Longitudinal Surveillance of Outpatient Quinolone Antimicrobial Use in Canada
Bibliographic record
Abstract
INTRODUCTION: Because antimicrobial use is commonly associated with the development of antimicrobial resistance, monitoring the volume and patterns of use of these agents is important.OBJECTIVE: To assess the use of quinolone antimicrobials within Canadian provinces over time.METHODS: Antimicrobial prescribing data collected by IMS Health Canada were acquired from the Canadian Integrated Program for Antimicrobial Resistance Surveillance and the Canadian Committee for Antimicrobial Resistance, and were used to calculate two yearly metrics: prescriptions per 1000 inhabitant-days and the mean defined daily doses (DDDs) per prescription. These measures were used to produce linear mixed models to assess differences among provinces and over time, while accounting for repeated measurements.RESULTS: The quinolone class of antimicrobials is used similarly among Canadian provinces. Year-to-year increases in quinolone prescribing occurred from 1995 to 2010, with a levelling off in the latter years. Year-to-year decreases in the DDDs per prescription were found to be significant from 2000 to 2010.DISCUSSION: Although the overall use of antimicrobials differs significantly among Canadian provinces, the use of the quinolone class does not vary at the provincial level. Results suggest that prescribing of ciprofloxacin may be a potential target for antimicrobial stewardship programs; however, decreases in the average DDDs per prescription suggest continued uptake of appropriate treatment guidelines.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".