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Record W2999926506 · doi:10.1159/000502886

Update on the Management of Inflammatory Bowel Disease during Pregnancy and Breastfeeding

2020· review· en· W2999926506 on OpenAlexaff
Sophie Restellini, Luc Biedermann, Petr Hrúz, Christian Mottet, Annick Moens, Marc Ferrante, Alain Schoepfer

Bibliographic record

VenueDigestion · 2020
Typereview
Languageen
FieldMedicine
TopicPregnancy and Medication Impact
Canadian institutionsMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsBreastfeedingMedicinePregnancyInflammatory bowel diseaseDiseaseHealth careFamily medicineIntensive care medicineHealth professionalsPostpartum periodObstetricsPediatricsInternal medicine

Abstract

fetched live from OpenAlex

Inflammatory bowel disease (IBD) affects patients during their peak reproductive years. This raises important questions, in both patients and healthcare providers, regarding conception, pregnancy, and breastfeeding. Lack of information and insufficient communication among healthcare providers can leave patients with limited information and even contradictory advice. Given the fact that pregnant and/or breastfeeding IBD patients are excluded from clinical studies the evidence on many questions related to pregnancy and postpartum period is limited. However, there exists increasing data from case series and cohort studies that allows to provide clinical guidance. The overarching concept is that optimizing the mother's health is critical for optimizing the health of the unborn child and benefit of continuing medical therapy in IBD during pregnancy outweighs possible risks in most instances. This paper provides an up-to-date systematic review of the literature on IBD in pregnancy and proposes guidance to questions frequently encountered by healthcare professionals.

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)0.002
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.027
GPT teacher head0.298
Teacher spread0.271 · 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 designNot applicable
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

Citations38
Published2020
Admission routes1
Has abstractyes

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