Markers of Vascular Dysfunction After Hypertensive Disorders of Pregnancy
Bibliographic record
Abstract
Women with prior hypertensive disorders of pregnancy (HDP) are at twice the risk of cardiovascular disease compared with women with prior normotensive pregnancy, possibly because of sustained vascular dysfunction after delivery. The aim of this systematic review and meta-analysis is to summarize evidence of vascular dysfunction at least 3 months after HDP. Articles in all languages were retrieved from principal databases. Studies included were observational, with HDP as the main exposure and measurements of vascular dysfunction via imaging modalities or serum biomarkers as the main outcome, assessed at least 3 months postpartum. We pooled results of modalities reported in >3 studies using a random effects model. Of 6109 potentially relevant studies, 72 were included that evaluated 10 imaging modalities and 11 serum biomarkers in 8702 women. There was evidence of vascular dysfunction in women post HDP compared with women with prior normal pregnancy when measured by carotid-femoral pulse wave velocity (0.64 m/s [0.17-1.11]), carotid intima-media thickness (0.025 mm [0.004-0.045]), and augmentation index (5.48% [1.58-9.37]), as well as mean levels of soluble fms-like tyrosine kinase (6.12 pg/mL [1.91-10.33]). Between-groups differences in measures of vascular dysfunction were more pronounced when assessments were performed in younger women (<40 years) or closer to the index pregnancy for almost all modalities. In conclusion, pooled data from studies evaluating vascular imaging suggest that some vascular dysfunction persists after HDP as compared with women with prior normal pregnancy.
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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".