Global antibiotic dosing strategies in hospitalised children: Characterising variation and implications for harmonisation of international guidelines
Bibliographic record
Abstract
BACKGROUND: Paediatric global antibiotic guidelines are inconsistent, most likely due to the limited pharmacokinetic and efficacy data in this population. We investigated factors underlying variation in antibiotic dosing using data from five global point prevalence surveys. METHODS & FINDINGS: Data from 3,367 doses of the 16 most frequent intravenous antibiotics administered to children 1 month-12 years across 23 countries were analysed. For each antibiotic, we identified standard doses given as either weight-based doses (in mg/kg/day) or fixed daily doses (in mg/day), and investigated the pattern of dosing using each strategy. Factors underlying observed variation in weight-based doses were investigated using linear mixed effects models. Weight-based dosing (in mg/kg/day) clustered around a small number of peaks, and all antibiotics had 1-3 standard weight-based doses used in 5%-48% of doses. Dosing strategy was more often weight-based than fixed daily dosing for all antibiotics apart from teicoplanin, which had approximately equal proportions of dosing attributable to each strategy. No strong consistent patterns emerged to explain the historical variation in actual weight-based doses used apart from higher dosing seen in central nervous system infections, and lower in skin and soft tissue infections compared to lower respiratory tract infections. Higher dosing was noted in the Americas compared to the European region. CONCLUSIONS: Antibiotic dosing in children clusters around a small number of doses, although variation remains. There is a clear opportunity for the clinical, scientific and public health communities to consolidate behind a consistent set of global antibiotic dosing guidelines to harmonise current practice and prioritise future research.
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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 | 0.067 | 0.178 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| 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".