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Record W2914139567 · doi:10.1111/scd.12365

Greater palatine block for V2 trigeminal neuralgia: Case report

2019· article· en· W2914139567 on OpenAlexafffund
Mervyn Gornitsky, Sherif M. Elsaraj, Olivia Canie, Shrisha Mohit, Ana Míriam Velly, Hyman M. Schipper

Bibliographic record

VenueSpecial Care in Dentistry · 2019
Typearticle
Languageen
FieldMedicine
TopicTrigeminal Neuralgia and Treatments
Canadian institutionsMcGill UniversityJewish General Hospital
FundersJewish General Hospital
KeywordsMedicineTrigeminal neuralgiaDiscontinuationAnesthesiaRefractory (planetary science)Trigeminal nerveAnalgesicReduction (mathematics)Adverse effectSurgeryMandibular nerveNerve blockNeuralgiaDentistryNeuropathic painInternal medicine

Abstract

fetched live from OpenAlex

AIMS: This study describes a novel nerve block directed at the maxillary (V2) division of the fifth cranial nerve as treatment for medication-refractory trigeminal neuralgia (TN). METHODS AND RESULTS: The authors present three cases of TN treated with V2 nerve block using commonly available local anesthetics injected through the greater palatine foramen. Patients' medications were noted before and after the procedure. Following the injection, patients were followed over time and outcome was assessed. Patients experienced rapid and long-lasting pain relief allowing for significant reduction in antineuralgia medications. This was done with the objective of breaking the pain cycle with subsequent discontinuation or reduction of analgesic medications. CONCLUSION: This technique may be an effective treatment for medication-refractory V2 TN. By interrupting the pain cycle, this renders the condition amenable to long-term control using diminished doses of standard antineuralgia pharmaceuticals. The practical implications of the described procedure are that it is simple, safe, and well-tolerated with few or no adverse effects. This novel technique is a diagnostic feature for the dentist to differentiate between sources of facial pain.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.803

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)0.0010.000

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 head0.018
GPT teacher head0.309
Teacher spread0.291 · 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 designCase report
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

Citations13
Published2019
Admission routes2
Has abstractyes

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