The Pregravid Vascular Risk Factor Profile of Low-Risk Women Who Develop Pregnancy Outcomes That Predict Future Cardiovascular Disease
Bibliographic record
Abstract
Background: Women with a history of certain adverse outcomes in pregnancy (preterm birth, delivery of a small-for-gestational age [SGA] infant, preeclampsia, and gestational diabetes mellitus [GDM]) have an elevated lifetime prevalence of metabolic syndrome (MetS) and cardiovascular disease, compared with their peers. However, it is not known if MetS precedes the index pregnancy in young, nulliparous women who experience these antepartum outcomes. Thus, we sought to evaluate the relationship between pregravid cardiovascular risk factor profile and these pregnancy outcomes in low-risk women. Methods: In this prospective preconception cohort study, 1183 newly married women underwent systematic assessment of cardiovascular risk factors (anthropometry, blood pressure, lipids, glucose) at median 24.7 weeks before pregnancy, whereupon they were followed for the outcomes of preterm birth, SGA delivery, preeclampsia, and GDM. Results: Women who had pregravid MetS (harmonized definition) ( n = 49) were more likely to have a Caesarean delivery than their peers (61.4% vs. 38.6%, p = 0.003). However, they did not have a higher incidence of preterm delivery, SGA, preeclampsia, or GDM. Similarly, women who had at least one of these adverse pregnancy outcomes ( n = 141) did not have a higher prevalence of MetS or any of its component disorders before pregnancy. Indeed, before pregnancy, there were no significant differences between these women and their peers in waist circumference, body mass index, blood pressure, fasting glucose, triglycerides, low-density-lipoprotein, or high-density-lipoprotein cholesterol. Conclusions: The adverse cardiovascular risk factor profile that is seen in women with a history of preterm birth, SGA, preeclampsia, or GDM does not necessarily manifest before their pregnancy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".