Variability in the Analgesic Response to Ibuprofen Is Associated With Cyclooxygenase Activation in Inflammatory Pain
Bibliographic record
Abstract
The mechanisms underlying interindividual variability in analgesic efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs) are not well understood. Therefore, we performed pain phenotyping, functional neuroimaging, pharmacokinetic/pharmacodynamic assessments, inflammation biomarkers, and gene expression profiling in healthy subjects who underwent surgical extraction of bony impacted third molars and were treated with ibuprofen (400 mg; N = 19) or placebo (N = 10). Analgesic efficacy was not associated with demographic or clinical characteristics, ibuprofen pharmacokinetics, or the degree of cyclooxygenase inhibition by ibuprofen. Compared with partial responders to ibuprofen (N = 9, required rescue medication within the dosing interval), complete responders (N = 10, no rescue medication) exhibited greater induction of urinary prostaglandin metabolites and serum tumor necrosis factor-α and interleukin 8. Differentially expressed genes in peripheral blood mononuclear cells were enriched for inflammation-related pathways. These findings suggest that a less pronounced activation of the inflammatory prostanoid system is associated with insufficient pain relief on ibuprofen alone and the need for additional therapeutic intervention.
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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) | 0.000 | 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) | 0.001 | 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".