Neonatal morbidity associated with late preterm and early term birth: the roles of gestational age and biological determinants of preterm birth
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to elucidate the role of gestational age in determining the risk of neonatal morbidity among infants born late preterm (34-36 weeks) and early term (37-38 weeks) compared with those born full term (39-41 weeks) by examining the contribution of gestational age within the context of biological determinants of preterm birth. METHODS: This was a retrospective cohort study. The sample included singleton live births with no major congenital anomalies, delivered at 34-41 weeks of gestation to London-Middlesex (Canada) mothers in 2002-11. Data from a city-wide perinatal database were linked with discharge abstract data. Multivariable models used modified Poisson regression to directly estimate adjusted relative risks (aRRs). The roles of gestational age and biological determinants of preterm birth were further examined using mediation and moderation analyses. RESULTS: Compared with infants born full term, infants born late preterm and early term were at increased risk for neonatal intensive care unit triage/admission [late preterm aRR=6.14, 95% confidence interval (CI) 5.63, 6.71; early term aRR=1.54, 95% CI 1.41, 1.68] and neonatal respiratory morbidity (late preterm aRR=6.16, 95% CI 5.39, 7.03; early term aRR=1.46, 95% CI 1.29, 1.65). The effect of gestational age was partially explained by biological determinants of preterm birth acting through gestational age. Moreover, placental ischaemia and other hypoxia exacerbated the effect of gestational age on poor outcomes. CONCLUSIONS: Poor outcomes among infants born late preterm and early term are not only due to physiological immaturity but also to biological determinants of preterm birth acting through and with gestational age to produce poor outcomes.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".