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The reproductive effects of beta interferon therapy in pregnancy

2005· article· en· W2044566162 on OpenAlexaff
Radinka Boskovic, R. Wide, Jacob Wolpin, Daniel J. Bauer, Gideon Koren

Bibliographic record

VenueNeurology · 2005
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsUniversity of TorontoToronto Western Hospital
Fundersnot available
KeywordsPregnancyInterferon betaBETA (programming language)MedicineInterferon beta-1bObstetricsInterferonBiologyImmunologyComputer science

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine whether interferon therapy during human pregnancy increases reproductive risks in women. METHODS: This longitudinal, controlled cohort study consisted of three groups of women: an exposed group, a disease matched unexposed group, and a healthy comparative group. Subjects were selected from women contacting the Motherisk Program regarding maternal beta interferon exposure, mostly for multiple sclerosis during pregnancy, from 1997 to 2004. After delivery all of the women were re-contacted for a follow-up interview regarding maternal health, pregnancy outcome, and neonatal health. RESULTS: The study group (n = 16 women, 23 pregnancies) were exposed to interferon beta-1a (Avonex, Rebif) and interferon-1b (Betaseron). There was a decrease in mean birth weight in the exposed group (3,189 +/- 416 g) as compared to healthy controls (3,783 +/- 412 g, p = 0.002). Women exposed to beta interferon had a higher rate of miscarriages and stillbirths (39.1%) vs healthy controls (5%) (p = 0.03), even after correction for potential confounders. There were two major malformations (abnormality in the X chromosome, Down's syndrome) among exposed fetuses. CONCLUSIONS: Beta interferon therapy in the first trimester of pregnancy appears to be associated with an increased risk for fetal loss and low birth weight.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.790
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.033
GPT teacher head0.323
Teacher spread0.290 · 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

Citations153
Published2005
Admission routes1
Has abstractyes

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