Evidence map›Paper›PMID 39235398›Full record

ArticleTranslational vision science & technology2024

Assessing Visual Crowding in Participants With Preperimetric Glaucoma Using Eye Movement and Manual Response Paradigms.

Dilce Tanriverdi, Khaldoon O Al-Nosairy, Michael B Hoffmann, Frans W Cornelissen

Abstract read
In one paragraph

Article in Translational vision science & technology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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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

4 authors.

Dilce TanriverdiLaboratory for Experimental Ophthalmology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.
Khaldoon O Al-NosairySection for Clinical and Experimental Sensory Physiology, Ophthalmic Department, Otto-von-Guericke University, Magdeburg, Germany.
Michael B HoffmannSection for Clinical and Experimental Sensory Physiology, Ophthalmic Department, Otto-von-Guericke University, Magdeburg, Germany.
Frans W CornelissenLaboratory for Experimental Ophthalmology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: Crowding is the inability to distinguish objects in the periphery in the presence of clutter. Previous studies showed that crowding is elevated in patients with glaucoma. This could serve as an indicator of the functional visual performance of patients with glaucoma but at present appears too time-consuming and attentionally demanding. We examined visual crowding in individuals with preperimetric glaucoma to compare the potential effectiveness of eye movement-based and manual response paradigms. Methods: We assessed crowding magnitude in 10 participants with preperimetric glaucoma and 10 age-matched controls. Crowding magnitudes were assessed using four different paradigms: a conventional two-alternative forced choice (2AFC) manual, a 2AFC and a six-alternative forced choice (6AFC) eye movement, and a serial search paradigm. All paradigms measured crowding magnitude by comparing participants' orientation discrimination thresholds in isolated and flanked stimulus conditions. Moreover, assessment times and participant preferences were compared across paradigms. Results: Patients with preperimetric glaucoma exhibited elevated crowding, which was most evident in the manual-response paradigm. The serial search paradigm emerged as the fastest method for assessing thresholds, yet it could not effectively distinguish between glaucoma and control groups. The 6AFC paradigm proved challenging for both groups. Conclusions: We conclude that patients with preperimetric glaucoma demonstrate heightened binocular visual crowding. This is most effectively demonstrated via the 2AFC manual response paradigm. The additional attentional demand in eye movement paradigms rendered them less effective in the elderly population of the present study. Translational Relevance: Our findings underscore both the value and the complexity of efficiently evaluating crowding in elderly participants, including those with preperimetric glaucoma.

Indexed as

GlaucomaPattern Recognition, VisualVisual FieldsAgedEye MovementsFemaleHumansMaleManual CommunicationVisual Field Tests

Identifiers

PMID39235398
PMCPMC11379081

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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.