Choosing Wisely internationally – helpful recommendations for antimicrobial stewardship!
Bibliographic record
Abstract
PURPOSE: Antimicrobial resistance poses a major threat to human health globally and antibiotic overuse is a main driver of resistance. Antimicrobial stewardship (AMS) was developed to improve the rationale use of antibiotics. The Choosing Wisely campaign was initiated to ameliorate medical practice through avoidance of unnecessary diagnostic and therapeutic procedures. Our objective was to give an overview on the Choosing Wisely recommendations related to AMS practices from a selection of different countries in order to define future needs. METHODS: We evaluated the seven countries already analyzed for Choosing Wisely recommendations related to topics of infectious medicine before. Finally, we included five of the former countries (Australia/New Zealand, Canada, Italy, Switzerland, and USA) and Germany with easily accessible recommendations and selected those related to six categories of AMS as following: diagnostics, indication, choice of antiinfective drugs, dosing, application and duration of therapy. RESULTS: In total, 213 recommendations could be extracted related to AMS for the six countries and were matched to the chosen categories. Interestingly, no recommendations were found for the category "dosing." Topics related to indication and diagnostics were most frequently found with 85 and 78 recommendations, respectively. Perioperative prophylaxis was a frequently addressed issue - both related to application, indication and duration. Avoiding antibiotic treatment of asymptomatic bacteriuria and upper respiratory tract infections were central topics of all countries. CONCLUSION: AMS is an important strategy to fight increasing resistance and is frequently addressed by Choosing Wisely recommendations of different countries. Similar issues are considered important in the selected countries.
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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 | 0.018 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".