Effects of pharmacogenetic profiles on pediatric pain relief and adverse events with ibuprofen and oxycodone
Bibliographic record
Abstract
Abstract Introduction: Individual genetic variation may influence clinical effects for pain medications. Effects of CYP2C9, CYP3A4, and CYP2D6 polymorphisms on clinical effectiveness and safety for ibuprofen and oxycodone were studied. Objective: Primary objectives were to AU2 evaluate if allelic variations would affect clinical effectiveness and adverse events (AEs) occurrence. Methods: This pragmatic prospective, observational cohort included children aged 4 to 16 years who were seen in a pediatric emergency department with an acute fracture and prescribed ibuprofen or oxycodone for at-home pain management. Saliva samples were obtained for genotyping of allelic variants, and daily telephone follow-up was conducted for 3 days. Pain was measured using the Faces Pain Scale-Revised. Results: We included 210 children (n = 140 ibuprofen and n = 70 oxycodone); mean age was 11.1 (±SD 3.5) years, 33.8% were female. Median pain reduction on day 1 was similar between groups [ibuprofen 4 (IQR 2,4) and oxycodone 4 (IQR 2,6), P = 0.69]. Over the 3 days, the oxycodone group experienced more AE than the ibuprofen group (78.3% vs 53.2%, P < 0.001). Those with a CYP2C9*2 reduced function allele experienced less adverse events with ibuprofen compared with those with a normal functioning allele CYP2C9*1 ( P = 0.003). Neither CYP3A4 variants nor CYP2D6 phenotype classification affected clinical effect or AE. Conclusion: Although pain relief was similar, children receiving oxycodone experienced more AE, overall, than those receiving ibuprofen. For children receiving ibuprofen or oxycodone, pain relief was not affected by genetic variations in CYP2C9 or CYP3A4/CYP2D6, respectively. For children receiving ibuprofen, the presence of CYP2C9*2 was associated with less adverse events.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 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) | 0.000 | 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 teacher head, 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".