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Record W2140155096 · doi:10.1212/wnl.0000000000001257

Relationships between quantitative spinal cord MRI and retinal layers in multiple sclerosis

2015· article· en· W2140155096 on OpenAlexaff
Jiwon Oh, Elias S. Sotirchos, Shiv Saidha, Anna Whetstone, Min Chen, Scott D. Newsome, Laura J. Balcer, Elliot M. Frohman, Jerry L. Prince, Marie Diener‐West, Daniel S. Reich, Peter A. Calabresi

Bibliographic record

VenueNeurology · 2015
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Neurological Disorders and StrokeU.S. Public Health ServiceNational Institutes of Health
KeywordsFractional anisotropyExpanded Disability Status ScaleOptic neuritisMedicineMultiple sclerosisRetinalAtrophyNerve fiber layerMagnetic resonance imagingDiffusion MRIOphthalmologyNuclear medicineInternal medicineRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To assess relationships between spinal cord MRI (SC-MRI) and retinal measures, and to evaluate whether these measures independently relate to clinical disability in multiple sclerosis (MS). METHODS: One hundred two patients with MS and 11 healthy controls underwent 3-tesla brain and cervical SC-MRI, which included standard T1- and T2-based sequences and diffusion-tensor and magnetization-transfer imaging, and optical coherence tomography with automated segmentation. Clinical assessments included visual acuity (VA), Expanded Disability Status Scale, MS functional composite, vibration sensation threshold, and hip-flexion strength. Regions of interest circumscribing SC cross-sections at C3-4 were used to obtain cross-sectional area (CSA), fractional anisotropy (FA), perpendicular diffusivity (λ⊥), and magnetization transfer ratio. Multivariable regression assessed group differences and SC, retinal, and clinical relationships. RESULTS: In MS, there were correlations between SC-CSA, SC-FA, SC-λ⊥, and peripapillary retinal nerve fiber layer (pRNFL) (p = 0.01, p = 0.002, p = 0.001, respectively) after adjusting for age, sex, prior optic neuritis, and brain atrophy. In multivariable clinical models, when SC-CSA, pRNFL, and brain atrophy were included simultaneously, SC-CSA and pRNFL retained independent relationships with low-contrast VA (p = 0.04, p = 0.002, respectively), high-contrast VA (p = 0.06, p = 0.008), and vibration sensation threshold (p = 0.01, p = 0.05). SC-CSA alone retained independent relationships with Expanded Disability Status Scale (p = 0.001), hip-flexion strength (p = 0.001), and MS functional composite (p = 0.004). CONCLUSIONS: In this cross-sectional study of patients with MS, correlations exist between SC-MRI and retinal layers, and both exhibit independent relationships with clinical dysfunction. These findings suggest that the SC and optic nerve reflect ongoing global pathologic processes that supplement measures of whole-brain atrophy, highlighting the importance of combining measures from unique compartments to facilitate a thorough examination of regional and global disease processes that contribute to clinical disability in MS.

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.

How this classification was reachedexpand

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.494

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.364
GPT teacher head0.385
Teacher spread0.021 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations61
Published2015
Admission routes1
Has abstractyes

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