Cannabis, Cannabinoids, and Stroke: Increased Risk or Potential for Protection—A Narrative Review
Bibliographic record
Abstract
Worldwide, approximately 15 million people per year suffer from stroke. With about 5 million deaths, stroke is the second most common cause of death and a major cause of long-term disability. It is estimated that about 25% of people older than 85 years will develop stroke. Cannabis sativa and derived cannabinoids have been used for recreational and medical purposes for many centuries. However, due to the legal status in the past, research faced restrictions, and cannabis use was stigmatized for potential negative impacts on health. With the changes in legal status in many countries of the world, cannabis and cannabis-derived substances such as cannabinoids and terpenes have gained more interest in medical research. Several medical effects of cannabis have been scientifically proven, and potential risks identified. In the context of stroke, the role of cannabis is controversial. The negative impact of cannabis use on stroke has been reported through case reports and population-based studies. However, potential beneficial effects of specific cannabinoids are described in animal studies under certain conditions. In this narrative review, the existing body of evidence regarding the negative and positive impacts of cannabis use prior to stroke will be critically appraised.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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".