Evidence-Based Neonatal Drug Therapy for Prevention of Bronchopulmonary Dysplasia in Very-Low-Birth-Weight Infants
Bibliographic record
Abstract
Corticosteroids, intramuscular vitamin A and caffeine reduce the risk of bronchopulmonary dysplasia (BPD) in very-low-birth-weight infants. We compared the size of the beneficial drug effects on BPD and evaluated long-term drug safety by estimating the number needed to treat (NNT) and the number needed to harm (NNH) for the outcome of cerebral palsy (CP). When given prophylactically during the first 4 days of life, corticosteroids increase the risk of CP (NNH 22; 95% CI: 12-133). When prescribed between days 7 and 14, corticosteroids reduce the 28-day mortality rate in addition to reducing BPD. Their effect on CP remains uncertain: the limited data available are consistent with a best-case scenario (NNT 15) and a worst-case scenario (NNH 14). Although repeated intramuscular injections of vitamin A during the 1st month of life reduce BPD (NNT 12; 95% CI: 6-94), estimates for CP range from an NNT of 11 to an NNH of 33. Early use of caffeine reduces both BPD and CP. The NNT for BPD is 10 (95% CI: 7-16), while the NNT for CP is 34 (95% CI: 20-132). We conclude that caffeine is the drug of choice for the prevention of BPD in very-low-birth-weight infants. Corticosteroids should be avoided during the first few days of life. However, when given during the 2nd week of life to infants at high risk of BPD corticosteroids may have important short- and long-term benefits. These should be urgently confirmed or refuted in well-designed controlled trials.
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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 | 0.007 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".