Evidence map›Paper›PMID 28566961›Full record

ArticleNoro psikiyatri arsivi2017

Retinal Nerve Fiber Layer Thickness Measurement by Spectral-Domain Optical Coherence Tomography in Patients with Major Depressive Disorder.

İpek Sönmez, Ferdi Köşger, Ümit Aykan

Open access · greenAbstract read
In one paragraph

Article in Noro psikiyatri arsivi, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
0.9field-weighted citation impact, top 23% of its field
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

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 38 citations in OpenAlex.

  1. Retinal sublayer changes in cases with Alzheimer's disease and depression.Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie · 2026
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  11. Retinal correlates of psychiatric disorders.Therapeutic advances in chronic disease · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

İpek SönmezDepartment of Psychiatry, Near East University School of Medicine, Nicosia, Turkish Republic of Northern Cyprus.
Ferdi KöşgerDepartment of Psychiatry, Eskişehir Osmangazi University School of Medicine, Eskişehir, Turkey.
Ümit AykanDepartment of Ophtalmology, Bahçeşehir University School of Medicine, İstanbul, Turkey.
Bahçeşehir University · TREskişehir Osmangazi University · TRNear East University · CY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn recent years, an increasing number of studies have researched retinal nerve fiber layer (RNFL) changes in neurodegenerative disorders. In this study, our aim was to determine structural RNFL changes in patients with major depressive disorder.

methodsA total of 30 patients with major depressive disorder and 30 age- and sex-matched controls were recruited. Using optical coherence tomography (OCT), the peripapillary RNFL thickness in major depressive disorder patients and control subjects was measured and compared at each location.

resultsPatients with major depressive disorder did not show a statistically significant reduction in overall peripapillary RNFL thickness.

conclusionOur study showed that RNFL thickness is not reduced in major depressive disorder patients and that OCT is not a useful tool for diagnosing and monitoring the progression of major depressive disorder. This study suggests that the pathophysiology of unipolar depression is different than in neurodegenerative disorders, pervasive developmental disorders, schizophrenia, and bipolar disorder.

Indexed as

Depressionmagnocellular pathwayretina

Identifiers

PMID28566961
PMCPMC5439474
OpenAlexW2612110650

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.