A national, multicentre, web-based point prevalence survey of antimicrobial use and quality indices among hospitalised paediatric patients across South Africa
Bibliographic record
Abstract
OBJECTIVES: Data on antimicrobial consumption among the paediatric population in public hospitals in South Africa are limited. This needs to be addressed to improve future antimicrobial use and reduce antimicrobial resistance rates. This study aimed to quantify antimicrobial usage and to identify and classify which antimicrobials are used in the paediatric population in public sector hospitals in South Africa according to the World Health Organization (WHO) AWaRe list of antimicrobials. METHODS: A point prevalence survey was conducted among 18 public sector hospitals from nine provinces using a newly developed web-based application. Data were analysed according to the WHO AWaRe list to guide future quality improvement programmes. RESULTS: A total of 1261 paediatric patient files were reviewed, with 49.7% (627/1261) receiving at least one antimicrobial and with 1013 antimicrobial prescriptions overall. The top five antimicrobials included ampicillin (16.4%), gentamicin (10.0%), amoxicillin/enzyme inhibitor (9.6%), ceftriaxone (7.4%) and amikacin (6.3%). Antimicrobials from the 'Access' classification were the most used (55.9%), with only 3.1% being from the 'Reserve' classification. The most common infectious conditions for which an antimicrobial was prescribed were pneumonia (14.6%; 148/1013) and clinical sepsis (11.0%; 111/1013). Parenteral administration (75.6%; 766/1013) and prolonged surgical prophylaxis (66.7%; 10/15) were common concerns. Only 28.0% (284/1013) of prescribed antimicrobials had cultures requested; of which only 38.7% (110/284) of culture results were available in the files. CONCLUSION: Overall, antimicrobial prescribing is common among paediatric patients in South Africa. Interventions should be targeted at improving antimicrobial prescribing, including surgical prophylaxis, and encouraging greater use of oral antibiotics.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".