Advancing antimicrobial stewardship: Summary of the 2015 CIDSC Report
Bibliographic record
Abstract
BACKGROUND: Antimicrobial resistance (AMR) is recognized as an important global public health concern that has a cross-cutting impact on human health, animal health, food and agriculture and the environment. The Communicable and Infectious Disease Steering Committee (CIDSC) of the Pan-Canadian Public Health Network (PHN) created a Task Group on Antimicrobial Stewardship to look at this issue from a Canadian perspective. OBJECTIVE: To summarize the key findings of the Task Group Report that identified core components of antimicrobial stewardship programs, best practices, key challenges, gaps and recommendations to advance stewardship across jurisdictions. METHODS: Search strategies were developed to identify scientific literature, grey literature and relevant websites on antimicrobial stewardship. The information was reviewed and based on this evidence, expert opinion and consensus-building, the Task Group identified core components, best practices, key challenges and gaps and developed recommendations to advance stewardship in Canada. RESULTS: Recommendations to the CIDSC about how to advance stewardship across jurisdictions included the following: institute a national infrastructure; develop best practices to implement stewardship programs; develop education and promote awareness; establish consistent evidence-based guidance, resources, tools and training; mandate the incorporation of stewardship education; develop audit and feedback tools; establish benchmarks and performance targets for stewardship; and conduct timely evaluation of stewardship programs. CONCLUSION: Findings of this report will inform a more systematic approach to addressing antimicrobial stewardship Canada-wide.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".