Evidence map›Paper›PMID 42908507›Full record

ArticleFrontiers in ophthalmology2026

Structural changes in the retinal layers of patients with Steinert disease.

Beatriz Cordón, Beatriz Pardiñas, Mónica Hernández, María Jesús Rodrigo, Elvira Mayordomo, Luis Emilio Pablo, Elena García-Martin

Abstract read
In one paragraph

Article in Frontiers in ophthalmology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Beatriz CordónMiguel Servet Ophthalmology Research and Innovation Group (GIMSO), Aragon Institute for Health Research (IIS Aragón), University of Zaragoza, Zaragoza, Spain.
Beatriz PardiñasDepartment of Neurology, Miguel Servet University Hospital, Zaragoza, Spain.
Mónica HernándezDepartment of Computer Science, University of Zaragoza, Zaragoza, Spain.
María Jesús RodrigoMiguel Servet Ophthalmology Research and Innovation Group (GIMSO), Aragon Institute for Health Research (IIS Aragón), University of Zaragoza, Zaragoza, Spain.
Elvira MayordomoDepartment of Computer Science, University of Zaragoza, Zaragoza, Spain.
Luis Emilio PabloMiguel Servet Ophthalmology Research and Innovation Group (GIMSO), Aragon Institute for Health Research (IIS Aragón), University of Zaragoza, Zaragoza, Spain.
Elena García-MartinMiguel Servet Ophthalmology Research and Innovation Group (GIMSO), Aragon Institute for Health Research (IIS Aragón), University of Zaragoza, Zaragoza, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The purpose of this study was to evaluate the different retinal layers of the posterior pole protocol and peripapillary areas in optical coherence tomography (OCT) to identify significant changes attributable to Steinert disease. Methods: We analyzed 128 eyes of healthy control subjects and 79 eyes of patients with Steinert disease. We performed the posterior pole and Nsite analytics peripapillary protocols on all subjects and compared thicknesses in the retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), retinal pigment epithelium (RPE), and complete retina (RETINA). Results: Patients with Steinert disease showed significant alterations in retinal layer thickness compared with age-matched controls. Overall, a generalized thickening of retinal layers was observed; significant thickening of the RNFL was also found in the temporal area of the optic nerve and in the papillomacular bundle, which comprises the retinal ganglion cell axons connecting the macula with the optic nerve. Conclusions: Steinert disease is associated with retinal structural alterations in retinal layer structure, OCT may provide potential structural markers of retinal involvement in Steinert disease.

Indexed as

ganglion cellsOCToptical coherence tomographyretinal layersretinal nerve fiber layerSteinert disease

Identifiers

PMID42908507
PMCPMC13682967

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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.