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Record W2416678670 · doi:10.1590/0004-282x20150109

OnabotulinumtoxinA for trigeminal neuralgia: a review of the available data

2015· review· en· W2416678670 on OpenAlexaff
Pedro André Kowacs, Marco Antônio Takashi Utiumi, Fábio A. Nascimento, Élcio Juliato Piovesan, Hélio Afonso Ghizoni Teive

Bibliographic record

VenueArquivos de Neuro-Psiquiatria · 2015
Typereview
Languageen
FieldMedicine
TopicTrigeminal Neuralgia and Treatments
Canadian institutionsToronto Western Hospital
FundersAllergan
KeywordsMedicineTolerabilityTrigeminal neuralgiaHeadachesRandomized controlled trialAnesthesiaNarrative reviewAnalgesicIntensive care medicineSurgeryAdverse effectInternal medicine

Abstract

fetched live from OpenAlex

Trigeminal neuralgia (TN) patients may develop side effects from centrally acting drugs, have contraindications for neurosurgical procedures, or experience relapse during conventional therapies. OnabotulinumtoxinA (BoNT/A) has been reported to be effective for TN, although this finding has been challenged. An overview of the available evidence based on a narrative/qualitative analysis of the literature is presented. About 90% of patients who receive BoNT/A show an improvement, a higher figure than that reported for the placebo effect of BoNT/A for other headaches. Tolerability of BoNT/A is good, and its few side-effects are transient. The articles reviewed were mainly case reports, case series and open-label trials; however, randomized controlled trials have endorsed the efficacy of BoNT/A for TN. This evidence, together with a better understanding of the analgesic mechanisms of BoNT/A and its proven efficacy in treating other pain syndromes, supports the use of this toxin as a therapeutic option for TN.

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)0.003
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
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 head0.244
GPT teacher head0.436
Teacher spread0.193 · 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

Citations22
Published2015
Admission routes1
Has abstractyes

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