Vasculopathic and thrombophilic risk factors for spontaneous preterm birth
Bibliographic record
Abstract
BACKGROUND: Mothers who give birth to preterm infants are at increased risk of mortality from coronary heart disease and stroke, but the biological pathways underlying these associations have not been explored. METHODS: We carried out a case-control study nested in a large (n = 5337) prospective, multicentre cohort. All cohort women had an interview, examination and venipuncture at 24-26 weeks. Frozen plasma samples in spontaneous preterm births (n = 207) and 444 term controls were analysed for plasma homocysteine, folate, cholesterol (total, low-density lipoprotein and high-density lipoprotein) and thrombin-antithrombin (TAT) complexes. DNA was extracted and analysed for seven gene polymorphisms involved in thrombophilia or folate or homocysteine metabolism. Fresh placentas were fixed, stained and blindly assessed for histologic evidence of infarction and decidual vasculopathy. RESULTS: High (above the median) plasma homocysteine and HDL cholesterol were significantly and independently associated with the risk of spontaneous preterm birth [adjusted odds ratios (OR)s = 1.9 (95% 1.1-3.3) and 0.5 (0.3-0.9), respectively]. A higher proportion of women with high homocysteine concentrations had decidual vasculopathy [(13.0 vs 6.8%; OR = 1.9 (1.1-3.5)], although the positive association between decidual vasculopathy and preterm birth did not achieve statistical significance [OR = 1.5 (0.9-2.7)]. No significant associations were observed with the DNA polymorphisms or with plasma TAT or folate levels. CONCLUSIONS: Similar vasculopathic risk factors may underlie preterm birth and adult coronary heart disease and stroke.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.002 | 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".