Evaluation of the Prescription Patterns of Antibiotics among Oral and Maxillofacial Surgeons in Canada
Bibliographic record
Abstract
Background: The rise in bacterial resistance is attributed to the inappropriate or unnecessary use of antibiotics. Objectives: The aim of this study was to evaluate the current knowledge and antibiotic prescription patterns among Canadian oral and maxillofacial surgeons. Methods: A web-based survey featuring 17 clinical scenarios was distributed to active oral and maxillofacial surgeons in Canada. The sample group was asked questions about their management these clinical scenarios. Descriptive and multivariate logistic regression analyses were performed (P ≤ .05). Results: More than half of the prescriptions were generated in clinical scenarios where there is little evidence to support their use. Most prescriptions followed the correct antibiotic regimen. Clinicians with a limited scope of practice had a significantly higher overprescribing index rate than those with a more extensive scope of practice. Conclusion: Improving the available evidence and ensuring that all practitioners have up-to-date, evidence-based guidelines could help minimize unnecessary antibiotic use.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| 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".