A comparison of the efficacy and safety of nonsteroidal antiinflammatory agents versus acetaminophen in the treatment of osteoarthritis: A meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: To perform a meta-analysis comparing the efficacy and safety of recommended dosages of nonsteroidal antiinflammatory drugs (NSAIDs), including cyclooxygenase 2 inhibitors, versus acetaminophen in the treatment of symptomatic hip and knee osteoarthritis. METHODS: Medline and EMBASE searches were performed for original clinical trials directly comparing NSAIDs with acetaminophen. A standardized form was used to abstract all data, including outcome measures of pain at rest, walking pain, and dropouts due to adverse effects. Inverse-variance-weighted mean differences (WMDs) and 95% confidence intervals (95% CI) for pain measures were determined for treatment groups. Odds ratios (ORs) and 95% CIs were calculated for withdrawals due to adverse events. Results were compared using a random effects model. RESULTS: Seven articles met inclusion criteria with sufficient data for analysis. Participants had a mean age of 61.1 years and 71.1% were women. Test of heterogeneity was not significant for either rest (P = 0.73) or walking (P = 0.76) pain. The scores for overall pain at rest (WMD -6.33 mm on a 100-mm visual analog scale [VAS], 95% CI -9.24, -3.41) and walking pain (WMD -5.76 mm on a 100-mm VAS, 95% CI -8.99, -2.52) favored the NSAID-treated group. Although NSAIDs elevated the risk of withdrawals due to adverse events, the difference was not statistically significant (OR 1.45, 95% CI 0.93, 2.27). CONCLUSION: NSAIDs are statistically superior in reducing rest and walking pain compared with acetaminophen for symptomatic osteoarthritis. Safety, measured by discontinuation due to adverse events, was not statistically different between NSAID- and acetaminophen-treated groups.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".