Abstract 08: Preterm Delivery and Maternal Cardiovascular Risk Factor Trajectories across the Life Course
Bibliographic record
Abstract
Introduction: Preterm delivery (<37 weeks) predicts 2 to 3-fold greater risk of cardiovascular disease in mothers. Development of subclinical cardiovascular risk in these women prior to and following pregnancy is not well understood. Hypothesis: Women who deliver preterm have an adverse cardiovascular health profile even prior to pregnancy. Methods: Linked data from the population-based, longitudinal HUNT study (1984-2008) and the Medical Birth Registry of Norway (1967-2012) yielded clinical measurements and pregnancy outcomes for 23,179 parous women. Women had up to 3 measurements of body mass index, waist circumference, blood pressure, non-fasting lipids and glucose, and high-sensitivity C-reactive protein (hs-CRP) during a follow-up period between 20 years before first birth to 41 years after first birth. We used mixed effects linear spline models, adjusting for age, pre-pregnancy smoking, education, and time since last meal, to compare risk factor trajectories for women with preterm versus term/postterm first births. Results: Women with a preterm first birth (n=1,402, 6%) had significantly higher triglyceride (Figure 1 A) and glucose levels prior to pregnancy. They also experienced steeper increases in systolic and diastolic blood pressure, non-HDL cholesterol, triglycerides, and hs-CRP from first birth to age 50 compared to women who delivered at term/post-term (Figure 1 A,B). Measures of adiposity were similar throughout the life course. Conclusions: These results are consistent with the hypothesis that preterm birth is an early marker of cardiometabolic impairment. A history of preterm birth may predict high cardiovascular risk well before the development of traditional risk factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".