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Record W2167992220 · doi:10.1517/14712598.2014.924496

Efficacy and safety of subcutaneous interferon-β-1a in patients with a first demyelinating event and early multiple sclerosis

2014· review· en· W2167992220 on OpenAlexaff
Mark S. Freedman

Bibliographic record

VenueExpert Opinion on Biological Therapy · 2014
Typereview
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsOttawa HospitalUniversity of Ottawa
FundersEMD SeronoTeva Pharmaceutical Industries
KeywordsMultiple sclerosisMedicineDemyelinating diseaseEvent (particle physics)ImmunologyInterferonPhysics

Abstract

fetched live from OpenAlex

INTRODUCTION: Multiple sclerosis (MS) is an inflammatory demyelinating disease of the CNS. Evidence suggests that MS should be treated as early as possible in order to maximize the benefit of treatment. AREAS COVERED: This review details current understanding about the treatment of relapsing-remitting MS (RRMS). The pharmacological and clinical data on the use of subcutaneous (s.c.) interferon β-1a (IFN-β-1a) as a therapeutic option for RRMS are covered, with a focus on the importance of treating patients with MS as early as possible in the course of the disease, in order to delay permanent axonal damage that is responsible for the signs and symptoms of disease progression. EXPERT OPINION: There is a wealth of data on the treatment of RRMS with s.c. IFN-β-1a indicating that patients treated during the early inflammatory stages of the disease have significantly improved short-term outcomes compared with patients who commence treatment late. It remains to be determined whether the short-term effects of early treatment will translate into long-lasting benefits, although it is hoped that ongoing research will help to answer this question.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
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 head0.147
GPT teacher head0.369
Teacher spread0.222 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations5
Published2014
Admission routes1
Has abstractyes

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