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Gabapentin: The First Preemptive Anti-Hyperalgesic for Opioid Withdrawal Hyperalgesia?

2003· article· en· W4232079824 on OpenAlexaffabout
Ian Gilron

Bibliographic record

VenueAnesthesiology · 2003
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsQueen's University
Fundersnot available
KeywordsGabapentinMedicineHyperalgesiaMorphineAnesthesiaOpioidAnalgesicNociceptionAllodyniaAnesthesiologyPharmacologyInternal medicine

Abstract

fetched live from OpenAlex

Departments of Anesthesiology and Pharmacology & Toxicology, Queen's University, Kingston, Ontario, Canada. gilroni@post.queensu.caIn Reply:—The above letter responds to the provocative question of whether gabapentin is a “broad spectrum” analgesic 1and appropriately points out that things are not quite so simple.Gustorff et al. postulate that the effects of gabapentin reported by Dirks et al. 2are not due to antinociception but, rather, to the suppression of hyperalgesia caused by withdrawal from intraoperative opioids. This is a reasonable hypothesis; however, it should be noted that Fassoulaki et al. recently observed similar reductions in pain and opioid consumption with gabapentin in patients who received no intraoperative opioids. 3Therefore, gabapentin's effects cannot be solely due to suppression of opioid withdrawal hyperalgesia.Nevertheless, this raises questions central to understanding the modulation of pain by gabapentin. While Gustorff et al. correctly indicate that postoperative pain is predominantly nociceptive, they fail to emphasize the importance of spinal sensitization, 4which contributes to hyperalgesia and allodynia and which may be suppressed by gabapentin. Indeed, although gabapentin has little antinociceptive effect in the uninjured organism, it has been shown, in the absence of opioids, to reduce pain responses after surgical tissue injury. 5The latter comments by Gustorrf et al. illustrate the complexities of interpreting gabapentin's effect when administered with opioids. Ethical conduct of most postoperative trials requires the provision of rescue analgesia, often in the form of patient-controlled analgesia with morphine, which necessitates the integration of pain measures with morphine consumption as co-relevant outcome measures. 6Although trials have been equivocal thus far, 7,8the possibility that mechanisms of opioid tolerance 9contribute to postoperative hyperalgesia and increased opioid requirements may confound results of analgesic trials. Therefore, gabapentin trials involving concomitant morphine administration must be interpreted in light of a possible interaction between these drugs. In this regard, we have observed in the rat that gabapentin prevents the development of morphine tolerance and partially reverses established tolerance indicating that such an interaction indeed exists. 10Thus, although follow-up studies will further characterize the role of gabapentin in postoperative pain, even more sophisticated strategies are needed to distinguish between its specific pharmacological effects (e.g. , analgesia, antihyperalgesia, antiallodynia and reversal of opioid tolerance).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.017
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0170.016
Insufficient payload (model declined to judge)0.0040.005

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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations2
Published2003
Admission routes2
Has abstractyes

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