Global Consensus Statement on the Management of Pregnancy in Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND & AIMS: Pregnancy can be a complex and risk-filled event for women with inflammatory bowel disease (IBD). High-quality studies in this population are lacking, with limited data on medications approved to treat IBD during pregnancy. For patients, limited knowledge surrounding pregnancy impacts pregnancy rates, medication adherence, and outcomes. Limited provider knowledge leads to highly varied practices in care affected by local dogma, available resources, individual interpretation of the literature, and fear of harming the fetus. The variations in guidelines by different societies and countries reflect this and lead to confusion for physicians and patients alike. The Global Consensus Consortium is a group of 39 IBD and content experts and 7 patient advocates from 6 continents who convened to review and assess current data and come to an agreement on best practices based on these data. METHODS: The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) process was used when sufficient published data were available and the RAND (Research and Development) process in those instances where expert opinion was needed to guide consistent practice. Recommendations were informed by the guiding principle that maternal health best supports infant health. RESULTS: The topics were divided into ten categories with 34 GRADE recommendations and 35 consensus statements. CONCLUSIONS: Overall, the goal of the group was to provide data-driven and practical guidance to improve the care of women with IBD around the globe based on the best available research.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".