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Record W2605838753 · doi:10.5812/aapm.44732

The Efficacy of Systemic Lidocaine in the Management of Chronic Pain: A Literature Review

2017· review· en· W2605838753 on OpenAlexafffund
Fardin Yousefshahi, Oana Predescu, Juan Francisco Asenjo

Bibliographic record

VenueAnesthesiology and Pain Medicine · 2017
Typereview
Languageen
FieldMedicine
TopicPain Management and Treatment
Canadian institutionsMcGill University Health Centre
FundersMcGill University
KeywordsMedicineLidocaineChronic painNeuropathic painNeuralgiaNarrative reviewAnesthesiaTransdermal patchIntensive care medicineTransdermalPhysical therapyPharmacology

Abstract

fetched live from OpenAlex

CONTEXT: Despite recent advances in the understanding of the chronic pain concept, its diagnosis and management remains a daily challenge for clinicians and patients. Based on the published literature, this review discusses and tries to organize the current knowledge and the up-to-date clinical experience about the efficacy and safety of the use of intravenous lidocaine in treatment and prevention of chronic pain. EVIDENCE ACQUISITION: To prepare this narrative review, we performed an in depth literature review using the PubMed searching engine. We extracted all relevant articles published in English, up to April 2016. RESULTS: Lidocaine, administered as transdermal patch or intravenous lidocaine, is a safe and effective modality in the treatment of post-herpetic neuralgia (PHN), complex regional pain syndrome, as well and for prevention of chronic pain. It may be effective in the management of neuropathic pain syndromes, chronic pain, post-operative pain, and refractory cancer pain. CONCLUSIONS: Intravenous lidocaine and lidocaine patch are effective and safe for the treatment of several chronic or neuropathic pain syndromes. The use of lidocaine during surgery could prevent the development of some chronic post-surgical pain syndromes.

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)0.015
metaresearch head score (Gemma)0.001
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 score0.764
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.046
GPT teacher head0.354
Teacher spread0.308 · 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

Citations35
Published2017
Admission routes2
Has abstractyes

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