Quantitation of Methadone and Metabolite in Patients under Maintenance Treatment
Bibliographic record
Abstract
Gas chromatography-mass spectrometry quantitative method was developed to monitor concentrations of methadone and its metabolite 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP) in plasma and urine of patients. The developed method was simple, accurate and reproducible to quantify methadone and EDDP in plasma and urine samples in the concentration range of 15-1,000 and 50-2,000 ng/mL, respectively. The proposed analytical method was applied to plasma and urine samples obtained from 96 patients undergoing methadone maintenance treatment (MMT) with daily methadone doses of 2-120 mg/day. Urinary methadone excretion was observed to be significantly affected by pH, in which the ratio of methadone to EDDP was two times higher in acidic urine (P = 0.029). The findings of this study further enhance the guidelines for monitoring of methadone treatment among outpatients. Methadone-to-EDDP ratio in urine was found to be consistent at 24 and 4 h, hence suggesting the possibility that outpatients may be monitored with single urine sample in order to check for compliance. This study which provides data on peak concentrations of methadone and EDDP as well as the ratio of both compounds has added to the body of knowledge regarding pharmacokinetic properties of methadone among heroin-dependent patients under MMT.
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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 | 0.001 | 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 | 0.000 |
| 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 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".