Emergency department visits during the 4/20 cannabis celebration
Bibliographic record
Abstract
BACKGROUND: In many cities, annual "4/20" cannabis festivals occur on April 20 and often feature synchronized consumption of cannabis at 4:20 p.m. 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 ten consecutive years of data (2009 to 2018) from six regional hospitals. The number of emergency department (ED) visits between 4:20 p.m. and 11:59 p.m. on April 20 were compared to the number of visits during identical time intervals on control days one week earlier and one week later (i.e. April 13 and April 27) using negative binomial regression. RESULTS: A total of 3,468 ED visits occurred on April 20 and 6,524 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 - 1.12). April 20 was associated with a significant increase in ED visits among pre-specified subgroups including a five-fold increase in visits for substance misuse and a ten-fold increase in visits for intoxication. The hospital closest to the festival site experienced a clinically and statistically significant 17% (95% CI, 5.1% - 29.6%) relative increase in ED visits on April 20 compared to control days. INTERPRETATION: Substance use at annual "4/20" festivals may be associated with an increase in emergency department 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 | 0.001 |
| 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".