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Record W4414372077 · doi:10.1016/j.ebiom.2025.105905

Positive cerebrospinal fluid in the 2024 McDonald criteria for multiple sclerosis

2025· article· en· W4414372077 on OpenAlexaff
Florian Deisenhammer, Harald Hegen, Georgina Arrambide, Brenda Banwell, Tim Coetzee, Sharmilee Gnanapavan, Xavier Montalbán, Hayrettin Tumani, Maria Alice V. Willrich, Mark S. Freedman

Bibliographic record

VenueEBioMedicine · 2025
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersNational Institutes of HealthEuropean Committee for Treatment and Research in Multiple SclerosisNational Multiple Sclerosis SocietyU.S. Department of Health and Human Services
KeywordsMultiple sclerosisConcordanceCerebrospinal fluidKappaIntrathecalConfidence intervalDiseaseDiagnostic test

Abstract

fetched live from OpenAlex

The 2024 McDonald diagnostic criteria for Multiple Sclerosis (MS) introduce kappa free light chains (κ-FLC) detection in cerebrospinal fluid (CSF) which can be used interchangeably with oligoclonal IgG bands (OCB) to demonstrate intrathecal immunoglobulin synthesis. Diagnostic sensitivity and specificity of κ-FLC is equal to OCB on a 95% confidence level. In rare cases determination of both, κ-FLC and OCB should be considered as the concordance rate is around 90%. We recommend calculating the κ-FLC index with values of ≥6.1 performing best for diagnosing MS. Validated turbidimetric or nephelometric assays should be applied for which proficiency testing programs are available. There is some prognostic use of the κ-FLC index with higher values predicting higher disease activity. Neurofilament light (NfL) should not be used for diagnostic purposes although it might be useful for prognosis and disease monitoring. All recommendations apply to paediatric and adult relapsing as well as progressive onset 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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.078
GPT teacher head0.373
Teacher spread0.294 · 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

Citations26
Published2025
Admission routes1
Has abstractyes

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