Evidence map›Paper›PMID 39136958›Full record

ArticleTranslational vision science & technology2024

Impact of Demographics on Regional Visual Field Loss and Deterioration in Glaucoma.

Yueyin Pang, Melody Tang, Min Shi, Yu Tian, Yan Luo, Tobias Elze, Louis R Pasquale, Nazlee Zebardast, Michael V Boland, David S Friedman and 3 more

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

13 authors.

Yueyin PangHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Melody TangHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Min ShiHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Yu TianHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Yan LuoHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Tobias ElzeHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Louis R PasqualeEye and Vision Research Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Nazlee ZebardastMassachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Michael V BolandMassachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
David S FriedmanMassachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Lucy Q ShenMassachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Anagha LokhandeHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.
Mengyu WangHarvard Ophthalmology AI Lab, Schepens Eye Research Institute of Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA.

Funding

VISION RESEARCHP30EY003790 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI Patricia Ann D'Amore · 1985 to 2026
$25.5M
Personalizing Glaucoma Diagnosis by Disease Specific Patterns and Individual Eye AnatomyR01EY030575 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI ELZE, TOBIAS · 2019 to 2023
$2.4M
Personalizing Circumpapillary Retinal Nerve Fiber Layer Thickness Norms for GlaucomaR21EY035298 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI WANG, MENGYU · 2023 to 2023
$557k
NEI NIH HHS P30 EY003790NEI NIH HHS R01 EY030575NEI NIH HHS R21 EY035298
6 · The paper itself

Abstract

Purpose: To elucidate the impact of demographics, including gender, race, ethnicity, and preferred language, on regional visual field (VF) loss and progression in glaucoma. Methods: Multivariable linear mixed regressions were performed to determine the impact of race, ethnicity, and preferred language on regional VF loss with adjustment for age and gender. Regional VF loss was defined by pointwise total deviation values and VF loss patterns quantified by an unsupervised machine learning method termed archetypal analysis. All cross-sectional and longitudinal analyses were performed both without and with adjustment for VF mean deviation, which represented overall VF loss severity. P values were corrected for multiple comparisons. Results: All results mentioned had corrected P values less than 0.05. Asian and Black patients showed worse pointwise VF loss than White patients with superior hemifield more affected. Patients with a preferred language other than English demonstrated worse pointwise VF loss than patients with English as their preferred language. Longitudinal analyses revealed Black patients showed worse VF loss/year compared to White patients. Patients with a preferred language other than English demonstrated worse VF loss/year compared to patients preferring English. Conclusions: Blacks and non-English speakers have more severe VF loss, with superior hemifield being more affected and faster VF worsening. Translational Relevance: This study furthered our understanding of racial, ethnic, and socioeconomic disparities in glaucoma outcomes. Understanding the VF loss burden in different racial, ethnic, and socioeconomic groups may guide more effective glaucoma screening and community outreach efforts. This research could help reduce vision loss and improve quality of life in disproportionately affected populations by guiding public health efforts to promote glaucoma awareness and access to care.

Indexed as

GlaucomaVision DisordersVisual FieldsAgedCross-Sectional StudiesDisease ProgressionFemaleHumansLanguageMaleMiddle AgedVisual Field Tests

Identifiers

PMID39136958
PMCPMC11323995

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.