Evidence map›Paper›PMID 40357265›Full record

ArticleMultiple sclerosis journal - experimental, translational and clinical

Test-retest reliability of Cirrus HD-optical coherence tomography retinal layer thickness measurements in people with multiple sclerosis.

Anna Bacchetti, Brenna McCormack, Ting-Yi Lin, Rozita Doosti, Gelareh Ahmadi, Omar Ezzedin, Nicole Pellegrini, Evan Johnson, Anna Kim, Gabriel Otero-Duran and 11 more

Abstract read
In one paragraph

Article in Multiple sclerosis journal - experimental, translational and clinical. 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

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.

  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

21 authors.

Anna BacchettiDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0009-0000-9434-8531
Brenna McCormackDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0009-0002-6678-7021
Ting-Yi LinDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0001-9605-8095
Rozita DoostiDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Gelareh AhmadiDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Omar EzzedinDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Nicole PellegriniDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Evan JohnsonDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Anna KimDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0009-0002-1188-5345
Gabriel Otero-DuranDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Devon J BonairDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Elle LawrenceDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Ernest LieversDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0009-0006-5274-277X
Simidele DavisDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Sooyeon ParkDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Madeline InserraDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Ananya GulatiDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
Kathryn C FitzgeraldDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0003-3137-0322
Elias S SotirchosDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0002-8812-1637
Peter A CalabresiDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0002-7776-6472
Shiv SaidhaDepartment of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0001-6387-0714

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Optical coherence tomography (OCT) allows evaluation of inter-eye differences (IEDs) in peri-papillary retinal nerve fiber layer (pRNFL) and macular ganglion cell-inner plexiform layer (GCIPL) thicknesses to identify unilateral optic nerve involvement (UONI), which is included in the 2024 revised McDonald diagnostic criteria for multiple sclerosis (MS). Objectives: To evaluate the test-retest reliability of pRNFL and GCIPL thicknesses/IEDs in people with MS, other neurological disorders, and healthy controls using Cirrus HD-OCT. Methods: 509 participants underwent Cirrus HD-OCT, acquiring two macular and optic disc scans per eye within each session. Scans meeting OSCAR-IB quality control criteria were included in final analyses (959 eyes), with no clinical/demographic exclusions (reflecting a real-world clinical setting). Reliability was assessed using coefficients of variation (COVs), intraclass correlation coefficients (ICCs), and Bland-Altman limits of agreement (LOA). IED consistency was evaluated using difference-in-differences (DiDs) of test-retest measurements. Results: GCIPL demonstrated superior reliability (ICC: 0.998, COV: 0.40%, LOA: -1.29 to 1.35 μm) to pRNFL (ICC: 0.989, COV: 1.18%, LOA: -3.59 to 3.70 μm) thickness. Inter-eye absolute DiDs [pRNFL: 2.00 μm (standard deviation (SD) 1.73); GCIPL: 0.64 μm (SD 0.67)] were lower than IED thresholds proposed for identifying UONI. Conclusions: The excellent reliability of GCIPL and pRNFL thicknesses/IEDs support OCT for identifying UONI to diagnose MS.

Indexed as

Diagnosisimagingmultiple sclerosisOCTreliabilitytest–retest

Identifiers

PMID40357265
PMCPMC12066860

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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.