Evidence map›Paper›PMID 37037307›Full record

ArticleOphthalmology. Glaucoma

Intraocular Pressure and Rates of Macular Thinning in Glaucoma.

Abia Ahmed, Alessandro A Jammal, Tais Estrela, Samuel I Berchuck, Felipe A Medeiros

Open access · greenAbstract read
In one paragraph

Article in Ophthalmology. Glaucoma. 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
0.8field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

5 authors at 2 institutions in 1 country.

Abia AhmedVision, Imaging, and Performance Laboratory, Duke Eye Center and Department of Ophthalmology, Duke University, Durham, North Carolina; Department of Biology, University of North Carolina, Chapel Hill, North Carolina.
Alessandro A JammalVision, Imaging, and Performance Laboratory, Duke Eye Center and Department of Ophthalmology, Duke University, Durham, North Carolina.
Tais EstrelaVision, Imaging, and Performance Laboratory, Duke Eye Center and Department of Ophthalmology, Duke University, Durham, North Carolina.
Samuel I BerchuckVision, Imaging, and Performance Laboratory, Duke Eye Center and Department of Ophthalmology, Duke University, Durham, North Carolina; Department of Statistical Science and Forge, Duke University, Durham, North Carolina.
Felipe A MedeirosVision, Imaging, and Performance Laboratory, Duke Eye Center and Department of Ophthalmology, Duke University, Durham, North Carolina; Department of Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina. Electronic address: felipe.medeiros@duke.edu.
Duke University · USUniversity of North Carolina at Chapel Hill · US

Funding

The BCI (Brain Computer Interface) Glaucoma Study: Objective Home-Based Detection of Progressive Visual Function Loss in GlaucomaR01EY029885 · NEI · UNIVERSITY OF MIAMI SCHOOL OF MEDICINE · PI ASRANI, SANJAY, MEDEIROS, FELIPE · 2019 to 2022
$2.2M
Objective Quantification of Neural Damage for Screening, Diagnosis and Monitoring of Glaucoma with Fundus PhotographsR21EY031898 · NEI · DUKE UNIVERSITY · PI MEDEIROS, FELIPE · 2020 to 2021
$437k
NEI NIH HHS R01 EY029885NEI NIH HHS R21 EY031898
6 · The paper itself

Abstract

purposeTo evaluate the effect of intraocular pressure (IOP) on the rates of macular thickness (ganglion cell layer [GCL] and ganglion cell-inner plexiform layer [GCIPL]) change over time measured by spectral-domain (SD) OCT.

designRetrospective cohort study.

participantsOverall, 451 eyes of 256 patients with primary open-angle glaucoma.

methodsData were extracted from the Duke Ophthalmic Registry, a database of electronic medical records of patients observed under routine clinical care at the Duke Eye Center, and satellite clinics. All records from patients with a minimum of 6 months of follow-up and at least 2 good-quality Spectralis SD-OCT macula scans were included. Linear mixed models were used to investigate the relationship between average IOP during follow-up and rates of GCL and GCIPL thickness change over time.

main outcome measuresThe effect of IOP on the rates of GCL and GCIPL thickness loss measured by SD-OCT.

resultsEyes had a mean follow-up of 1.8 ± 1.3 years, ranging from 0.5 to 10.2 years. The average rate of change for GCL thickness was -0.220 μm/year (95% confidence interval [CI], -0.268 to -0.172 μm/year) and for GCIPL thickness was -0.231 μm/year (95% CI, -0.302 to -0.160 μm/year). Each 1-mmHg higher mean IOP during follow-up was associated with an additional loss of -0.021 μm/year of GCL thickness (P = 0.001) and -0.032 μm/year of GCIPL thickness (P = 0.001) after adjusting for potentially confounding factors, such as baseline age, disease severity, sex, race, central corneal thickness, and follow-up time.

conclusionsHigher IOP was significantly associated with faster rates of GCL and GCIPL loss over time measured by SD-OCT, even during relatively short follow-up times. These findings support the use of SD-OCT GCL and GCIPL thickness measurements as structural biomarkers for the evaluation of the efficacy of IOP-lowering therapies in slowing down the progression of glaucoma. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

GlaucomaGlaucoma, Open-AngleDisease ProgressionHumansIntraocular PressureNerve FibersRetinal Ganglion CellsRetrospective StudiesTomography, Optical CoherenceVisual FieldsGanglion cell complexGanglion cell layerGlaucomaIntraocular pressure

Identifiers

PMID37037307
PMCPMC10523920
OpenAlexW4362720952

What OpenQuestion holds

Textmetadata
LicenceTDM
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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.