Association of external cephalic version before term with late preterm birth
Bibliographic record
Abstract
Abstract Introduction While evidence suggests that beginning an external cephalic version (ECV) before term (340/7 to 366/7 weeks) compared with after term may be associated with an increase in late preterm birth (340/7 to 366/7 weeks), it remains unknown what might account for this risk. The objective of the present study is to further investigate the association between ECV before term and late preterm birth. Material and methods Secondary analysis of data collected from the international, multicenter Early ECV trials. We evaluated the relation between ECV exposure and late preterm birth (340/7 to 366/7 weeks), as well as whether additional risk factors for preterm birth (such as maternal age, height, body mass index, parity, placental location, and perinatal mortality rate) moderated this relation. Generalized linear mixed methods were used to account for center effect and adjust for covariates. Result Among 1765 women with breech pregnancies and without a prior preterm birth, 749 (42.4%) received at least one ECV before term. Exposure to an ECV before term was not associated significantly independently with odds of preterm birth. However, placenta location moderated the association between early ECV exposure and late preterm birth. The odds of preterm birth in women who were exposed to an ECV before term and who also had an anterior placenta were doubled (OR 2.05; 95% CI 1.12–3.71; p = 0.02). Conclusion In a large cohort of women without known risks for preterm birth, those with an anterior placenta who undergo an ECV before term constitute a subgroup at particular risk for late 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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".