA during 8 months vs change in SD-OCT parameters during 4 months, adjusted for baseline logMAR VA. ![]() B, Change in logMAR VA during 8 months vs change in SD-OCT parameters during 8 months, adjusted for baseline logMAR VA. A, Baseline logarithm of the minimum angle of resolution (logMAR) VA vs baseline SD-OCT parameters, with central subfield thickness (CST) included as a parameter of a priori interest with regard to VA. Forest plots show the results from multivariate backward elimination linear regression. ![]()
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