Dihydroergotamine and triptan use to treat migraine during pregnancy and the risk of adverse pregnancy outcomes
Bibliographic record
Abstract
Migraine is prevalent during pregnancy. Antimigraine medications such as dihydroergotamine (DHE) and triptans have been associated with adverse pregnancy outcomes in individual studies but lack of consensus remains. We compared the risk of prematurity, low birth weight (LBW), major congenital malformations (MCM), and spontaneous abortions (SA) associated with gestational use of DHE or triptans. Three cohort and one nested-case-control analyses were conducted within the Quebec Pregnancy Cohort to assess the risk of prematurity, LBW, MCM, and SA. Exposure was defined dichotomously as use of DHE or triptan during pregnancy. Generalized estimation equations were built to quantify the associations, adjusting for potential confounders. 233,900 eligible pregnancies were included in the analyses on prematurity, LBW, and MCM; 29,104 cases of SA were identified. Seventy-eight subjects (0.03%) were exposed to DHE and 526 (0.22%) to triptans. Adjusting for potential confounders, DHE and triptans were associated with increased risks of prematurity, LBW, MCM, and SA but not all estimates were statistically significant. DHE was associated with the risk of prematurity (aRR: 4.12, 95% CI 1.21-13.99); triptans were associated with the risk of SA (aOR: 1.63, 95% CI 1.34-1.98). After considering maternal migraine, all antimigraine specific medications increased the risk of some adverse pregnancy outcomes, but estimates were unstable.
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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 | 0.003 |
| 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 | 0.000 |
| 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".