Codeine and opioid metabolism
Bibliographic record
Abstract
PURPOSE OF REVIEW: Use of perioperative opioids for surgical pain management of children presents clinical challenges because of concerns of serious adverse effects including life-threatening respiratory depression. This is especially true for children with history of obstructive sleep apnea. This review will explore current knowledge of clinically relevant factors and genetic polymorphisms that affect opioid metabolism and postoperative outcomes in children. RECENT FINDINGS: Within the past several years, an increasing number of case reports have illustrated clinically important respiratory depression, anoxic brain injuries and even death among children receiving appropriate weight-based dosages of codeine and other opioids for analgesia at home setting particularly following tonsillectomy. Several national and international organizations have issued advisories on use of codeine in pediatrics, based on cytochrome P450 family 2 subfamily D type 6 (CYP2D6) pharmacogenetics. We have discussed the pros and cons of alternatives to codeine for pain management. SUMMARY: Although routine preoperative genotyping to identify children at risk and personalized opioid use for pediatric perioperative pain management is still a distant reality, current known implications of CYP2D6 pharmacogenetics on codeine use shows that pharmacogenetics has the potential to guide anesthesia providers on perioperative opioid selection and dosing to maximize efficacy and safety.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".