Associations Between Migraine and Adverse Pregnancy Outcomes: Systematic Review and Meta-analysis
Bibliographic record
Abstract
Importance Migraine is a highly prevalent disorder associated with cardiovascular diseases. Cardiovascular diseases are also associated with preeclampsia (PE). The adverse pregnancy outcomes PE, preterm birth (PTB), low birth weight (LBW), small for gestational age (SGA) and placental abruption share aspects in their pathophysiology, which are also found in patients with migraine, such as inflammatory stress and hypercoagulability. Objective To determine the association of adverse pregnancy outcomes including PE, PTB, LBW, SGA, and placental abruption with a history of migraine through a systematic review and meta-analysis. Evidence Acquisition MEDLINE (PubMed), the Cochrane Library, and EMBASE, were searched from inception to November 11, 2018. Cohort studies and case-control studies evaluating migraine history and pregnancy complications were eligible. Results Of 1388 screened references, 14 studies were included in the systematic review. There were higher risks of PE (odds ratio [OR], 2.07; 95% confidence interval [CI], 1.51–2.85; I 2 = 76%) and LBW (OR, 1.18; 95% CI, 1.03–1.34; I 2 = 9%) in women with migraine compared with women without migraine. We observed no significant association between history of migraine and PTB (OR, 1.23; 95% CI, 0.97–1.55; I 2 = 61%) or SGA (OR, 1.06; 95% CI, 0.98–1.15; I 2 = 0%). Conclusions A history of migraine is significantly associated with an increased risk of adverse pregnancy outcomes including PE and LBW. We hypothesize that shared pathophysiology due to underlying preclinical cardiovascular risk in women with migraine might play a role during pregnancy. Relevance Pregnant women with a history of migraine should be considered at higher risk of adverse pregnancy outcomes and should be informed, monitored, and treated preventively accordingly. Target Audience Obstetricians and gynecologists, family physicians. Learning Objectives After completing this activity, the learner should be better able to: Describe the association between migraine and placenta-induced pregnancy complications; Explain the possibility of the developing preeclampsia in women with a history of migraine; and Assess the risk of preterm birth or a neonate with low birth weight or small for gestational age in women with 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 | 0.009 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.030 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".