Maternal, fetal, and placental conditions associated with medically indicated late preterm and early term delivery: a retrospective study
Bibliographic record
Abstract
OBJECTIVE: Our objectives were: (1) to examine the association between maternal, fetal, and placental phenotypes of preterm delivery and medically indicated early delivery of singletons during the late preterm and early term periods; and (2) to identify the specific maternal, fetal, and placental conditions associated with these early deliveries. DESIGN: Retrospective study. SETTING: City of London and Middlesex County, Ontario, Canada. SAMPLE: Singleton live deliveries, at 34-41 weeks of gestation to women in London and Middlesex. METHODS: We obtained data from a city-wide perinatal database (2002-2011; n = 25 699). We used multinomial logistic regression for multivariable analyses. MAIN OUTCOME MEASURE: The outcome was the occurrence of medically indicated late preterm (34-36 weeks of gestation) and early term (37-38 weeks of gestation) delivery, versus delivery at full term (39-41 weeks of gestation). RESULTS: After controlling for confounding factors, all phenotypes were associated with increased odds of medically indicated late preterm and early term delivery. Within the maternal phenotype, chronic maternal medical conditions were associated with increased odds of medically indicated early term delivery (e.g. for gastrointestinal disease, adjusted odds ratio, aOR 1.72, 95% CI 1.47-2.00; for anaemia, aOR 1.40, 95% CI 1.20-1.63), but not late preterm delivery. CONCLUSIONS: The aetiology of medically indicated early delivery close to full term is heterogeneous. Patterns of associations suggest slightly different conditions underlying the late preterm and early term phenotypes, with chronic maternal medical conditions being associated with early term delivery but not with late preterm delivery. These results have implications for the prevention of early delivery as well as the identification of high-risk groups among those born early. TWEETABLE ABSTRACT: The aetiology of medically indicated late preterm and early term delivery is heterogeneous.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".