Variations in antenatal corticosteroid therapy: a persistent problem despite 30 years of evidence
Bibliographic record
Abstract
OBJECTIVE: To document current use of antenatal corticosteroid therapy in a large cohort of Canadian preterm infants admitted to neonatal intensive care units, and to assess the impact of variations in use on neonatal outcomes. METHODS: The study subjects included 11,440 infants less than 38 weeks' gestation who were admitted to 17 Canadian Neonatal Network intensive care units from January 1996 to October 1997. Data analyses were conducted separately for infants less than 24 weeks' gestation, 24-34 weeks' gestation, and over 34 weeks' gestation. Logistic regression analysis was used to model the examined relationships, controlling for patient characteristics. RESULTS: The incidence of antenatal corticosteroid treatment was 42% for infants less than 24 weeks' gestation, 59% for infants 24-34 weeks' gestation, and 10% for infants over 34 weeks' gestation. Antenatal corticosteroid treatment was associated with reduced risk for neonatal mortality and respiratory distress syndrome, but not for infants over 34 weeks' gestation. Significant institutional variations in antenatal corticosteroid use were present among both inborn and outborn infants. Increased antenatal corticosteroid treatment for infants 24-34 weeks' gestation can potentially reduce the number of neonatal deaths by 41 cases (10%) and respiratory distress syndrome by 90 cases (3%) among participating hospitals. CONCLUSION: Wide institutional differences persist in the incidence of antenatal corticosteroid treatment for women expected to give birth preterm. Increased use of antenatal corticosteroids for preterm deliveries can reduce neonatal mortality in Canada by up to 10%.
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".