OUTPATIENT MEDICATION USE AND IMPLICATIONS FOR DENTAL CARE: GUIDANCE FOR CONTEMPORARY DENTAL PRACTICE.
Bibliographic record
Abstract
BACKGROUND: Adverse effects of medication used in dental care are likely to increase as North Americans live longer, experience more and greater severity of chronic conditions and take more medications. Thus, documentation of medication use and the implications for contemporary dental practice is of increasing importance. METHODS: We recorded medication use in patients referred to a large private periodontal practice in Ottawa, Ontario. Patients self-reported medication use and medication allergies in their health history forms on admission. RESULTS: Of 322 sequential patients enrolled, 164 were female and the overall median age was 52 (range 6-94 years). Participants reported taking 249 unique medications in 28 categories. Two-thirds of patients (63.7%) were taking prescription or over-the-counter (OTC) medications or both. The average number of medications per patient was 1.9 (range 0-14). The average number of OTC medications per patient was 0.5 for those not taking prescription medications and 0.4 for patients taking prescription medications concurrently. The number of OTC products per patient was 0-7. CONCLUSIONS: Given the prevalence of the use of both prescription and OTC products, accurate recording of the medication profile is necessary in contemporary dental practice. Medication use and medication allergies provide information on patients' medical history and diagnoses that may have implications for their oral condition and delivery of dental care. Additional concerns include potential interactions between frequently used medications reported by patients and medications that are commonly used in dentistry. CLINICAL IMPLICATIONS: The increase in the use of multiple medications and OTC products by the outpatient community has an impact on dental care and prescribed medications in dental care. Thus, it is important to have a complete and accurate medication history to ensure a high standard of care in dental practice.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".