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Record W4409785659 · doi:10.1016/j.msard.2025.106459

Results from a multiple sclerosis relapse clinic

2025· article· en· W4409785659 on OpenAlexfundno aff
Mullan Gerry, Rachael Kee, Fiona Kennedy, Stella Hughes, Gavin McDonnell

Bibliographic record

VenueMultiple Sclerosis and Related Disorders · 2025
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersQueen's UniversityQueen's University Belfast
KeywordsMultiple sclerosisMedicinePsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: A multiple sclerosis (MS) relapse clinic can lead to early diagnosis and management of MS relapses, yet published outcomes from MS relapse clinics are scarce. METHODS: We analysed the Belfast Health and Social Care Trust (BHSCT) relapse clinic over a 12 month period. RESULTS: Only 16 % of attendees were diagnosed with a relapse, defined as new neurological symptoms with radiological evidence of new disease activity. Pseudorelapse was a more common cause of presentation (19 %) than relapse. Corticosteroid therapy was administered in 3 % of all attendances. CONCLUSIONS: This low figure highlights the importance of clinical evaluation of new symptoms, justifies caution in corticosteroid prescribing and may reflect the impact of highly-effective therapies. We encourage other groups to publish their relapse clinic findings to best characterise the frequency of relapses and the utility of such services using real world data.

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)0.007
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.047
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0130.002

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 head0.055
GPT teacher head0.290
Teacher spread0.235 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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