The Association of Adverse Pregnancy Outcomes With Overactive Bladder Anticholinergics
Bibliographic record
Abstract
IMPORTANCE: The pregnancy safety and teratogenicity of overactive bladder (OAB) anticholinergic medications in humans are unknown. OBJECTIVE: The aim of this study was to determine if the use of OAB anticholinergics during pregnancy was associated with adverse pregnancy outcomes or congenital malformation. STUDY DESIGN: Using routinely collected health care data from Ontario, Canada, we conducted a retrospective cohort study and identified women aged 18-45 years who gave birth between 2004 and 2022 and were eligible for provincial drug benefits. We used gestational age and birth dates to approximate conception dates. The primary exposure was filling a prescription for an OAB anticholinergic during pregnancy (compared with nonusers). The coprimary outcomes were pregnancy complication (which included preterm birth or low birth weight) and congenital malformation. Poisson regression models with generalized estimating equations and inverse probability of treatment weighting were used to estimate risk ratios (RRs). RESULTS: We identified 138,271 births, of which 479 (0.3%) had exposure to an OAB anticholinergic, for a median of 60 (interquartile range, 30-120) days. The most common OAB anticholinergic was oxybutynin (84%). In the weighted cohort, the risk of a pregnancy complication was significantly elevated (RR, 1.65; 95% confidence interval [CI], 1.40-1.95; P < 0.01; absolute risk difference + 9.9% [95% CI, +5.9, +13.9]), with a dose-response relationship close to statistical significance ( P = 0.07). The risk of congenital malformations with OAB anticholinergic use was not significant (RR, 1.24; 95% CI, 0.85-1.80; P = 0.26). CONCLUSIONS: Pregnant women who take OAB anticholinergic medications have a higher risk of pregnancy complications, but not congenital malformations, compared with non-OAB anticholinergic users. This information can be used when counseling women of child-bearing age about these medications.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".