The association between threatened preterm labour and perinatal outcomes at term: a population‐based cohort study
Bibliographic record
Abstract
OBJECTIVE: To estimate the association between threatened preterm labour (TPTL) and perinatal outcomes of infants born at term. DESIGN: A population-based cohort study of perinatal outcomes following TPTL <37 weeks of gestation with delivery at term. SETTING: Nova Scotia, Canada. POPULATION: All non-anomalous, singleton pregnancies ≥37 weeks of gestation without antepartum haemorrhage from 1988 to 2019. METHODS: Using data from the Nova Scotia Atlee Perinatal Database, TPTL was defined as pregnancies with a hospital admission between 20 and 37 weeks of gestation, with a diagnosis code denoting TPTL with administration of antenatal corticosteroids, or with administration of any tocolysis. Poisson regression models were used to estimate the risk ratios (RR) with 95% CI of maternal and perinatal outcomes in women who had an episode of TPTL relative to those who did not. MAIN OUTCOME MEASURES: Birthweight for gestational age below the tenth centile and a composite of perinatal mortality or severe perinatal morbidity. RESULTS: Of 256 599 term deliveries meeting the inclusion criteria, 2278 (0.9%) involved TPTL. The risks of the primary outcomes were higher among those with TPTL relative to those without: birthweight for gestational age below the tenth centile (RR 1.24, 95% CI 1.11-1.39) and the composite of perinatal mortality/severe perinatal morbidity (RR 1.33, 95% CI 1.15-1.54). CONCLUSIONS: Although the prevalence of TPTL in term deliveries is low, affected pregnancies are at increased risk for adverse perinatal outcomes. Increased fetal surveillance should be considered in the management of pregnancies affected by TPTL.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".