The Effect of Three Cyclo-oxygenase Inhibitors on Intensity of Primary Dysmenorrheic Pain
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of 3 different cyclo-oxygenase (COX) inhibitors on primary dysmenorrheic pain. METHOD: Eleven female patients self-medicated with either placebo (sugar), 25 mg of the COX-2 specific inhibitor rofecoxib, 50 mg of the nonselective COX inhibitor diclofenac potassium, or 7.5 mg of the COX-2 selective inhibitor meloxicam, over 4 menstrual cycles. Pain was assessed using the McGill Pain Questionnaire and a visual analog scale. RESULTS: The pain response index, present pain index, and visual analog scale were highly correlated as measures of intensity of pain (r=0.81 to 0.96, P<0.0001). Rofecoxib and diclofenac potassium both decreased the duration of dysmenorrheic pain compared with placebo (P<0.001) and with meloxicam (P<0.01), and were equally effective in improving pain, compared with placebo, after each capsule (P<0.001). When compared with placebo, both drugs also provided 50% or more pain relief, after each capsule (P<0.0048). Meloxicam, although superior to placebo, was not as effective as rofecoxib and diclofenac potassium in reducing pain, and when compared with placebo, was associated with providing 50% or more of pain relief only after the third and fourth capsules (P=0.016). CONCLUSIONS: Rofecoxib and diclofenac potassium, when taken in recommended doses, were equally effective in alleviating pain associated with primary dysmenorrhea.
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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 | 0.000 |
| 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) | 0.002 | 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".