Emergency department visits during the 4/20 cannabis celebration
Bibliographic record
Abstract
BACKGROUND: Annual '4/20' cannabis festivals occur around the world on April 20 and often feature synchronised consumption of cannabis at 4:20 pm. The relationship between these events and demand for emergency medical services has not been systematically studied. METHODS: We conducted a population-based retrospective cohort study in Vancouver, Canada, using 10 consecutive years of data (2009-2018) from six regional hospitals. The number of emergency department (ED) visits between 4:20 pm and 11:59 pm on April 20 were compared with the number of visits during identical time intervals on control days 1 week earlier and 1 week later (ie, April 13 and April 27) using negative binomial regression. RESULTS: A total of 3468 ED visits occurred on April 20 and 6524 ED visits occurred on control days. A non-significant increase in all-cause ED visits was observed on April 20 (adjusted relative risk: 1.06; 95% CI 1.00 to 1.12). April 20 was associated with a significant increase in ED visits among prespecified subgroups including a 5-fold increase in visits for substance misuse and a 10-fold increase in visits for intoxication. The hospital closest to the festival site experienced a clinically and statistically significant 17% (95% CI 5.1% to 29.6%) relative increase in ED visits on April 20 compared with control days. INTERPRETATION: Substance use at annual '4/20' festivals may be associated with an increase in ED visits among key subgroups and at nearby hospitals. These findings may inform harm reduction initiatives and festival medical care service planning.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".