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Record W4408786136 · doi:10.1186/s13722-025-00552-3

Rethinking trazodone for insomnia in alcohol use disorder

2025· article· en· W4408786136 on OpenAlex
Jeffrey Pan, Jürgen Rehm, Evan Wood

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAddiction Science & Clinical Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsUniversity of British ColumbiaCentre for Addiction and Mental HealthPublic Health OntarioUniversity of TorontoBritish Columbia Centre on Substance Use
FundersCanadian Institutes of Health Research
KeywordsTrazodoneAlcohol use disorderPsychiatryInsomniaAlcohol dependencePsychologyPopulationMedicineAlcoholAntidepressantAnxiety

Abstract

fetched live from OpenAlex

BACKGROUND: Insomnia is a common condition experienced by many individuals with excessive alcohol use and alcohol use disorder, and the serotonin antagonist and reuptake inhibitor trazodone has emerged as a mainstay of treatment for insomnia in this population. MAIN BODY: However, an underappreciated literature has demonstrated potential for an increase in alcohol use while persons with alcohol use disorder are taking trazodone for sleep challenges. Additionally, multiple trials have identified trazodone's metabolite meta-Chlorophenylpiperazine as a pharmaceutical inducer of increased alcohol craving and use. CONCLUSION: Increased awareness in the potential of worsening drinking behaviour with trazodone accompanied by the preferential use of safer alternative treatment strategies can likely improve outcomes for patients with heavy drinking and alcohol use disorder.

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)0.003
metaresearch head score (Gemma)0.028
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.119
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.028
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.150
GPT teacher head0.483
Teacher spread0.333 · 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