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Record W1982342332 · doi:10.1358/dnp.2004.17.1.829021

Neuropathic pain: Drug targets for current and future interventions

2004· review· en· W1982342332 on OpenAlexaff
Peter A. Smith

Bibliographic record

VenueDrug News & Perspectives · 2004
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsNeuropathic painMedicineContext (archaeology)GabapentinNeuroscienceSpinal cord injuryNociceptionKetamineAnalgesicDrugNervous systemSpinal cordAnesthesiaPharmacologyReceptorPsychologyInternal medicinePathologyBiology

Abstract

fetched live from OpenAlex

Nociceptive pain alerts the body to potential or actual tissue damage. By contrast, neuropathic pain, which results from injury or damage to the nervous system, persists long after all signs of the original injury have disappeared. This type of maladaptive pain presents a significant clinical problem, as it responds poorly or unpredictably to classical analgesics. There is also no single, uniformly well-tolerated drug that is reliably helpful. Current understanding of the etiology of neuropathic pain reveals seven potential targets for therapeutic intervention. These are: 1) ectopic activity in damaged peripheral nerves; 2) increased excitability in spinal dorsal horn neurons; 3) restoration or augmentation of GABAergic inhibition in the dorsal horn; 4) supraspinal and affective mechanisms; 5) alterations in the sympathetic nervous system; 6) spinal peptidergic mechanisms; and 7) spinal excitatory amino acid receptors. Current therapeutic approaches, using drugs such as gabapentin, anticonvulsants, ketamine or methadone, and potential new approaches are discussed in the context of these seven drug targets.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.042
GPT teacher head0.366
Teacher spread0.324 · 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 designNot applicable
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

Citations23
Published2004
Admission routes1
Has abstractyes

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