Anti-TNFα Therapies Are Safe During Pregnancy in Women with Inflammatory Bowel Disease
Bibliographic record
Abstract
BACKGROUND: The use of TNFα antagonists is well described for inflammatory bowel disease (IBD), but their safety profile during pregnancy is yet to be fully elucidated. A systematic review and meta-analysis were performed to identify studies that explored the safety of anti-TNFα therapy during pregnancy in patients with IBD. METHODS: A systematic literature search was conducted to identify studies that investigated the pregnancy outcomes among women with IBD on anti-TNFα therapy. The primary outcome was the overall rate of unfavourable pregnancy-related outcomes among women with IBD on anti-TNFα therapy. Secondary outcomes included rates of abortions (spontaneous or elective), preterm delivery, low birth weight, and congenital malformations. Odds ratios (OR) with 95% confidence interval (CI) are reported. Eligible studies used an observational or interventional design, enrolled subjects with IBD on anti-TNFα therapy for at least 1 trimester and compared outcomes with appropriately matched controls. RESULTS: Overall, 5 studies with a total of 1216 participants were eligible for inclusion in the meta-analysis. There was no significant difference in the rates of total unfavourable pregnancy outcomes between pregnant women with IBD who were on anti-TNFα therapy and controls not on anti-TNFα therapy (OR, 1.00 [95% CI, 0.72-1.41]). Similarly, there were no statistically significant differences in the rates of abortion (OR, 1.53 [95% CI, 0.97-2.41]), preterm birth (OR, 1.00 [95% CI, 0.62-1.62]), low birth weight (OR, 1.05 [95% CI, 0.62-1.78]), or congenital malformation (OR, 1.10 [95% CI, 0.58-2.09]). CONCLUSIONS: The use of anti-TNFα therapy does not seem to increase the risk of unfavorable pregnancy outcomes among women with IBD, although the optimal timing of therapy through pregnancy and the postpartum period was not assessed in this analysis. These data can help counsel patients around family planning and perinatal management.
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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 | 0.012 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.010 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".