Concentrations of Delta 9-tetrahydrocannabinol (THC) in oral fluid at different time points after use: An individual participant meta-analysis
Bibliographic record
Abstract
Background: Delta 9-tetrahydrocannabinol (THC) concentrations in oral fluid (OF) at different time points after cannabis administration and factors related to these concentrations have not been previously described in a meta-analysis. This information is critical for better understanding of these tests for detection of prior cannabis use and cannabis impairment. Objectives: : To describe the independent contribution of each of the variables in Objective 2, based on a multivariate analysis of THC concentrations. Methods: A meta-analysis of studies from two databases (PubMed and Scopus) was conducted. Our inclusion criteria included published empirical articles that administered natural cannabis to subjects in a controlled setting, with OF drug tests showing the exact THC concentrations in OF for each subject (i.e., raw data) for at least two time points after cannabis administration using confirmatory methods. Seven studies of tests with published raw data for OF THC after cannabis administration met these criteria (n observations = 1157). Results: Summary statistics showed OF THC concentrations by time after use were highly dispersed at every time point, positively skewed, and declined over time. Many positive OF THC concentrations were found after 24-h in one study, but most studies did not conduct observations past 24 h. In a multivariate analysis, we found that increased dose, increased frequency of cannabis use, and inhaled (versus ingested) cannabis were statistically related to higher OF THC concentrations. OF collection with the intercept DOA device was significantly higher than expectorant (i.e. saliva) and being male (versus female) were only significant in a bivariate analysis. Too little data existed to reliably analyze the possible influence of other variables of age, race and body mass index (BMI) on OF THC concentrations. Discussion: False negatives exist when the tests are used to detect prior use. OF test results are related to confounders of frequency of cannabis use and inhaled (versus ingested) cannabis. OF tests can produce positives at a cut-off 1.0 ng/mL well beyond 24 h. The tests are not valid to detect cannabis impairment. More information is needed on the influence of potential confounders for OF concentrations. We do not have a good idea of the degree to which the subjects in these studies are representative of persons who use cannabis. Overall, more research is needed for these tests to be used in workplace settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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 teacher head, 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".