Thiopurine exposure during pregnancy is not associated with anemia in infants born to mothers with IBD
Bibliographic record
Abstract
Abstract Background Thiopurines are commonly used to treat inflammatory bowel disease (IBD). Thiopurines are considered safe throughout pregnancy. However, a published study suggested the risk of neonatal anemia was increased if exposed to thiopurines in-utero. This prospective cohort study aimed to determine if there is an increased risk of cytopenia among infants born to pregnant people with IBD, exposed or un-exposed to thiopurines, compared to infants born to those without IBD. Methods Pregnant IBD patients, with and without thiopurine exposure, and one cohort of control individuals were recruited over a 5-year period. Consenting individuals completed a questionnaire and infants had a complete blood cell count at the newborn heel prick. Anemia was defined as hemoglobin (Hb) <140g/L. Descriptive statistics were used to characterize the study population. Fisher exact tests were used to examine differences in outcomes between groups, a p value of <0.05 was deemed significant. Results Three cohorts were recruited: 19 IBD patients on thiopurines, 50 IBD patients not on thiopurines and 37 controls (total 106). Neonatal median Hb was not different with 177g/L (IQR 38g/L) for the IBD thiopurine group, 180.5g/L (IQR 40g/L) for the IBD non-thiopurine group, and 181g/L (IQR 37g/L) for the controls. Nineteen infants (18%) were cytopenic with 12 (11%) anemic, 6 (5.6%) thrombocytopenic and 1 (0.94%) lymphopenic. Thiopurine exposure was only in one, mildly anemic, infant. Conclusion These findings further support physicians and IBD patients contemplating pregnancy that current guidelines recommending thiopurine adherence do not lead to increased perinatal risk of anemia or cytopenia.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".