Antibiotic Use in a Canadian Province, 1995–1998
Bibliographic record
Abstract
OBJECTIVE: Antibiotics are among the most commonly used classes of agents in community practice; yet, studies of antibiotic use in this setting are scarce. Data from developed countries suggest increasing use of newer broad-spectrum agents, which has implications for the development of antibiotic resistance as well as cost of therapy. In this study, we quantified changing patterns of antibiotic use in community practice in Manitoba, Canada, from 1995 to 1998. DESIGN: A descriptive, population-based study of antibiotic use in Manitoba was facilitated by the Drug Programs Information Network (DPIN) of Manitoba Health; a data management system responsible for recording details of prescriptions dispensed for all Manitoba residents. Antibiotic use data, defined as numbers of prescriptions dispensed, were extracted from the DPIN from January 1, 1995, to March 31, 1998. Antibiotic use is reported as prescriptions per 1000 persons per year (Rx/1000/Yr) based on quarterly use. RESULTS: Penicillins (48.3%), macrolides (16.0%), and sulfonamides (12.5%) accounted for 75% of total antibiotic use; total use decreased 19.1% between 1995 and 1998. Use of the four most commonly prescribed agents decreased over the study period (amoxicillin, -17.4%; erythromycin, -29.0%; trimethoprim/sulfamethoxazole, -18.7%; penicillins G and V, -19.2%). In contrast, use of newer and/or broad-spectrum agents increased (ciprofloxacin, 21.9%; cefuroxime, 30.7%; and azithromycin/clarithromycin, 29.5%). Use of second-line agents as a percentage of total antibiotic use increased from 14.4% to 19.3% between January 1995 and March 1998 (p < 0.001). CONCLUSIONS: Penicillins, macrolides, and sulfonamides accounted for 75% of antibiotic use. Total antibiotic use declined over the study period; however, use of newer, broad-spectrum agents increased while use of older, narrow-spectrum agents decreased.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".