Biological determinants of spontaneous late preterm and early term birth: a retrospective cohort study
Bibliographic record
Abstract
OBJECTIVE: Our aim was to examine the association between biological determinants of preterm birth (infection and inflammation, placental ischaemia and other hypoxia, diabetes mellitus, other) and spontaneous late preterm (34-36 weeks) and early term (37-38 weeks) birth. DESIGN: Retrospective cohort study. SETTING: City of London and Middlesex County, Canada. SAMPLE: Singleton live births, delivered at 34-41 weeks to London-Middlesex mothers following spontaneous labour. METHODS: Data were obtained from a city-wide perinatal database on births between 2002 and 2011 (n = 17,678). Multivariable analyses used multinomial logistic regression. MAIN OUTCOME MEASURE: The outcome of interest was the occurrence of late preterm (34-36 weeks) and early term (37-38 weeks) birth, compared with full term birth (39-41 weeks). RESULTS: After controlling for covariates, there were associations between infection and inflammation and late preterm birth (aOR = 2.07, 95% CI 1.65, 2.60); between placental ischaemia and other hypoxia and late preterm (aOR = 2.21, 95% CI 1.88, 2.61) and early term (aOR = 1.25, 95% CI 1.13, 1.39) birth; between diabetes mellitus and late preterm (aOR = 3.89, 95% CI 2.90, 5.21) and early term (aOR = 2.66, 95% CI 2.19, 3.23) birth; and between other biological determinants (polyhydramnios, oligohydramnios) and late preterm (aOR = 2.81, 95% CI 1.70, 4.64) and early term (aOR = 1.89, 95% CI 1.32, 2.70) birth. CONCLUSIONS: Our findings show that delivery following spontaneous labour even close to full term may be a result of pathological processes. Because these biological determinants of preterm birth contribute to an adverse intrauterine environment, they have important implications for fetal and neonatal health.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".