Analgesic Use for Knee and Hip Osteoarthritis in Community-Dwelling Elders
Bibliographic record
Abstract
OBJECTIVE: To examine the prevalence and correlates of non-opioid and opioid analgesic use and descriptively evaluate potential undertreatment in a sample of community-dwelling elders with symptomatic knee and/or hip osteoarthritis (OA). DESIGN: Cross-sectional. SETTING: Health, Aging, and Body Composition Study. PATIENTS: Six hundred and fifty-two participants attending the year 6 visit (2002-03) with symptomatic knee and/or hip OA. OUTCOME MEASURES: Analgesic use was defined as taking ≥1 non-opioid and/or ≥1 opioid receptor agonist. Non-opioid and opioid doses were standardized across all agents by dividing the daily dose used by the minimum effective analgesic daily dose. Inadequate pain control was defined as severe/extreme OA pain in the past 30 days from a modified Western Ontario and McMaster Universities Osteoarthritis Index. RESULTS: Just over half (51.4%) reported taking at least one non-opioid analgesic and approximately 10% was taking an opioid, most (88.5%) of whom also took a non-opioid. One in five participants (19.3%) had inadequate pain control, 39% of whom were using <1 standardized daily dose of either a non-opioid or opioid analgesic. In adjusted analyses, severe/extreme OA pain was significantly associated with both non-opioid (adjusted odds ratio [AOR] = 2.44; 95% confidence interval [95% CI] = 1.49-3.99) and opioid (AOR = 2.64; 95% CI = 1.26-5.53) use. CONCLUSIONS: Although older adults with severe/extreme knee and/or hip OA pain are more likely to take analgesics than those with less severe pain, a sizable proportion takes less than therapeutic doses and thus may be undertreated. Further research is needed to examine barriers to optimal analgesic use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".