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Record W2001851098 · doi:10.1097/ajp.0b013e318285be25

Percutaneous Trigeminal Rhizotomy for Facial Pain Secondary to Head and Neck Malignancy

2013· article· en· W2001851098 on OpenAlexaff
Daniel Mendelsohn, Manish Ranjan, Pippa Hawley, Christopher R. Honey

Bibliographic record

VenueClinical Journal of Pain · 2013
Typearticle
Languageen
FieldMedicine
TopicTrigeminal Neuralgia and Treatments
Canadian institutionsBC Cancer AgencyUniversity of British Columbia
Fundersnot available
KeywordsMedicineRhizotomyPercutaneousSurgeryTrigeminal nerveTrigeminal neuralgiaForamen ovale (heart)AnesthesiaSpinal cord

Abstract

fetched live from OpenAlex

BACKGROUND: Nearly 80% of patients with head and neck cancers experience facial pain related to their tumor or treatment. The majority obtain pain relief with appropriate medical treatment. Occasionally some remain refractory to all analgesics or cannot tolerate the accompanying side effects. They may benefit from surgical intervention. OBJECTIVES: We report a case of medically intractable facial pain secondary to squamous cell carcinoma of the tongue that was successfully treated with percutaneous trigeminal rhizotomy. METHODS: Percutaneous trigeminal radiofrequency rhizotomy involves thermoablation of the trigeminal nerve within Meckel's cave by an electrode inserted through the cheek and foramen ovale. RESULTS: Facial pain was successfully controlled postoperatively. DISCUSSION: Percutaneous trigeminal rhizotomy is a surgical option for managing nociceptive pain secondary to a head and neck malignancy. This technique, last reported in the literature almost 30 years ago, must not be forgotten by the next generation of oncologists, pain specialists, and neurosurgeons.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.732
Threshold uncertainty score0.547

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.040
GPT teacher head0.364
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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations5
Published2013
Admission routes1
Has abstractyes

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