ArticleBMC ophthalmology2022
Normative data and repeatability for macular ganglion cell layer thickness in healthy Swedish children using swept source optical coherence tomography.
Article in BMC ophthalmology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Comparison of Two Spectral-Domain Optical Coherence Tomographs for Macular Thickness in Romanian Children Reveals Device-Dependent Normative Data and Significant Gender Differences.Diagnostics (Basel, Switzerland) · 2026Article
- Normative retinal thickness values in children, measured by swept-source optical coherence tomography.Medical hypothesis, discovery & innovation ophthalmology journal · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
backgroundOptical coherent tomography (OCT) technology is evolving with improved resolution and accuracy in segmentation between different cell layers in the retina. The ganglion cell layer in the macula region is a window to see what is happening in the visual pathways and a macula OCT is an examination that most children tolerate. This makes updated normative data necessary since variables may differ between different OCT devices and normative data for children is often not presented. The aim of this study was to develop normative data for macular ganglion cell layer thickness in children, measured with swept source OCT, and investigate the repeatability between measurements.
methodsHealthy Swedish children between 4 and 16 years old, with normal refraction, spherical equivalent mean:1.13 (sd:0.66) dioptre and normal visual acuity Logmar, mean: 0,015 (sd:0,05), were examined with swept source OCT. Macula OCT was performed three times in both eyes and the different retinal layers were evaluated.
resultsFifty-eight children were screened for inclusion. Fifty-five children were included in the study, 24 boys and 31 girls. Mean age was 8.9 years. Results from right eyes was analysed. The mean average thickness of macular ganglion cell layer thickness, retinal nerve fibre layer/ganglion cell layer boundary to inner plexiform layer/inner nuclear layer boundary, was 68.0 μm (sd:4.0, range:58-77). There was no correlation with sex or age. Fifty-three children manage to complete two, and 41 children three acceptable measurement and the mean coefficient of variation was low.
conclusionThe ganglion cell layer thickness differs according to which OCT device that is used, and the population examined. This makes normative data essential to accurately interpret results. Swept source OCT of the macula have excellent repeatability and the examination well tolerated in most children making it an investigation useful for diagnosing and following diseases in the optic pathways.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.