Establishing Benchmarks for Antimicrobial Use in Canadian Children’s Hospitals
Bibliographic record
Abstract
BACKGROUND: Point prevalence surveys (PPS) are potentially useful to measure antimicrobial use across institutions. The objectives of the study were to describe and compare antimicrobial use between pediatric hospitals in Canada. METHODS: Fifteen pediatric hospitals all with pediatric infectious diseases service participated in 2 single-day PPS in 2018/19. Children <18 years of age who were inpatients were included. Age, service, clinical diagnosis as well as name, route, and start date for each antimicrobial was collected. Antibiotics were grouped according to the World Health Organization AWaRe classification. RESULTS: There were 3924 inpatient patients-days representing 2729 children and 1195 infants in neonatal intensive care units (NICU) surveyed. Among non-NICU patients, 1210 (44.3%) received 1830 antimicrobials of which 73.9% were for empiric or pathogen-directed therapy and 25.6% for prophylaxis. The mean proportion of core Access and Watch group antibiotics was 45.8% and 63.5%, respectively, with no differences in means between tertiary and quaternary care sites. Among 1195 infants in NICU, 19.7% received 410 antimicrobials of which 17.1% were for prophylaxis and a mean of 45.4% were Watch group antibiotics. Of patients admitted for community-acquired pneumonia, 32.7% received penicillin or aminopenicillins only with variability among sites. CONCLUSIONS: PPS of antimicrobial use in Canadian pediatric hospitals revealed a high proportion of Watch group (broader spectrum) antibiotics, even among children with community-acquired pneumonia. This study demonstrates the feasibility of PPS to document antimicrobial use and potentially to use this data to establish goals for decreasing both overall and Watch group antibiotics.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".