Cannabis Use and Stroke: Does a Risk Exist?
Bibliographic record
Abstract
AIMS: Cannabis use has been reported as a risk factor for stroke. We systematically review the prevalence and outcomes of stroke in people with cannabis use. METHODS: We searched MEDLINE and 6 other databases from inception to January 2020 for studies on the relationship between cannabis use and stroke. We followed the preferred reporting items for systematic reviews and meta-analyses (PRISMA) recommendations. Two independent reviewers extracted the data. Study quality was assessed by the Newcastle-Ottawa Scale for cohort and case-control studies. RESULTS: Seventeen studies involving 3,185,560 people with cannabis use were included. Descriptive statistics demonstrated 18,676 (median 1.1%, interquartile range [IQR] 0.3%-1.3%) experienced stroke compared with 0.8% of those without use (Odds Ratio 1.17, 95% CI 1.10-1.25). Among people with cannabis use, median age was 26.2 years (IQR 25.2-34.3 years) and mostly male (median 57.8%). Of stroke subtypes, ischemic stroke was most prevalent (median 1.2%, IQR 0.4%-1.9%), followed by undefined stroke subtype (median 1.2%, IQR 1.1%-1.2%) and hemorrhagic stroke (median 0.3%, IQR 0.1%-0.6%). The majority of people with cannabis use who experienced stroke survived (median: 85.1%, IQR 83%-87.5%) and 64.0% of people experienced a good neurologic outcome, defined as modified Rankin Scale of 0 to 3. Few studies included outcomes of vasospasm or seizure. CONCLUSIONS: In people with cannabis use, the prevalence of ischemic stroke and hemorrhagic stroke was 1.2% and 0.3%, respectively, higher than the prevalence of people without use (0.8% and 0.2%). There is insufficient information on timing, exposure, duration, and dose-responsive relationship.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 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 | 0.002 |
| 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 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".