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Record W1992174536 · doi:10.1097/wno.0b013e31829c510e

Spectral-Domain Optical Coherence Tomography of Retinal Nerve Fiber Layer Thickness in NMO Patients

2013· article· en· W1992174536 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Neuro-Ophthalmology · 2013
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of CalgaryUniversity of British Columbia
Fundersnot available
KeywordsOptical coherence tomographyNerve fiber layerRetinalMaterials scienceNerve fibre layerLayer (electronics)OpticsOphthalmologyMedicinePhysicsComposite material

Abstract

fetched live from OpenAlex

BACKGROUND: Neuromyelitis optica (NMO) is a demyelinating syndrome of the central nervous system. NMO might be underdiagnosed at early stages when patients have not yet developed the full spectrum of disease. The aim of this study was to analyze the retinal nerve fiber layer (RNFL) with optical coherence tomography (OCT) and to compare RNFL measurements between NMO patients, patients with relapsing-remitting multiple sclerosis (RRMS), and healthy controls to determine whether differences in RNFL thickness could be an early diagnostic marker for NMO. METHODS: In a cross-sectional study, eyes of 25 NMO patients, 25 RRMS patients, and 50 healthy controls underwent RNFL measurements by OCT. Clinical parameters were collected by history and chart review. Pairwise Wilcoxon rank sum tests with Holm correction were used to compare means of RNFL thickness among 6 groups (NMO, RRMS, and healthy control) of patients [without or with 1 or more episode of optic neuritis (ON)]. The association between RNFL thickness and patient characteristics for NMO group was examined via linear mixed-effects models (adjusting for within-patient intereye correlations and history of ON, where appropriate). RESULTS: Based on the pairwise Wilcoxon rank sum tests with Holm correction, significant differences were found between NMO with 1 episode of ON and non-ON eyes (mean RNFL 63.7 vs 97.0 µm, P < 0.0001), multiple sclerosis (MS) non-ON eyes, and controls (RNFL 93.2 vs 98.4 µm, P = 0.03). No significant differences were found between NMO and MS with 1 attack of ON eyes (RNFL 63.7 vs 73.9 µm, P = 0.46), NMO non-ON eyes and healthy controls (RNFL 97.0 vs 98.4 µm, P = 0.56), and NMO non-ON and MS non-ON (RNFL 97.0 vs 93.2 µm, P = 0.56). For NMO group, RNFL thickness was associated with a history of ON (P < 0.001) but not with disability or disease duration when adjusting for the history of ON (P > 0.1). CONCLUSIONS: RNFL in NMO is not different enough to distinguish NMO ON from MS ON eyes, but the intereye difference in RFNL with a history of unilateral ON may be a better diagnostic marker for NMO.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.064
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.320
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it