GC-MS Quantitation of Codeine, Morphine, 6-Acetylmorphine, Hydrocodone, Hydromorphone, Oxycodone, and Oxymorphone in Blood*
Bibliographic record
Abstract
A method is described for the simultaneous analysis of seven opiates, codeine, morphine, 6-acetylmorphine, hydrocodone, hydromorphone, oxycodone, and oxymorphone, in blood samples by gas chromatography-mass spectrometry (GC-MS). One milliliter of blood is combined with an internal standard mixture containing 200 ng of each of the seven deuterated opiates. Two milliliters of acetonitrile is added to precipitate the proteins and cellular material. After centrifugation, the clear supernatant is removed, and the acetonitrile is evaporated. The remaining aqueous portion is adjusted to pH 9 with sodium bicarbonate buffer, and the drugs are extracted into chloroform/trifluoroethanol (10:1). The organic extractant is transferred and dried under nitrogen. The residue is reconstituted in dilute hydrochloric acid and washed consecutively with hexane and chloroform. The purified aqueous portion is adjusted to pH 9 with bicarbonate buffer, and the drugs are again extracted into chloroform/trifluoroethanol (10:1). The organic portion is removed from the aqueous fraction and dried under nitrogen. The residue is consecutively derivatized with methoxyamine and propionic anhydride using pyridine as a catalyst. The ketone groups on hydrocodone, hydromorphone, oxycodone, and oxymorphone are converted to methoximes. Hydroxyl groups present at the O3 and O6 positions of codeine, morphine, 6-acetylmorphine, hydromorphone, and oxymorphone are converted to their respective propionyl esters. After a postderivatization purification step, the extracts are analyzed by full scan GC-MS using electron impact ionization. The method is linear to at least 2000 ng/mL. Day-to-day precision (N = 15) at 500 ng/mL and 75 ng/mL were less than 10% for all seven targeted opiates. Extraction efficiencies at these two concentrations ranged from 50% to 68%. For each opiate, the limit of quantitation was 10 ng/mL, and the limit of detection was 2 ng/mL.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".