Advanced neonatal medicine in China: Is newborn ward capacity associated with inpatient antibiotic usage?
Bibliographic record
Abstract
Previous surveys of neonatal medicine in China have not collected comprehensive information on antibiotic use in newborns. The goal of the present study was to assess the trends in antibiotic use in inpatient newborns from advanced hospitals in mainland China and to evaluate the contributing factors. We extracted retrospective data on newborn clinical units from a database containing key clinical subspecialty area indicators from provincial or ministerial (Class A level III) hospitals over three consecutive years (2008-2010) and in 25 of 31 provincial districts of mainland China. Fifty-five newborn units were included in the study. The results showed that two thirds (65.7% ± 23.1%) of inpatient newborns were prescribed antibiotic products. Antibiotic use rates were significantly different by newborn ward bed capacity (p = 0.023; 60.6% for d capacity (ficant65.7% ± 23-100 beds group, and 77.1% for (ficant65.7% ± 23.1%) of inpatient newb significantly different by type of hospital, geographic area, admission to physician or nurse ratio, or physician or nurse academic degree. Factors contributing significantly to antibiotic use included ward bed capacity, physician to nurse ratio, average hospital stay, and pneumonia to preterm infant ratio. Our data suggested that the use of antibiotics among inpatient newborns in advanced hospitals in mainland China was prevalent and should be subject to rigorous monitoring, and highlighted the need to explore how newborn ward bed capacity potentially impacts antibiotic use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".