Population-based study on antenatal corticosteroid treatment in preterm small for gestational age and non-small for gestational age twin infants
Bibliographic record
Abstract
Objectives: To assess the associations between antenatal corticosteroid use (ACU), mortality and severe morbidities in preterm, twin neonates and compare these between small for gestational age (SGA) and non-SGA twins.Materials and methods: Population-based study using data collected by the Israel National Very Low Birth Weight infant database from 1995 to 2012, comprising twin infants of 24–31 weeks' gestation, without major malformations. Univariate and multivariable logistic regression analyses were performed.Results: Among the 6195 study twin infants, 784 were SGA. Among SGA neonates, ACU were associated with decreased mortality (23.9% vs. 39.2%, p < 0.0001) and composite adverse outcome including mortality or severe neonatal morbidity (43.8% vs. 56.8%, p = 0.0015), similar to the effect in non-SGA neonates (mortality 13.0% vs. 24.5%, p < 0.0001; composite outcome 34.2% vs. 44.8%, p < 0.0001). In the multivariable logistic regression analyses, ACU were associated with an almost 50% reduced mortality risk among SGA twin neonates (OR = 0.52, 95% CI 0.31–0.88) similar to the effect in non-SGA twin neonates (OR = 0.56, 95% CI 0.45–0.70), Pinteraction = 0.69. Composite adverse outcome risk was also reduced in SGA (OR = 0.78, 95% CI 0.50–1.23) and non-SGA groups (OR = 0.78, 95% CI 0.65–0.95), Pinteraction = 0.95.Conclusions: ACU should be considered in all mothers with twin gestation, at risk for preterm delivery at 24–31 weeks, in order to improve perinatal outcome.
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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) | 0.001 | 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) | 0.001 | 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".