Use of a simple pain model to evaluate analgesic activity of ibuprofen versus paracetamol
Bibliographic record
Abstract
OBJECTIVE: To evaluate the analgesic activity of ibuprofen against paracetamol using a simple pain model. DESIGN: A double-blind study. SETTING: Twenty general practitioners in Harare, Zimbabwe. PATIENTS: Adults with acute sore throat of a maximum of two days' duration. INTERVENTIONS: One hundred and thirteen patients with acute pain associated with tonsillo-pharyngitis randomly received either 400 mg ibuprofen or 1000 mg paracetamol. The study design included repeated administration up to 48 hours to assess tolerability. MAIN OUTCOME MEASURES: At hourly intervals for six hours after the first dose of treatment, the patients evaluated pain intensity on swallowing, difficulty in swallowing and global pain relief according to visual analogue scales. RESULTS: Ibuprofen 400 mg was significantly more effective than paracetamol 1000 mg in all three ratings, at all time-points for pain intensity and difficulty in swallowing, and from two hours onwards for pain relief. There were no serious adverse effects and no statistically significant difference in the incidence of adverse effects in the two treatment groups. CONCLUSIONS: Sore throat pain provided a sensitive model to assess the analgesic efficacy of class I analgesics and discriminated between the analgesic efficacy of ibuprofen and paracetamol.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".