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Record W4368360306 · doi:10.1093/alcalc/agad031

Cannabidiol as a candidate pharmacotherapy for sleep disturbance in alcohol use disorder

2023· article· en· W4368360306 on OpenAlexaff
Marie Gendy, Benício N. Frey, Michael Van Ameringen, Nirushi Kuhathasan, James MacKillop

Bibliographic record

VenueAlcohol and Alcoholism · 2023
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsAlcohol use disorderCannabidiolContext (archaeology)Sleep disorderMedicinePsychiatryInsomniaCannabisAlcohol

Abstract

fetched live from OpenAlex

Among individuals with alcohol use disorder (AUD), it is estimated that the majority suffer from persistent sleep disturbances for which few candidate medications are available. Our aim wass to critically review the potential for cannabidiol (CBD) as a treatment for AUD-induced sleep disturbance. As context, notable side effects and abuse liability for existing medications for AUD-induced sleep disturbance reduce their clinical utility. CBD modulation of the endocannabinoid system and favorable safety profile have generated substantial interest in its potential therapeutic use for various medical conditions. A number of preclinical and clinical studies suggest promise for CBD in restoring the normal sleep-wake cycle and in enhancing sleep quality in patients diagnosed with AUD. Based on its pharmacology and the existing literature, albeit primarily preclinical and indirect, CBD is a credible candidate to address alcohol-induced sleep disturbance. Well-designed RCTs will be necessary to test its potential in managing this challenging feature of AUD.

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.

How this classification was reachedexpand

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.358
Teacher spread0.320 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2023
Admission routes1
Has abstractyes

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