Fetal and neonatal outcomes after term and preterm delivery following betamethasone administration in twin pregnancies
Bibliographic record
Abstract
OBJECTIVE: To investigate effects of betamethasone on fetal growth and neonatal outcomes in twins. METHODS: A retrospective cohort study was conducted of twins delivered at one center in Berlin, Germany, between 1993 and 2011. The betamethasone group included twin pregnancies with preterm labor, cervical shortening, preterm premature rupture of membranes, or vaginal bleeding, and exposure to betamethasone between 23(+5) and 33(+6) weeks. The control group included twin pregnancies with no betamethasone exposure matched for length at delivery. Fetal growth and neonatal anthropometric data were analyzed by twin-pair structure, dose, and gestational age (linear mixed model). RESULTS: Overall, 1922 live-born twin pairs (653 betamethasone group, 1269 controls) were included. Compared with controls, late-preterm twins exposed to betamethasone were lighter (mean difference -126g), had a smaller head circumference (-0.4cm), and a shorter body length (-0.8cm) after adjustment for confounders (P<0.05). Female neonates from mixed or same-sex twin pairs had a lower birth weight than controls (betamethasone ≤16mg: -114g; betamethasone 24mg: -124g; betamethasone >24mg: -187g), with no detectable improvement in neonatal morbidity (hyperbilirubinemia, respiratory distress, asphyxia) or mortality. CONCLUSION: Betamethasone reduced birth weight, head circumference, and length of female preterm neonates in twin pairs in a dose-dependent manner. The neonatal mortality and morbidity were not improved by betamethasone.
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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 | 0.005 |
| 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 | 0.000 | 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".