The rise in singleton preterm births in the USA: the impact of labour induction
Bibliographic record
Abstract
OBJECTIVE: To assess the extent to which increased rates of labour induction and caesarean section have contributed to the recent rise in preterm birth. DESIGN: National birth cohort study. SETTING: USA. POPULATION AND SAMPLE: Singleton live births, with primary analysis based on non-Hispanic white women. METHODS: Ecological study based on the 50 states and the District of Columbia during two time periods 10 years apart: 1992-94 and 2002-04. MAIN OUTCOME MEASURE: Preterm birth (live birth <37 completed weeks of gestation), based on an algorithm combining menstrual and clinical estimates of gestational age. RESULTS: The state-level ecological analysis among non-Hispanic white women showed that the change in preterm birth rate from 1992-94 to 2002-04 was significantly associated with the change in rate of labour induction (r = 0.50, 95% CI 0.26-0.68), but not with the change in rate of caesarean delivery (r = -0.06, 95% CI -0.33 to 0.22). Weaker but otherwise similar associations with labour induction were observed in Hispanic women and in non-Hispanic black women. CONCLUSIONS: Increasing use of labour induction is probably an important cause of the observed increased rate in preterm birth.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".