Comparison of Cannabinoid Concentrations in Plasma, Oral Fluid and Urine in Occasional Cannabis Smokers After Smoking Cannabis Cigarette
Bibliographic record
Abstract
PURPOSE: A randomized cross-over, double blind placebo controlled study of smoked cannabis was carried out on occasional cannabis smokers. The objective of this research was to describe the pharmacokinetic parameters of THC and its metabolites in plasma, oral fluid and urine, from samples obtained simultaneously to provide estimations of THC and metabolites concentrations after smoking a cannabis cigarette. METHODS: Blood, oral fluid and urine samples were collected until up to 72 h after smoking the cannabis cigarette (4% of delta-9-tetrathydrocannabinol (THC)). THC, 11-OH-THC and THC-COOH were analyzed by gas-chromatography-mass spectrometry. Pharmacokinetic parameters were estimated from these data. RESULTS: Eighteen male healthy adults participated in the study. In total, 560 plasma, 288 oral fluid and 448 urine samples were quantified for cannabinoids. Plasma, oral fluid and urine pharmacokinetic parameters were calculated. A wide range of median THC Cmax (1.6-160.0 µg/L and 55.4-123120.0 µg/L in plasma and oral fluid, respectively), 11-OH-THC Cmax (0-11.1 µg/L in plasma) and THC-COOH Cmax (1.0-56.3 µg/L in plasma) was observed. When expressed as a percentage of the total available THC dose, and corrected for molar equivalents, mean percentage of total THC dose excreted was 1.9 +/-2.5 % with range of 0.2-7.5%. This high inter-individual variability was also observed on other calculated pharmacokinetic parameters. CONCLUSION: Prediction of plasma THC concentration from THC oral fluid concentration or from THC-COOH urinary concentrations is not feasible due to the large variations observed. The results from this study support the assumption that a positive oral fluid THC result or a positive urine fluid result are indicative of a recent cannabis exposure. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".