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Record W2920748704 · doi:10.1002/pds.4735

Use and safety of disease‐modifying therapy in pregnant women with multiple sclerosis

2019· article· en· W2920748704 on OpenAlexfundno aff
Sarah Macdonald, Thomas F. McElrath, Sonia Hernández–Dı́az

Bibliographic record

VenuePharmacoepidemiology and Drug Safety · 2019
Typearticle
Languageen
FieldMedicine
TopicMultiple Sclerosis Research Studies
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentCanadian Institutes of Health ResearchPfizer
KeywordsMedicineGlatiramer acetatePregnancyPreeclampsiaObstetricsMultiple sclerosisAbortionPharmacoepidemiologyNatalizumabMedical prescription

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study is to describe dispensing patterns and comparative safety of disease-modifying therapies (DMTs) during pregnancy in women with multiple sclerosis (MS). METHODS: We identified pregnancies from the Truven Health Marketscan® Commercial Claims and Encounters Database (2011-2015) and ascertained MS before delivery from inpatient and outpatient claims. We computed the proportion of women with DMT dispensing claims around pregnancy and estimated risk ratios of spontaneous abortion, infections, cesarean section, preterm delivery, poor fetal growth, preeclampsia, and major structural malformations by DMT exposure. RESULTS: Of 984 058 pregnancies, 1649 were to women with MS. Thirty-five percent of women with MS filled a prescription for a DMT in the 90 days before pregnancy. DMT use declined during pregnancy but increased again after delivery. Glatiramer acetate and interferon beta were most commonly dispensed. Pregnancies with and without early DMT exposure had similar risks of outcomes to one another and to pregnancies in women without MS. Small numbers did not allow evaluation of specific DMTs. CONCLUSIONS: Approximately one third of commercially insured women with MS in the United States uses DMTs before conception. Neither MS itself nor early pregnancy use of DMTs overall seems to be associated with a substantial risk of adverse pregnancy outcomes.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.097
GPT teacher head0.340
Teacher spread0.243 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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