Pregnant women with IBD are more likely to be adherent to biologic therapies than other medications
Bibliographic record
Abstract
BACKGROUND: There are differences in the efficacy and safety profiles of medications used to treat IBD that may impact a woman's perceived risk of medication exposure during pregnancy, potentially leading to medication non-adherence, poor disease-control and adverse pregnancy outcomes. AIM: To assess whether medication adherence patterns differ by drug class during pregnancy and influence birth outcomes for women with IBD. METHODS: Of 143 491 women, a validated case definition was used to identify 370 women with IBD in five administrative health databases in Alberta, Canada (2012-2015). Women who had ≥2 consecutive medications prescription for maintenance therapy for IBD in the year prior to pregnancy were included (n = 230). Prescription-based medication possession ratio ≥0.8 defined adherence. Chi-squared tests were used to compare adherence patterns by drug class and outcomes. RESULTS: Of the 159/230 women who were adherent during the year prior to pregnancy, 20 (12.6%; 95% CI: 8.2%, 18.8%) were not adherent and 21 (13.2%; 95% CI: 8.7%, 19.5%) discontinued their medications during pregnancy. Medication adherence during pregnancy differed significantly by drug class. A greater proportion of women on biologics (41.5%; 95% CI 32.9%, 50.7%) were adherent during pregnancy than women on thiopurines (22.9%; 95% CI 16.1%, 31.5%; P = 0.006); adherence was not significantly different for 5-aminosalicylates (35.6%; 95% CI 27.4%, 44.8%; P = 0.204). Women were more likely to be adherent to biologics (49.3%, 95% CI 37.3%, 61.3%) than thiopurines (20.9%; 95% CI 12.6%, 32.6%; P = 0.014) and 5-aminosalicylates (29.9%; 95% CI 19.9%, 42.1%; P = 0.030) in the first trimester. This was similar in the third trimester. In the second trimester, adherence pattern did not significantly differ by drug class (biologics vs thiopurines: P = 0.348; biologics vs 5-aminosalicylate: P = 0.999). Infants born to women with IBD (adherent: RR 1.58. 95% CI 1.02, 2.27; non-adherent: RR 1.32, 95% CI 0.97, 1.81) were more likely to be admitted into the neonatal intensive care unit than the general obstetric population, but this was not significantly different between women who were adherent or not adherent to their IBD medication (P = 0.711). CONCLUSION: Almost a quarter of women with IBD who were previously adherent to medical therapy were not adherent during pregnancy. Adherence pattern differed by drug class.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".