Evidence map›Paper›PMID 39056571›Full record

ArticleOphthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists)2024

Exploring the relationship between 24-2 visual field and widefield optical coherence tomography data across healthy, glaucoma suspect and glaucoma eyes.

Janelle Tong, Jack Phu, David Alonso-Caneiro, Jason Kugelman, Sieu Khuu, Ashish Agar, Minas Coroneo, Michael Kalloniatis

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. Article
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

8 authors.

Janelle TongCentre for Eye Health, University of New South Wales, Sydney, New South Wales, Australia.ORCID 0000-0002-4268-5138
Jack PhuCentre for Eye Health, University of New South Wales, Sydney, New South Wales, Australia.ORCID 0000-0002-9933-6780
David Alonso-CaneiroSchool of Science, Technology and Engineering, University of Sunshine Coast, Sunshine Coast, Queensland, Australia.
Jason KugelmanContact Lens and Visual Optics Laboratory, Centre for Vision and Eye Research, School of Optometry and Vision Science, Queensland University of Technology, Kelvin Grove, Queensland, Australia.
Sieu KhuuSchool of Optometry and Vision Science, University of New South Wales, Sydney, New South Wales, Australia.
Ashish AgarDepartment of Ophthalmology, University of New South Wales at Prince of Wales Hospital, Sydney, New South Wales, Australia.
Minas CoroneoDepartment of Ophthalmology, University of New South Wales at Prince of Wales Hospital, Sydney, New South Wales, Australia.
Michael KalloniatisSchool of Optometry and Vision Science, University of New South Wales, Sydney, New South Wales, Australia.ORCID 0000-0002-5264-4639

Funding

National Health and Medical Research Council 1186915
6 · The paper itself

Abstract

purposeTo utilise ganglion cell-inner plexiform layer (GCIPL) measurements acquired using widefield optical coherence tomography (OCT) scans spanning 55° × 45° to explore the link between co-localised structural parameters and clinical visual field (VF) data.

methodsWidefield OCT scans acquired from 311 healthy, 268 glaucoma suspect and 269 glaucoma eyes were segmented to generate GCIPL thickness measurements. Estimated ganglion cell (GC) counts, calculated from GCIPL measurements, were plotted against 24-2 SITA Faster visual field (VF) thresholds, and regression models were computed with data categorised by diagnosis and VF status. Classification of locations as VF defective or non-defective using GCIPL parameters computed across eccentricity- and hemifield-dependent clusters was assessed by analysing areas under receiver operating characteristic curves (AUROCCs). Sensitivities and specificities were calculated per diagnostic category.

resultsSegmented linear regression models between GC counts and VF thresholds demonstrated higher variability in VF defective locations relative to non-defective locations (mean absolute error 6.10-9.93 dB and 1.43-1.91 dB, respectively). AUROCCs from cluster-wide GCIPL parameters were similar across methods centrally (p = 0.06-0.84) but significantly greater peripherally, especially when considering classification of more central locations (p < 0.0001). Across diagnoses, cluster-wide GCIPL parameters demonstrated variable sensitivities and specificities (0.36-0.93 and 0.65-0.98, respectively), with the highest specificities observed across healthy eyes (0.73-0.98).

conclusionsQuantitative prediction of VF thresholds from widefield OCT is affected by high variability at VF defective locations. Prediction of VF status based on cluster-wide GCIPL parameters from widefield OCT could become useful to aid clinical decision-making in appropriately targeting VF assessments.

Indexed as

GlaucomaIntraocular PressureNerve FibersRetinal Ganglion CellsROC CurveTomography, Optical CoherenceVisual FieldsVisual Field TestsAdultAgedFemaleHumansMaleMiddle AgedOcular HypertensionOptic Diskglaucomaoptical coherence tomographyvisual fields

Identifiers

PMID39056571
PMCPMC12891256

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Registered trials

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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.