Use of nonaspirin nonsteroidal anti-inflammatory drugs during pregnancy and the risk of spontaneous abortion
Bibliographic record
Abstract
BACKGROUND: The association between the use of nonaspirin nonsteroidal anti-inflammatory drugs (NSAIDs) during pregnancy and the risk of spontaneous abortion remains unclear because of inconsistent research results and the lack of evidence for an effect due to specific types or dosages of nonaspirin NSAIDs. We aimed to quantify the association between having a spontaneous abortion and types and dosages of nonaspirin NSAIDs in a cohort of pregnant women. METHODS: Using a nested case-control design, we obtained data from the Quebec Pregnancy Registry for 4705 women who had a spontaneous abortion. For each instance, we randomly selected 10 controls from the remaining women in the registry who were matched by index date (date of the spontaneous abortion) and gestational age. Use of nonaspirin NSAIDs (identified by filled prescriptions) and nonuse were compared. We also looked for associations between different types and dosages of nonaspirin NSAIDs and having a spontaneous abortion. Analyses of associations and adjustment for confounding were done using conditional logistic regression. RESULTS: We identified 4705 cases of spontaneous abortion (352 exposed [7.5%]); 47 050 controls (1213 exposed [2.6%]). Adjusting for potential confounders, the use of nonaspirin NSAIDs during pregnancy was significantly associated with the risk of spontaneous abortion (odds ratio [OR] 2.43, 95% confidence interval [CI] 2.12-2.79). Specifically, use of diclofenac (OR 3.09, 95% CI 1.96-4.87), naproxen (OR 2.64, 95% CI 2.13-3.28), celecoxib (OR 2.21, 95% CI 1.42-3.45), ibuprofen (OR 2.19, 95% CI 1.61-2.96) and rofecoxib (OR 1.83, 95% CI 1.24-2.70) alone, and combinations thereof (OR 2.64, 95% CI 1.59-4.39), were all associated with increased risk of spontaneous abortion. No dose-response effect was seen. INTERPRETATION: Gestational exposure to any type or dosage of nonaspirin NSAIDs may increase the risk of spontaneous abortion. These drugs should be used with caution during pregnancy.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".