Abstract P170: Cardiovascular Health Scores, Adverse Pregnancy Outcomes, And Angiogenic Biomarkers Associated With Cognition8-10 Years After Pregnancy
Bibliographic record
Abstract
Introduction: Women with adverse pregnancy outcomes (APO, preeclampsia, preterm birth, small for gestational age neonates), especially those with placental maternal vascular malperfusion (MVM), are at increased cardiovascular and cognitive risk, perhaps due to poor cardiovascular health (CVH) and other vascular pathology. Hypothesis: Including history of APO and MVM in CVH scores identifies women with lower cognitive function and circulating angiogenic biomarker profiles indicating ongoing vascular pathophysiology. Methods: CVH was evaluated in 39 women 8-10 years after pregnancy (mean age 39.8 ±6 years, 36% Black) using standard metrics (smoking, BMI, blood pressure, total cholesterol, fasting glucose, and physical activity; higher score is healthier). APO history was abstracted from the medical record and added to CVH (no APO [n=14], APO-MVM [n=13], APO+MVM [n=13] to create a CVH-APO score. We evaluated cognitive function (memory, processing speed and executive function) as domain z scores using standard tests. Angiogenic biomarkers (VEGF-A, VEGF-C, VEGF-D, Tie-2, sFlt1, PlGF, and bFGF) were quantified using Angiogenesis Panel 1 (Meso Scale Diagnostics). Associations of CVH with cognition and biomarkers were evaluated using Pearson correlations. CVH groups (poor [CVH ≤7] vs. healthy [CVH >8) were compared with and without APO history using t-test. Results: Women with APO+MVM had lower CVH scores compared to those with no APO, adjusted for age and race (-1.5, p=0.03). Poor CVH was associated with slower processing speed (r=0.350, p=0.031) and reduced executive function (r=0.353, p=0.03) but not memory. When APO history was added to CVH, associations became stronger (r=0.402, p=0.012 for processing speed; 0.422, p=0.008 for executive function). Poorer CVH scores also correlated with higher VEGF A (-0.501 p=0.001), VEGF C (-0.653, p<0.001), PlGF (-0.326 p=0.045), and bFGF (-0.383, p=0.018). Using the combined CVH-APO score, women with poor CVH (n=18) compared to healthy CVH (n=20) had higher bFGF (18 vs 9.5 pg/mL p=0.013), VEGF-A (78 vs 44pg/mL p=0.002) and VEGF-C (1319 vs 828 p=0.023). Discussion: Poor CVH is associated with lower cognition and higher circulating angiogenic biomarker profiles in women, and APO history may further contribute to the cumulative vascular pathophysiological burden a decade after 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 | 0.000 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".