Cannabis use and risks of respiratory and all-cause morbidity and mortality: a population-based, data-linkage, cohort study
Bibliographic record
Abstract
INTRODUCTION: Although cannabis is frequently used worldwide, its impact on respiratory health is characterised by controversy. OBJECTIVE: To evaluate the association between cannabis use and respiratory-related emergency room (ER) visits and hospitalisations. METHODS: A retrospective, population-based, cohort study was carried out, linking health survey and health administrative data for residents of Ontario, Canada, aged 12-65 years, between January 2009 and December 2015. Individuals self-reporting cannabis use within the past year were matched to control individuals (people who reported never using cannabis, or used cannabis only once, and more than 12 months ago) in upwards of a 1:3 ratio on 31 different variables, using propensity score matching methods. Respiratory-related and all-cause ER visits or hospitalisations, and all-cause mortality, were evaluated up to 12 months following the index date. RESULTS: We identified 35 114 individuals who had either used cannabis in the past year or were controls, of whom 6425 (18.3%) used cannabis in the past year. From this group, 4807 (74.8%) were propensity-score matched to 10 395 control individuals. In the propensity score matched cohort, there was no significant difference in odds of respiratory-related ER visit or hospitalisation between cannabis users and the control group (OR 0.91, 95% CI 0.77 to 1.09). Compared with control individuals, cannabis users had significantly increased odds of all-cause ER visit or hospitalisation (OR 1.22, 95% CI 1.13 to 1.31) and there was no significant difference with respect to all-cause mortality (OR 0.99, 95% CI 0.49 to 2.02). CONCLUSIONS: Although no significant association was observed between cannabis use and respiratory-related ER visits or hospitalisations, the risk of an equally important morbidity outcome, all-cause ER visit or hospitalisation, was significantly greater among cannabis users than among control individuals. Therefore, cannabis use is associated with increased risk for serious adverse health events and its recreational consumption is not benign.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".