Antimicrobial Use Over a Four‐Year Period Using Days of Therapy Measurement at a Canadian Pediatric Acute Care Hospital
Bibliographic record
Abstract
BACKGROUND: Antimicrobial resistance is a concern that is challenging the ability to treat common infections. Surveillance of antimicrobial use in pediatric acute care institutions is complicated because the common metric unit, the defined daily dose, is problematic for this population. OBJECTIVE: During a four-year period in which no specific antimicrobial stewardship initiatives were conducted, pediatric antimicrobial use was quantified using days of therapy (DOT) per 100 patient days (PD) (DOT/100 PD) at the Alberta Children's Hospital (Calgary, Alberta) for benchmarking purposes. METHODS: Drug use data for systemic antimicrobials administered on wards at the Alberta Children's Hospital were collected from electronic medication administration records. DOT were calculated and rates were determined using 100 PD as the denominator. Changes over the surveillance period and subgroup proportions were represented graphically and assessed using linear regression. RESULTS: Total antimicrobial use decreased from 93.6 DOT/100 PD to 75.7 DOT/100 PD (19.1%) over the 2010/2011 through to the 2013/2014 fiscal years. During this period, a 20.0% increase in PD and an essentially stable absolute count of DOT (2.9% decrease) were observed. Overall, antimicrobial use was highest in the pediatric intensive care and oncology units. DISCUSSION: The exact changes in prescribing patterns that led to the observed reduction in DOT/100 PD with associated increased PD are unclear, but may be a topic for future investigations. CONCLUSION: Antimicrobial use data from a Canadian acute care pediatric hospital reported in DOT/100 PD were compiled for a four-year time period. These data may be useful for benchmarking purposes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".