Efficacy of celecoxib versus ibuprofen for the treatment of patients with osteoarthritis of the knee: A randomized double-blind, non-inferiority trial
Bibliographic record
Abstract
Objective To compare the efficacy and tolerability of celecoxib and ibuprofen for the treatment of knee osteoarthritis symptoms. Method In this 6-week, multicentre, double-blind, non-inferiority trial, patients were randomized to 200 mg celecoxib once daily, 800 mg ibuprofen three times daily or placebo. The primary outcome was non-inferiority of celecoxib to ibuprofen in Patient's Assessment of Arthritis Pain (scored 0-100). Secondary outcomes included the Western Ontario and McMaster Universities (WOMAC) Osteoarthritis Index, Pain Satisfaction Scale, and upper gastrointestinal tolerability. Results A total of 388 patients were treated (celecoxib n = 153; ibuprofen n = 156; placebo n = 79). Mean difference (95% confidence interval) between celecoxib and ibuprofen in the Patient's Assessment of Arthritis Pain was 2.76 (-3.38, 8.90). As the lower bound was greater than -10, celecoxib was non-inferior to ibuprofen. The WOMAC total score was significantly improved with celecoxib and ibuprofen, versus placebo. Patients receiving celecoxib were significantly more satisfied (versus placebo) in 10 of 11 measures on the Pain Satisfaction Scale versus three measures with ibuprofen. Upper gastrointestinal events were less frequent with celecoxib (1.3%) than ibuprofen (5.1%) or placebo (2.5%). Conclusion Celecoxib was well tolerated and as effective as ibuprofen for symptoms associated with knee osteoarthritis. ClinicalTrials.gov identifier NCT00630929.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".