Tramadol/Acetaminophen Combination Tablets for the Treatment of Pain Associated with Osteoarthritis Flare in an Elderly Patient Population
Bibliographic record
Abstract
OBJECTIVES: To evaluate the efficacy and safety of adding tramadol 37.5 mg/acetaminophen (APAP) 325 mg combination tablets (tramadol/APAP) to existing therapy for painful osteoarthritis (OA) flare in a subset of elderly patients. DESIGN: Randomized, double-blind, placebo-controlled, 10-day add-on study. SETTING: Thirty outpatient centers. PARTICIPANTS: Of 308 patients with painful OA flare, a subset of 113 patients aged 65 and older. MEASUREMENTS: Average daily pain intensity and pain relief scores for Days 1 through 5 and secondary quality-of-life measures and medication assessments. METHODS: Patients received one or two tramadol/APAP tablets or placebo four times per day for 10 days during ongoing nonselective or cyclooxygenase (COX)-2-selective nonsteroidal antiinflammatory drug (NSAID) therapy. RESULTS: Tramadol/APAP (n=69) was significantly superior to placebo (n=44) for average daily pain intensity (P=.034) and pain relief (P=.010) for Days 1 through 5 and Days 1 through 10 (P=.012 and P=.019, respectively). Tramadol/APAP had significantly better investigator (P<.001) and patient (P=.001) overall medication assessments and significantly better scores on three of four Western Ontario and McMaster Universities Osteoarthritis Index measures (P< or =.027). Most common adverse events with tramadol/APAP were nausea (18.8%), vomiting (13.0%), dizziness (11.6%), and constipation (4.3%), with an incidence similar to that of the overall study population. Mean daily dose of tramadol/APAP was 4.5 tablets (168 mg/1,458 mg). CONCLUSION: Tramadol/APAP add-on therapy effectively managed painful OA flare in this elderly subset and was generally well tolerated.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".