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Record W2050763907 · doi:10.1016/s1754-3207(08)60014-0

Opioid analgesics in the management of neuropathic pain

2007· article· en· W2050763907 on OpenAlexaff
Dwight E. Moulin

Bibliographic record

VenueEuropean Journal of Pain Supplements · 2007
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsCancer Care OntarioWestern University
Fundersnot available
KeywordsMedicineNeuropathic painOxycodoneAnesthesiaOpioidPostherpetic neuralgiaPain ladderPopulationAnalgesicMethadoneRandomized controlled trialInternal medicine

Abstract

fetched live from OpenAlex

Neuropathic pain affects 2 to 3% of the population in developed countries and can be particularly severe and debilitating. There has been considerable controversy regarding the role of opioid analgesics in the management of this disabling condition. However, a recent systematic review of high‐quality randomized controlled trials (RCTs) utilizing opioid analgesics in the treatment of chronic neuropathic pain showed clinically significant benefit. These studies demonstrate, on average a 20 to 30% reduction in pain intensity. RCTs in patients with postherpetic neuralgia given controlled‐release oxycodone or controlled‐release morphine showed a significant reduction in pain intensity with variable improvement in sleep and disability. Trials of controlled‐release oxycodone in painful diabetic neuropathy showed more consistent improvement in pain, sleep and ability to function. Nausea and constipation are common side effects, but can usually be controlled with anti‐emetics and a bowel regimen, respectively. Psychological dependence or addiction is unusual in the absence of a history of substance abuse. Methadone may be particularly useful when conventional opioid analgesics have failed due to its N‐methyl‐D‐aspartate (NMDA) antagonist properties. When antidepressants and anticonvulsants fail to provide adequate pain control for neuropathic pain, opioid analgesics are emerging as an important treatment option ‐ in some cases, this class of drugs can make the difference between bearable and unbearable 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)0.052
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0520.000
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 head0.021
GPT teacher head0.278
Teacher spread0.258 · 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

Citations5
Published2007
Admission routes1
Has abstractyes

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