Bibliographic record
Abstract
Background: In Canada, marijuana is legal for those with seizures. We determined the prevalence of marijuana use in intractable epilepsy patients and assessed the perceived effects. Methods: Information about marijuana use was collected over 12 months from consecutive adult patients admitted to an 8 bed Epilepsy Monitoring Unit using a 27 item self-administered questionnaire. Patients unable to understand and give consent for participation were excluded. Results: 215 of 310 patients median age 36 (interquartile range 27-49) years, 57% female had proven epilepsy. Median duration of seizures was 12 years (interquartile range 5-24) occurring daily or weekly in 47%. 37% of patients used marijuana over the previous year, 85% by smoking and 56% on a daily basis. Mean dose was 1 gm/day. Another 19% had used it previously. Use of cigarettes was 27%, alcohol, 40% and street drugs 2%. Seizure improvement was perceived by 91%, decreased stress by 99%, improved sleep by 98% and reduction in antiepileptic drug side effects by 88%. Minor adverse effects of marijuana occurred in 13% including seizures worse in 3%. Conclusions: Patients investigated for intractable epilepsy use marijuana more than the general population and perceive improved seizure control, lower stress, better sleep and reduced side effects from antiseizure drugs.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".