MétaCan
Menu
Back to cohort
Record W2058391659 · doi:10.1177/0333102412468669

Use of cannabis among 139 cluster headache sufferers

2012· article· en· W2058391659 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCephalalgia · 2012
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsUniversité de MontréalHôpital Notre-Dame
Fundersnot available
KeywordsCannabisMedicineCohortPsychiatryCluster (spacecraft)Cluster headachePediatricsInternal medicineMigraine

Abstract

fetched live from OpenAlex

AIMS: A case report suggested the efficacy of cannabis to treat cluster headache (CH) attacks. Our aims were to study the frequency of cannabis use in CH patients, and the reported effects on attacks. METHODS: A total of 139 patients with CH attending two French headache centers filled out questionnaires. RESULTS: Sixty-three of the 139 patients (45.3%) had a history of cannabis use. As compared to nonusers, cannabis users were more likely to be younger (p < 0.001), male (p = 0.002) and tobacco smokers (p < 0.001). Among the 27 patients (19.4% of the total cohort) who had tried cannabis to treat CH attacks, 25.9% reported some efficacy, 51.8% variable or uncertain effects, and 22.3% negative effects. CONCLUSIONS: Cannabis use is very frequent in CH patients, but its efficacy for the treatment of the attacks is limited. Less than one third of self-reported users mention a relief of their attacks following inhalation. Cannabis should not be recommended for CH unless controlled trials with synthetic selective cannabinoids show a more convincing therapeutic benefit.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.344
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.037
GPT teacher head0.300
Teacher spread0.263 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it