Appropriateness of NSAID and Coxib prescribing for patients with osteoarthritis by primary care physicians in Ontario: results from the CANOAR study.
Bibliographic record
Abstract
OBJECTIVE: To assess the appropriateness of nonsteroidal anti-inflammatory drug (NSAID) use relative to recent osteoarthritis treatment guidelines from the Second Canadian Consensus Conference. STUDY DESIGN: Observational study of self-reported practice in a cohort of physicians from the Canadian Osteoarthritis Rx (CANOAR) study. SUBJECTS AND METHODS: Ontario primary care physicians were recruited from the top 10% of NSAID prescribers based on the number of NSAID prescriptions filled per year. Physicians were asked to record office visits on a 1-page data collection form from November 2000 to December 2001. RESULTS: Of 1400 physicians invited, 185 were enrolled and 119 registered office visits. Data were analyzed for the first visits of 5459 patients for whom a prescribed NSAID was identified, of whom 60% were female and 46% were older than 65 years. Coxibs were prescribed for 56% of study patients and were more commonly used by those with recent gastrointestinal (GI) events (85%), those receiving warfarin sodium therapy (79%), and those with congestive heart failure (68%). Coxib use increased with increasing global assessment of OA severity, but not patient age. Overall, 58% of prescriptions were considered appropriate given patient GI risk factors. CONCLUSIONS: Most coxib and NSAID prescriptions were consistent with the guidelines, but there was considerable underuse of coxibs in at-risk patients and some overuse of coxibs and of gastroprotective agents with NSAIDs in patients with no identified GI risk factors. Increased recognition of relationships between patient age and NSAID-related GI risk would likely promote more appropriate use of traditional NSAIDs, coxibs, and gastroprotective agents in osteoarthritis patients.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".