LETTER TO THE EDITOR Overexposure to Antenatal Corticosteroids: A Global Concern To the Editor:
Bibliographic record
Abstract
Antenatal corticosteroid (ACS) therapy is widely used toenhance fetal lung maturation when preterm birth (< 34 weeks gestational age [GA]) is expected. ACS reduces morbidity and mortality of infants born within one week after ACS treatment.1 Predicting preterm birth is difficult and therefore many infants will be unnecessarily exposed. Data on the clinical prescription pattern of ACS are limited. However, 45 % of all fetuses exposed to ACS are born beyond one week following administration and at a GA of 34 weeks or more; thus unnecessarily are exposed to ACS.2,3 We calculated the number of infants exposed to ACS dur-ing a 10-year period by analyzing data from birth registers from Canada, the US, Europe, Australia, and New Zealand. Since the incidence of preterm birth varies amongst coun-tries, we calculated the lowest and highest rates of infants born before 34 weeks ’ GA. Of these infants, 70 % will have been exposed to ACS (justified exposure; JE).3 The number of infants that were exposed to ACS but were born beyond one week after ACS administration and after 34 weeks GA (unnecessary exposure; UE) were derived since the ratio between UE and JE is 45:55.2,3 There were 120 569 275 births during the study period.4 The incidence of live preterm births at less than 34 weeks’ GA in Canada was 1.8 % and in the US 3.6%.5,6 Based on these numbers on average 1 864 440 infants (range 1 242 960–2 485 919) received ACS unnecessarily (Table). Since ACS treatment is widely used in many other countries
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.015 | 0.018 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".