Provincial and Temporal Variation in Macrolide and Lincosamide Antimicrobial Use by Outpatients in Canada, 1995 to 2010
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 very important. OBJECTIVE: To assess the use of macrolide and lincosamide (ML) antimicrobials within Canadian provinces over time, and to compare use rates with those reported by European countries. METHODS: ANTIMICROBIAL PRESCRIBING DATA WERE USED TO DEVELOP TWO YEARLY METRICS: prescriptions per 1000 inhabitant-days (PrIDs) and the mean defined daily doses (DDDs) per prescription, which were then used to build linear mixed models to assess differences among provinces over time. RESULTS: After accounting for repeated measures over time, prescribing rates (PrIDs) varied significantly according to province and year (P<0.001). However, little change occurred within each province over the time frame studied; from 1995 to 2010, each province had a PrID change <0.01. Quebec and British Columbia had significantly lower prescribing rates than all other provinces. No overall secular trend was apparent. In contrast, the DDDs per prescription did not vary significantly according to province, but showed a significant year-to-year increase. DISCUSSION: ML prescribing varied among provinces in Canada between 1995 and 2010, but remained relatively stable within each province. The average DDDs per ML prescription did not vary according to province, but increased linearly over time. These increases are likely to indicate that fewer prescriptions are being written for children over time, a practice supported by good antimicrobial stewardship principles.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".