Antibiotic prescribing by dentists has increased
Bibliographic record
Abstract
BACKGROUND: Although the overall rate of antibiotic prescribing has been declining in British Columbia, Canada, the authors conducted a study to explain the increased rate of prescribing by dentists. METHODS: The authors obtained anonymized, line-listed data on outpatient prescriptions from 1996 to 2013 from a centralized, population-based prescription database, including a variable coding prescriber licensing body. Analyses used Anatomical Therapeutic Classification standard codes and defined daily dose (DDD) values. The authors normalized prescribing rates to the population and expressed the rates in DDDs per 1,000 inhabitants per day (DID). The Canadian Dental Association released a webinar that invited correspondence from dentists about the drivers of the trend. RESULTS: From 1996 to 2013, overall antibiotic use declined from 18.24 DID to 15.91 DID, and physician prescribing declined 18.2%, from 17.25 DID to 14.11 DID. However, dental prescribing increased 62.2%, from 0.98 DID to 1.59 DID, and its proportionate contribution increased from 6.7% to 11.3% of antibiotic prescriptions. The rate of prescribing increased the most for dental patients 60 years or older. Communication from dentists in Canada and the United States identified the following explanatory themes: unnecessary prescriptions for periapical abscess and irreversible pulpitis; increased prescribing associated with dental implants and their complications; slow adoption of guidelines calling for less perioperative antibiotic coverage for patients with valvular heart disease and prosthetic joints; emphasis on cosmetic practices reducing the surgical skill set of average dentists; underinsurance practices driving antibiotics to be a substitute for surgery; the aging population; and more dental registrants per capita. CONCLUSIONS: Emerging themes for dental prescribing should be explored further in future studies; however, themes already identified may guide priorities in antibiotic stewardship for continuing dental education sessions. PRACTICAL IMPLICATIONS: Antibiotic prescribing should be reviewed to make sure that we are compliant with guidelines. Most practitioners will find opportunities to prescribe less often and for shorter durations.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".