Maternal chronic conditions and risk of reproductive and perinatal outcomes
Bibliographic record
Abstract
Individuals with chronic medical conditions are at an increased risk for adverse reproductive and perinatal outcomes. However, there is limited condition-specific information on the reproductive and perinatal implications of chronic conditions and their associated treatments. In this dissertation, we focus on thyroid disorders and migraines, two relatively common chronic conditions among females of reproductive age, and three distinct reproductive outcomes, spanning from preconception to delivery. In study one, we analyzed the association between thyroid disorders and fecundability, the per-cycle probability of conception among non-contracepting couples, using data from Pregnancy Study Online (PRESTO), a preconception cohort study of pregnancy planners in the United States and Canada. We did not find an association between a diagnosis of hypothyroid, hyperthyroid, thyroid autoimmunity, or thyroid nodules/thyroid cancer and fecundability. We also found no association between thyroid medication use or non-use among individuals with a thyroid disorder and fecundability. In the second study, we focused on migraines and spontaneous abortion (SAB), which is pregnancy loss before twenty weeks gestation, also using PRESTO data. We found that a history of migraines is not independently associated with SAB risk in females, but that routine use of medication for migraines during the preconception period may be associated with an increased risk of SAB. In the third study, we focused on the association between migraines and hypertensive disorders of pregnancy (HDOP), which include gestational hypertension and preeclampsia. We used data from the Clinical Practice Research Datalink Gold, a longitudinal database of de-identified patient records from hundreds of primary care practices in the United Kingdom. We found that while migraines overall are associated with a small increase in risk of HDOP, this increase is most substantial among those with pre-pregnancy migraines that persist in the first trimester of pregnancy. Overall, we observed that while a history of diagnosed thyroid disorder or migraines ascertained via self-report during the preconception period may not be associated with the reproductive and perinatal outcomes we studied, certain subgroups of individuals with migraines may be at increased risk of SAB or HDOP. Migraine severity and persistence in the first trimester are likely important factors in determining the magnitude of this increased risk. Nuanced research into chronic conditions with a disproportionate disease burden among females of reproductive age will guide and improve reproductive health care for individuals with chronic conditions. This dissertation aims to address these gaps in the literature by exploring the relationship between two chronic conditions and three reproductive and perinatal outcomes: thyroid disorders and fecundability, migraines and spontaneous abortion, and migraines and hypertensive disorders of 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 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".