Identifying clinically relevant subgroups of patients with knee pain flares for ibuprofen treatment: a secondary analysis
Bibliographic record
Abstract
OBJECTIVE: We aimed to evaluate whether subgroups with more severe inflammatory symptoms during a knee pain flare benefited more from a high dose ibuprofen treatment than subgroups with less severe inflammatory symptoms. METHODS: This secondary analysis included adults with ≥ 1 flares of knee pain in the last year, who experienced a new episode within 24 h and randomized into two treatment groups of daily ibuprofen 1200 mg or 2400 mg for 5 days. A multilevel regression analysis was used to assess interaction effects between intervention groups and pre-defined subgroups, based on osteoarthritis related symptoms (severity of morning stiffness, swelling, and pain). The primary outcome was the difference in treatment effect between subgroups on pain severity (0-10 on the numeric rating scale (NRS)) after 5 days. Differences in treatment effect between subgroups after 3 days (NRS) and 5 days (Western Ontario and McMaster Universities Osteoarthritis (WOMAC) scale) were secondary outcomes. RESULTS: Participants (N = 308) had a mean age of 52.4 ± 12.9 (SD) years with 41% female subjects. No significant interaction was found between the pre-defined subgroups and intervention groups on pain severity after day 5 (all p-values ≥ 0.28) or on the secondary outcomes (all p-values ≥ 0.38). Given the potential lack of power, the absolute and adjusted mean differences between treatment arms were compared for each subgroup; none of the differences reached clinical significance. CONCLUSION: Between subgroups with more and less severe inflammatory symptoms during knee pain flares, no significant nor clinical benefit was found from a higher dose of ibuprofen compared to a lower dose. Keypoints • Despite the overall superiority of the higher dose, patients with severe inflammatory knee symptoms do not benefit more from an anti-inflammatory dose of ibuprofen than patients with less severe symptoms. • A higher dose of ibuprofen is not indicated for patients with severe inflammatory knee symptoms. • Given the heterogeneity among patients with knee osteoarthritis, potential subgroups should be explored in future research.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".