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Revised Diagnostic Criteria for Neuromyelitis Optica Spectrum Disorders (S63.001)

2014· article· en· W1703601342 on OpenAlexaff
Dean M. Wingerchuk, Brenda Banwell, Jeffrey L. Bennett, Philippe Cabre, William M. Carroll, Tanuja Chitnis, de Sèze, Kazuo Fujihara, Benjamin Greenberg, Anu Jacob, Sven Jarius, Marco Aurélio Lana–Peixoto, Michael Levy, Jack H. Simon, Sílvia Tenembaum, Anthony Traboulsee, Patrick Waters, Kay E. Wellik, Brian G. Weinshenker

Bibliographic record

VenueNeurology · 2014
Typearticle
Languageen
FieldMedicine
TopicPeripheral Neuropathies and Disorders
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNeuromyelitis opticaSpectrum disorderMedicineBroad spectrumPsychoanalysisPsychologyPsychiatryMultiple sclerosisChemistry

Abstract

fetched live from OpenAlex

Objective: To revise diagnostic criteria for neuromyelitis optica (NMO) and NMO spectrum disorders. Background: NMO is an inflammatory demyelinating CNS syndrome distinct from multiple sclerosis (MS) and associated with serum aquaporin-4 antibodies (AQP4-IgG). Current diagnostic criteria were developed in 2006 and require both optic nerve and spinal cord involvement. However, clinical and neuroimaging evidence, especially from AQP4-IgG seropositive patients, has revealed a wider disease spectrum. The International Panel for NMO Diagnosis (IPND) was convened to develop revised, evidence-based consensus diagnostic criteria. Design/Methods: The INPD met on 7 occasions between October, 2011 and November, 2013. Nineteen panel members participated in 6 working groups (clinical presentation, serology, neuroimaging, pediatrics, systemic autoimmunity, and opticospinal MS), each of which were charged with addressing focused questions to contribute to the revised diagnostic criteria. Each working group conducted systematic literature reviews related to their specific charges and summarized the results. Electronic surveys were then used to develop new criteria, which were iteratively refined through electronic scoring and face-to-face meetings. Results: The new diagnostic nomenclature defines the unified term “NMO spectrum disorders” (NMOSD), which is stratified by serological testing results (NMOSD with or without AQP4-IgG). Core characteristics of NMOSD with AQP4 antibodies include clinical syndromes and/or MRI findings related to optic nerve, spinal cord, brain stem, diencephalic, or cerebral presentations. The presence of enriched core characteristics, plus additional supportive criteria, are required for diagnosis of NMOSD without AQP4-IgG. The IPND also achieved consensus on pediatric NMOSD diagnosis, AQP4-IgG testing, monophasic NMOSD and opticospinal MS. Conclusions: The IPND achieved consensus on revised diagnostic criteria for adult and pediatric NMOSD, with or without AQP4-IgG, for clinical and research purposes and to distinguish NMOSD from competing diagnoses. These criteria require prospective validation. The proposed nomenclature allow for future revisions to account for new clinical, neuroimaging, laboratory, and antibody associations. Study Supported by: Guthy-Jackson Charitable Foundation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.014
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0050.002
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0140.009

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 head0.011
GPT teacher head0.262
Teacher spread0.251 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations21
Published2014
Admission routes1
Has abstractyes

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