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Record W2185535953 · doi:10.2147/jpr.s88900

Approach to the pharmacological management of chronic pain in patients with an alcohol use disorder

2015· article· en· W2185535953 on OpenAlexaff
Andrea D Furlan, Laura Murphy, Karen Ng, Victoria Su, Sarah Woodworth-Giroux, Todd Levy, Beth Sproule

Bibliographic record

VenueJournal of Pain Research · 2015
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsCentre for Addiction and Mental HealthSt. Paul's HospitalUniversity Health NetworkUniversity of TorontoWindsor Regional HospitalInstitute for Work & Health
Fundersnot available
KeywordsMedicineChronic painAlcohol use disorderPsychiatryPregabalinAlcohol dependenceAnxietyAbstinenceAlcohol

Abstract

fetched live from OpenAlex

This paper provides an overview of research, guidelines, and clinical considerations for the use of medications for chronic pain in the management of patients with an alcohol use disorder. A review of the literature identified randomized controlled trials, epidemiological cohort studies, consensus guidelines, and one systematic review and meta-analysis. Where gaps in the literature existed, clinical experience of the authors is included. Use of nonopioid medications should be given priority and may offer a more favorable risk profile as well as benefits beyond pain management, such as improvement in anxiety, depression, or insomnia. Pregabalin and gabapentin have additional benefits to decrease alcohol cravings or time to relapse after a period of abstinence from alcohol. Drug interactions between selected analgesics and alcohol, disulfiram, or naltrexone require careful consideration.

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)0.013
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.000
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)0.0000.000

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 head0.160
GPT teacher head0.418
Teacher spread0.257 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2015
Admission routes1
Has abstractyes

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