Pre-pregnancy migraine diagnosis, medication use, and spontaneous abortion: a prospective cohort study
Bibliographic record
Abstract
BACKGROUND: Migraine is common among females of reproductive age (estimated prevalence:17-24%) and may be associated with reproductive health through underlying central nervous system excitability, autoimmune conditions, and autonomic dysfunction. We evaluated the extent to which pre-pregnancy migraine diagnosis and medication use are associated with risk of spontaneous abortion (SAB). METHODS: We analyzed data from a preconception study of pregnancy planners (2013-2021). Eligible participants self-identified as female, were aged 21-45 years, resided in the USA or Canada, and conceived during follow-up (n = 7890). Participants completed baseline and bimonthly follow-up questionnaires for up to 12 months or until a reported pregnancy, whichever occurred first. Pregnant participants then completed questionnaires during early (~ 8-9 weeks) and late (~ 32 weeks) gestation. We defined migraineurs as participants who reported a migraine diagnosis or use of a medication to treat migraine. Preconception questionnaires elicited migraine medication use during the past 4 weeks, and SAB on follow-up and pregnancy questionnaires. We used Cox regression models with gestational weeks as the time scale to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) for associations among preconception migraine, migraine medication use, and SAB, controlling for potential demographic, medical, and lifestyle confounders. RESULTS: Nineteen percent of study pregnancies ended in SAB. History of migraine before conception was not appreciably associated with SAB risk (HR = 1.03, 95% CI: 0.91-1.06). Use of any migraine medication was associated with a modest increase in SAB risk overall (HR = 1.14, 95% CI: 0.96-1.36). We observed the greatest increase in risk among those taking migraine medications daily (HR = 1.38, 95% CI: 0.81-2.35) and those taking prescription migraine prophylaxis (HR = 1.43, 95% CI: 0.72-2.84) or combination analgesic and caffeine medications (HR = 1.42, 95% CI: 0.99-2.04). CONCLUSIONS: Migraine medication use patterns suggesting greater underlying migraine severity were associated with increased risk of SAB. This research adds to the limited information available on the reproductive effects of migraine.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".