Part 2: Drug Interactions Involving Cannabis Products in Persons Aged 18 and Over: A Summary of Published Case Reports and Analysis of the <scp>FDA</scp> Adverse Event Reporting System
Bibliographic record
Abstract
The increasing utilization of cannabis products combined with lack of data regarding potential cannabis-prescription drug interactions is concerning. This study aimed to review published case reports and FDA Adverse Event Reporting System (FAERS) spontaneous reports to assess cannabis-drug interactions in persons aged 18 and over. A literature search identified 20 case reports that were each assessed for drug interaction causality using the Drug Interaction Probability Scale. Data collected from the FAERS revealed a greater proportion of reports mentioning serious outcomes, including death, when cannabis was used concomitantly with controlled substances compared to noncontrolled substances. Fisher's exact test showed a statistically significant difference between the controlled and noncontrolled groups (p = 0.043). Overall, these findings emphasize the need for additional research and vigilant monitoring of cannabis use when combined with other medications.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".