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Record W1999922206 · doi:10.1097/aco.0b013e3282efd175

Reassessment of the role of cannabinoids in the management of pain

2007· review· en· W1999922206 on OpenAlexaff
Pierre Beaulieu, Mark A. Ware

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2007
Typereview
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsMcGill University Health CentreUniversité de MontréalHôtel-Dieu de Montréal
Fundersnot available
KeywordsMedicinePain managementIntensive care medicineMEDLINEAnesthesia

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: The aim of this article is to assess the role of cannabinoids in the treatment of acute and chronic pain in humans. RECENT FINDINGS: Very few clinical trials looking at the analgesic effects of cannabinoids in the acute pain settings have been performed. Three recent studies have evaluated the oral administration of synthetic cannabinoids in postoperative pain. At low doses cannabinoids are not different from placebo, whereas at high doses they may be associated with adverse effects or even worsening of pain intensity. In chronic pain patients, the safety and analgesic efficacy of a number of cannabinoid compounds have recently been evaluated in several clinical trials in several chronic pain conditions. While the small size of the trials and the relatively short duration of follow-up limits broad generalization, to date there is increasing evidence that cannabinoids are safe and effective for refractory chronic pain conditions including neuropathic pain associated with multiple sclerosis, rheumatoid arthritis, and peripheral neuropathy associated with HIV/AIDS. SUMMARY: The precise role of cannabinoids in pain treatment still needs further evaluation. Cannabinoid compounds may be more effective in the context of chronic neuropathic pain than for the management of acute pain.

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)0.003
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.957
Threshold uncertainty score0.594

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.087
GPT teacher head0.429
Teacher spread0.341 · 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 designOther design
Domainnot available
GenreReview

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

Citations34
Published2007
Admission routes1
Has abstractyes

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