Early Antibiotic Use and Neonatal Outcomes Among Preterm Infants Without Infections
Bibliographic record
Abstract
OBJECTIVES: To determine whether use, duration, and types of early antibiotics were associated with neonatal outcomes and late antibiotic use in preterm infants without infection-related diseases. METHODS: This cohort study enrolled infants admitted to 25 tertiary NICUs in China within 24 hours of birth during 2015-2018. Death, discharge, or infection-related morbidities within 7 days of birth; major congenital anomalies; and error data on antibiotic use were excluded. The composite outcome was death or adverse morbidities. Late antibiotic use indicated antibiotics used after 7 days of age. Late antibiotic use rate was total antibiotic use days divided by the days of hospital stay after the first 7 days of life. RESULTS: Among 21 540 infants, 18 302 (85.0%) received early antibiotics. Early antibiotics was related to increased bronchopulmonary dysplasia (BPD) (adjusted odds ratio [aOR], 1.28; 95% confidence interval [CI], 1.05-1.56), late antibiotic use (aOR, 4.64; 95% CI, 4.19-5.14), and late antibiotic use rate (adjusted mean difference, 130 days/1000 patient-days; 95% CI, 112-147). Each additional day of early antibiotics was associated with increased BPD (aOR, 1.07; 95% CI, 1.04-1.10) and late antibiotic use (aOR, 1.41; 95% CI, 1.39-1.43). Broad-spectrum antibiotics showed larger effect size on neonatal outcomes than narrow-spectrum antibiotics. The correlation between early antibiotics and outcomes was significant among noncritical infants but disappeared for critical infants. CONCLUSIONS: Among infants without infection, early antibiotic use was associated with increased risk of BPD and late antibiotic use. Judicious early antibiotic use, especially avoiding prolonged duration and broad-spectrum antibiotics among noncritical infants, may improve neonatal outcomes and overall antibiotic use in NICUs.
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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 | 0.004 |
| 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 | 0.001 |
| 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".