General obstetrics: Pregnancy‐induced hypertension is associated with lower infant mortality in preterm singletons
Bibliographic record
Abstract
OBJECTIVE: To assess the association between pregnancy-induced hypertension (PIH) and infant mortality. DESIGN: Retrospective cohort study. SETTING: Birth and infant death registration dataset of the USA. POPULATION: A total of 17,432,987 eligible, liveborn singleton births in 1995-2000. METHODS: Multivariate logistic regression was applied to evaluate the association between PIH and infant mortality, with adjustment of potential confounders. MAIN OUTCOME MEASURES: Infant death (0-364 days) and its three components: early neonatal death (0-6 days), late neonatal death (7-27 days), and postneonatal death (28-364 days). RESULTS: There was a significant reduction in infant mortality associated with PIH in early preterm infants (OR = 0.59, 95% CI: 0.56-0.63) and in late preterm infants (OR = 0.80, 95% CI: 0.73-0.87), but a significant increase in term infants (OR = 1.08, 95% CI: 1.02-1.14). Both in early preterm and late preterm births, early neonatal mortality (OR = 0.38, 95% CI: 0.34-0.42; OR = 0.68, 95% CI: 0.61-0.77) and late neonatal mortality (OR = 0.59, 95% CI: 0.50-0.70; OR = 0.76, 95% CI: 0.61-0.96) were decreased in infants born to mothers with PIH compared with those born to mothers with normal blood pressure. The PIH-associated reduction in neonatal mortality among preterm singletons was stronger in small-for-gestational-age infants than in normal growth infants and stronger in infants born to nulliparous women than in those born to multiparous women. CONCLUSIONS: PIH is associated with lower risk of infant death in preterm births but higher risk in term births.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".