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Record W4362730348 · doi:10.2176/jns-nmc.2022-0392

Myotomy and Selective Peripheral Denervation Based on <sup>18</sup>F-FDG PET/CT in Intractable Cervical Dystonia: A Case Report

2023· article· en· W4362730348 on OpenAlexaboutno aff
Isamu Miura, Shiro Horisawa, Takakazu Kawamata, Takaomi Taira

Bibliographic record

VenueNMC Case Report Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCervical dystoniaSpasmodic TorticollisMyotomyDystoniaDenervationPositron emission tomographyTorticollisBotulinum toxinNuclear medicineRadiologySurgeryAnatomyEsophagus

Abstract

fetched live from OpenAlex

Cervical dystonia, characterized by the involuntary contraction of cervical muscles, is the most common form of adult dystonia. In a patient with intractable cervical dystonia, we carried out a myotomy of the left obliquus capitis inferior and selective peripheral denervation (SPD) of the posterior branches of the C3-C6 spinal nerves based on preoperative 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT). The patient was a 65-year-old, right-handed man with an unremarkable medical history. His head rotated involuntarily to the left. Medication and botulinum toxin injections were ineffective, and surgical treatment was considered. 18F-FDG PET/CT imaging revealed FDG uptake in the left obliquus capitis inferior, right sternocleidomastoideus, and left splenius capitis. Myotomy of the left obliquus capitis inferior and SPD of the posterior branches of the C3-C6 spinal nerves was performed under general anesthesia. During the 6-month follow-up, the patient's Toronto Western Spasmodic Torticollis Rating Scale score improved from 35 to 9. This case shows that preoperative 18F-FDG PET/CT is effective in identifying dystonic muscles and determining the surgical strategy for cervical dystonia.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.023
GPT teacher head0.290
Teacher spread0.267 · 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 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

Citations2
Published2023
Admission routes1
Has abstractyes

Explore more

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