Evidence map›Paper›PMID 34003891›Full record

ArticleTranslational vision science & technology2021

A Wide-Field Optical Coherence Tomography Normative Database Considering the Fovea-Disc Relationship for Glaucoma Detection.

Hyungjun Kim, Jong Sub Lee, Hae Min Park, Hyunsoo Cho, Han Woong Lim, Mincheol Seong, Junhong Park, Won June Lee

Open access · goldAbstract read
In one paragraph

Article in Translational vision science & technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.1field-weighted citation impact, top 14% 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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Characterisation of the normal human ganglion cell-inner plexiform layer using widefield optical coherence tomography.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2024
    Article
  4. Review
  5. Prediction of visual field defects from macular optical coherence tomography in glaucoma using cluster analysis.Ophthalmic & physiological optics : the journal of the British College of Ophthalmic Opticians (Optometrists) · 2022
    Article
  6. Article
  7. Article
  8. 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 at 2 institutions in 1 country.

Hyungjun KimDepartment of Ophthalmology, Hanyang University College of Medicine, Seoul, Korea.
Jong Sub LeeDepartment of Ophthalmology, Hanyang University College of Medicine, Seoul, Korea.
Hae Min ParkDepartment of Ophthalmology, Hanyang University College of Medicine, Seoul, Korea.
Hyunsoo ChoDepartment of Ophthalmology, Hanyang University College of Medicine, Seoul, Korea.
Han Woong LimDepartment of Ophthalmology, Hanyang University College of Medicine, Seoul, Korea.
Mincheol SeongDepartment of Ophthalmology, Hanyang University College of Medicine, Seoul, Korea.
Junhong ParkDepartment of Mechanical Engineering, Hanyang University, Seoul, Korea.
Won June LeeDepartment of Ophthalmology, Hanyang University College of Medicine, Seoul, Korea.
Hanyang University · KRHanyang University Seoul Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: One purpose of this study was to collect wide-field swept-source optical coherence tomography (SS-OCT) data from healthy eyes and build a wide-filed normative database. Another purpose was to compare the glaucoma diagnostic ability of new parameters based on this normative database to the parameters that are currently in use, such as the peripapillary retinal nerve fiber layer (RNFL), macular ganglion cell-inner plexiform layer, and ganglion cell complex (GCC) thickness. Methods: This study had 220 healthy eyes and 292 eyes with early-stage glaucoma (EG) and moderate-stage glaucoma (MG) enrolled. Using the wide-field SS-OCT images (12 × 9 mm) of healthy eyes, a wide-field normative database was constructed by transforming and combining the individual images into a uniform template using the fovea and optic disc centers as fixed landmarks. Adjustment for the disc size was conducted. With this normative database, new parameters based on the ratio of the fovea-disc distance (FDD) consisting of the fovea-disc relationship were evaluated. The glaucoma diagnostic ability was assessed based on the area under the receiver operating characteristic curve (AUC). Results: Among the new peripapillary parameters, the RNFL of the circumference of the circle with diameter 0.8 FDD showed the highest AUC value for EG and MG, but the value was not significantly superior to that of the initial RNFL (AUC = 0.940 vs. 0.937, P = 0.631). Among the macular parameters, the GCC of the area of the circle of 1.5 FDD showed the highest AUC value for EG and MG, and the value was significantly superior to that of initial GCC (AUC = 0.929 vs. 0.919, P = 0.033). However, there was no significant difference between the initial and adjusted GCC thickness in patients included in the EG or MG groups separately. Conclusions: A wide-field normative database was built to consider the relationship between the fovea and the optic disc. Considering this aspect, we found that the GCC analysis using a broader area presented a significantly greater glaucoma diagnostic performance for EG and MG in the macula than the initial parameter for the GCC. Translational Relevance: Based on this wide-field normative database, the clinical use of a wide-field deviation map may help diagnose the patients with EG and MG in the future.

Indexed as

GlaucomaTomography, Optical CoherenceCross-Sectional StudiesHumansNerve FibersRetinal Ganglion Cells

Identifiers

PMID34003891
PMCPMC7873501
OpenAlexW3126184874

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.