Review article: a decision‐making algorithm for the management of pregnancy in the inflammatory bowel disease patient
Bibliographic record
Abstract
BACKGROUND: Inflammatory bowel disease affects patients who are in their reproductive years. There are many questions regarding the management of IBD patients who are considering or who are already pregnant. These include the effect of the disease and the medications on fertility and on the pregnancy outcome. AIM: To create an evidence-based decision-making algorithm to help guide physicians through the management of pregnancy in the IBD patient. METHODS: A literature review using phrases that include: 'inflammatory bowel disease', 'Crohn's disease', 'ulcerative colitis', 'pregnancy', 'fertility', 'breast feeding', 'delivery', 'surgery', 'immunomodulators', 'azathioprine', 'mercaptopurine', 'biologics', 'infliximab', 'adalimumab', 'certolizumab'. CONCLUSIONS: The four decision-making nodes in the algorithm for the management of pregnancy in the IBD patient, and the key points for each one are as follows: (i) preconception counselling - pregnancy outcome is better if patients remain in remission during pregnancy, (ii) contemplating pregnancy or is already pregnant - drugs used to treat IBD appear to be safe during pregnancy, with the exception of methotrexate and thalidomide, (iii) delivery and (iv) breast feeding - drugs used to treat IBD appear to be safe during lactation, except for ciclosporin. Another key point is that biological agents may be continued up to 30 weeks gestation. The management of pregnancy in the IBD patient should be multi-disciplinary involving the patient and her partner, the family physician, the gastroenterologist and the obstetrician.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".