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Record W2169530775 · doi:10.1093/jat/bku096

Quantitation of Methadone and Metabolite in Patients under Maintenance Treatment

2014· article· en· W2169530775 on OpenAlexfundno aff
Shiau Hui Diong, Nor Shuhadah Mohd Yusoff, Maw Shin Sim, Raja Elina Raja Aziddin, Zamri Chik, Poppy Rajan, Rusdi Abd Rashid, Norliza Chemi, Zahurin Mohamed

Bibliographic record

VenueJournal of Analytical Toxicology · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicForensic Toxicology and Drug Analysis
Canadian institutionsnot available
FundersUniversiti MalayaRyerson University
KeywordsMethadoneUrineMetabolitePharmacokineticsMethadone maintenanceChromatographyChemistryUrinary systemMedicinePharmacologyInternal medicine

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.208
Threshold uncertainty score0.580

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.068
GPT teacher head0.412
Teacher spread0.344 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations20
Published2014
Admission routes1
Has abstractyes

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