An investigation of morphine‐to‐codeine metabolic ratios in postmortem blood, drug interactions, and cytochrome P450 2D6 (CYP2D6) genotype
Bibliographic record
Abstract
The objective of this study was to investigate the correlation between CYP2D6 genotype, drug interactions, and morphine‐to‐codeine metabolic ratio (MR) in codeine‐related deaths (CRD). The records of the Office of the Chief Coroner of Ontario were examined to identify all CRD from 2006–2008. Deaths in which codeine and its metabolite, morphine, were quantified on the toxicological screen were included. From these, cases in which the manner of death was undetermined, heroin use was suspected, and/or morphine use was suspected were excluded. A total of 59 CRD were included. Postmortem blood samples were analyzed for 17 polymorphisms in CYP2D6 as well as gene duplication. The frequencies of CYP2D6 ultrarapid, extensive, intermediate, and poor metabolizer (PM) was not different in CRDs and a previously published healthy cohort taking opioids. Alcohol use prior to death was significantly associated with CRD that were deemed to be accidental by the coroner (p=0.05). The presence of a selective‐serotonin reuptake inhibitor was significantly associated with suicides (p=0.014). PM was associated with low MR. These findings suggest that CYP2D6 genotype and drug interactions should considered as part of the postmortem toxicological interpretation for CRD, especially in cases with low or high MR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".