ArticleJournal of clinical medicine2023
Normative Data for Macular Thickness and Volume for Optical Coherence Tomography in a Diabetic Population without Maculopathies.
Article in Journal of clinical medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 6 citations in OpenAlex.
- Analysis of Aqueous Interleukin-6 in Diabetic Retinopathy: A Prospective, Controlled Trial of 328 Eyes.Ophthalmology. Retina · 2026Article
- Real-World Outcomes After Switch From Aflibercept to Faricimab in Eyes With Diabetic Macular Edema.Investigative ophthalmology & visual science · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
purposeThe purpose was to establish normative data for the macular thicknesses and volume using spectral-domain optical coherence tomography (SD-OCT) in a diabetic population without maculopathies for use as a reference in diabetic retinopathy (DR) and diabetic macular edema screening programs.
methodsThis was an observational study nested in a cohort of diabetics from a telemedicine DR screening program. Each patient underwent SD-OCT centered on the fovea. Macular thickness and volume were described and compared using the built-in normative database of the device. Quantile regression models for the 97.5% percentile were fitted to evaluate the predictors of macular thickness and volume.
resultsA total of 3410 eyes (mean age, 62.25 (SD, 0.22) years) were included. Mean (SD) central subfield thickness (CST) was 238.2 (23.7) µm, while center thickness (CT), average thickness (AT), and macular volume (MV) were 205.4 (31.6) µm, 263.9 (14.3) µm, and 7.46 (0.40) mm
conclusionsAll ETDRS sectors were thinner in patients with diabetes than in the reference population, except for the CST, which was the most stable parameter that only changed with sex. The upper cutoff limit to detect diabetic macular edema (DME) was different from that of the reference population and was influenced by conditions related to diabetes, such as DR. Therefore, specific normative data for diabetic patients should be used for the screening and diagnosis of DME using SD-OCT.
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