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Record W2899137047 · doi:10.1177/1756286418804760

Evaluation of pregnancy outcomes in patients with multiple sclerosis after fingolimod exposure

2018· article· en· W2899137047 on OpenAlexaff
Yvonne Geissbühler, Jere Vile, Gideon Koren, Morgane Guennec, Helmut Butzkueven, Hugh H. Tilson, Thomas M. MacDonald, Kerstin Hellwig

Bibliographic record

VenueTherapeutic Advances in Neurological Disorders · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSphingolipid Metabolism and Signaling
Canadian institutionsWestern University
FundersNovartis PharmaIC Design Education CenterBiogenIpsenNovartis
KeywordsFingolimodMedicineMultiple sclerosisPregnancyNatalizumabIntensive care medicineInternal medicineImmunology

Abstract

fetched live from OpenAlex

BACKGROUND AND METHODS: Limited data are available on the safety of fingolimod in pregnant women. We estimated the risk of adverse pregnancy outcomes in women with multiple sclerosis (MS) exposed to fingolimod either shortly before or during pregnancy in prospectively collected cases from clinical trials, observational studies, surveillance programs, and spontaneous reports. RESULTS: The prevalence of major malformations among live births does not appear to be significantly higher than those in the general population and the unexposed MS population. Similarly, the prevalence of cardiac malformations observed in this analysis was not significantly different from that of the general population. Proportions of miscarriage were in line with those of the general and unexposed MS population and no specific pattern of birth defects was identified. CONCLUSIONS: These data can help inform healthcare professionals and women with MS exposed to fingolimod during conception.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.068
Threshold uncertainty score0.415

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.019
GPT teacher head0.261
Teacher spread0.242 · 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

Citations38
Published2018
Admission routes1
Has abstractyes

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