Abstract P319: Do Pregnancy Complications Elevate Cardiovascular Risk After Pregnancy? An Examination of Cardiometabolic Biomarker and Risk Factor Trajectories Up to the First Nine Months Postpartum in Low Income Women
Bibliographic record
Abstract
Introduction: Preeclampsia, having a small for gestational age (SGA) baby or preterm delivery are associated with later maternal cardiovascular disease (CVD) risk. Therefore, we sought to examine whether peripartum CVD biomarker and risk factor trajectories differed among women with and without CVD-related pregnancy complications. Methods: In the Maternal Adiposity Metabolism and Stress (MAMAS) Study, we studied n=110 overweight and obese women in the MAMAS study of 8-week mindful eating and stress reduction intervention, we used mixed linear regression analysis to compare trajectories of CVD risk factors at three periods: 1) intrapartum at 12-20 weeks gestation, 2) 3 months postpartum, and 3) 9 months postpartum. CVD biomarkers/ risk factors studied included serum glucose, insulin, HOMA-IR, leptin, ghrelin, lipids, ALT, IL-6, IL-10, tumor necrosis factor, and blood pressure (BP). Covariates for multivariable adjustment included age, maternal smoking, prepregnancy BMI, BP, age*time and prepregnancy BMI*time. Results: Women had mean age =28 y (SD 6), mean prior pregnancies=0.8 (SD 1.0), 13% were White, 36% African American and 32% Latina; n=22 women had one or more CVD-related pregnancy complications. Peripartum glucose and systolic BP trajectories were statistically greater in complicated versus normal pregnancies (p values=0.008 and 0.01 respectively) ( Figure ). Trajectories for lipids, insulin, HOMA-IR, adipokines, ALT, IL-6 and diastolic BP were elevated in complicated versus normal pregnancies, but did not reach statistical significance. Conclusions: Glucose and systolic BP rise were significantly higher from early pregnancy to 9 months postpartum among low income women with complicated vs. uncomplicated pregnancies. Cardiometabolic risk factor modification among women with CVD-related pregnancy complications in the peripartum period may be warranted.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".