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Record W2266600836 · doi:10.1517/14656566.2016.1146691

Topical amitriptyline and ketamine for post-herpetic neuralgia and other forms of neuropathic pain

2016· article· en· W2266600836 on OpenAlexaff
Jana Sawynok, Celia Zinger

Bibliographic record

VenueExpert Opinion on Pharmacotherapy · 2016
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineNeuropathic painGabapentinAmitriptylineKetamineNeuralgiaPostherpetic neuralgiaAdverse effectAnesthesiaPeripheral neuropathyClinical trialPregabalinOnset of actionDosingPharmacologyInternal medicineDiabetes mellitus

Abstract

fetched live from OpenAlex

INTRODUCTION: Neuropathic pain (NP) has several therapeutic options but efficacy is limited and adverse effects occur, such that additional treatment options are needed. A topical formulation containing amitriptyline 4% and ketamine 2% (AmiKet) may provide such an option. AREAS COVERED: This report summarizes both published and unpublished results of clinical trials with AmiKet. In post-herpetic neuralgia (PHN), AmiKet produces a significant analgesia which is comparable to that produced by oral gabapentin. In diabetic painful neuropathy, AmiKet showed a strong trend towards pain reduction. In mixed neuropathic pain, case series reports suggest a favourable response rate, but are limited by trial characteristics. AmiKet is absorbed minimally following topical administration. Over 700 patients have now received topical AmiKet in clinical regimens, and it is well-tolerated with the adverse effects mainly being application site reactions. Both agents are polymodal, and several mechanisms may contribute to the peripheral efficacy of AmiKet. EXPERT OPINION: Topical AmiKet has the potential to be a first-line treatment option for PHN, and to be useful in other NP conditions. Furthermore, AmiKet has the potential to be an adjunct to systemic therapies, with the targeting of a peripheral compartment in addition to central sites of action representing a rational drug combination.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.033
GPT teacher head0.347
Teacher spread0.315 · 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 designBench or experimental
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

Citations35
Published2016
Admission routes1
Has abstractyes

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