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Record W2149626428 · doi:10.1177/0883073813488828

Subcutaneous Interferon Beta-1a in Pediatric Multiple Sclerosis

2013· article· en· W2149626428 on OpenAlexaff
Sílvia Tenembaum, Brenda Banwell, Daniela Pohl, Lauren Krupp, Alexey Boyко, Michael Meinel, Lorenz Lehr, Sanda Rocak, Elisabetta Verdun di Cantogno, Margaretha Stam Moraga, Angelo Ghezzi

Bibliographic record

VenueJournal of Child Neurology · 2013
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of OttawaHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMedicineTolerabilityMultiple sclerosisSubcutaneous injectionInterferon beta-1aInterferonInternal medicineAdverse effectMedical recordInterferon betaImmunology

Abstract

fetched live from OpenAlex

To expand current knowledge, we examined the safety and tolerability of subcutaneous interferon β-1a in patients with pediatric-onset multiple sclerosis. Records from 307 patients who had received at least 1 injection of subcutaneous interferon β-1a for demyelinating events when aged younger than 18 years were reviewed. Overall, 168 (54.7%) patients had at least 1 prespecified medical event related to or under close monitoring with subcutaneous interferon β-1a or specific to pediatric patients, 184 (59.9%) had nonserious medical events related to treatment or of unknown causality, and 12 (3.9%) had serious medical events irrespective of causality. The most common laboratory abnormalities were increased alanine (74/195; 37.9%) and aspartate aminotransferase levels (59/194; 30.4%). Annualized relapse rates were 1.79 before treatment and 0.47 during treatment. In conclusion, adult doses of subcutaneous interferon β-1a (44 and 22 μg, 3 times weekly) were well tolerated in pediatric patients and were associated with reduced relapse rates.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.000
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 head0.040
GPT teacher head0.267
Teacher spread0.227 · 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

Citations84
Published2013
Admission routes1
Has abstractyes

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