Tramadol for osteoarthritis: a systematic review and metaanalysis.
Bibliographic record
Abstract
OBJECTIVE: Tramadol is increasingly used for the treatment of osteoarthritis (OA) because it does not produce gastrointestinal bleeding or renal problems and does not affect articular cartilage. We sought to determine the analgesic effectiveness, the effect on physical function, the duration of benefit, and the safety of oral tramadol in people with OA. METHODS: We searched the Cochrane Central Register of Controlled Trials (Central), Medline, Embase, and Lilacs databases up to August 2005. We included randomized controlled trials (RCT) that evaluated the effect of tramadol or tramadol plus paracetamol on pain levels and/or physical function. No language restriction was applied. RESULTS: We included 11 RCT with a total of 1019 participants who received tramadol or tramadol/paracetamol and 920 participants who received placebo or active control. Participants who received tramadol reported (1) less pain [-8.5 units on a 0-100 scale; (95% CI -12.0 to -5.0)], a 12% relative decrease in pain intensity; (2) higher degree of global improvement: one of every 6 individuals taking tramadol or tramadol/paracetamol exhibited at least moderate global improvement (95% CI 4 to 9); and (3) improvement in stiffness and function, an 8.5% relative improvement in Western Ontario and McMaster University Osteoarthritis Index score, than patients who received placebo. In terms of adverse events, one of every 5 participants who received tramadol or tramadol/paracetamol experienced minor adverse events and one of every eight stopped taking the medication because of adverse events (95% CI 7 to 12) compared to participants who received placebo. CONCLUSION: Tramadol or tramadol/paracetamol decreases pain intensity, produces symptom relief, and improves function in patients with OA, but these benefits are small.
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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 | 0.011 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.024 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".