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Record W3196454992 · doi:10.1111/ncn3.12545

Magnetic resonance imaging–guided focused ultrasound thalamotomy for an essential tremor patient with a subcutaneous implantable cardioverter defibrillator: A case report

2021· article· en· W3196454992 on OpenAlexaff
Hisashi Ito, Sho Aoki, Takashi Odo, Shigeru Fukutake, Jun Kishihara, Kazuaki Yamamoto, Takaomi Taira, Toshio Yamaguchi

Bibliographic record

VenueNeurology and Clinical Neuroscience · 2021
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineImplantable cardioverter-defibrillatorAmiodaroneThalamotomyEssential tremorCardioversionVentricular fibrillationAnesthesiaMagnetic resonance imagingCardiologyAtrial fibrillationInternal medicineRadiologyDeep brain stimulationPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

Abstract We report a 52 years‐old, right‐handed man with medication‐refractory essential tremor (ET). Because of ventricular fibrillation (Vf) due to coronary spasm, he had been treated with an MR‐conditional subcutaneous implantable cardioverter defibrillator (S‐ICD) and medications including amiodarone, nifedipine, and isosorbide nitrate. Amiodarone was discontinued as Vf was not observed for more than 2 years, and it induced thyrotoxicosis. Vf did not occur after the cessation of amiodarone. Moreover, he did not suffer from an angina attack after the administration of vasodilators. After receiving informed consent to stop S‐ICD during the procedure, we performed MRI‐guided focused ultrasound (MRgFUS) left ventral intermediate nucleus thalamotomy. The right‐hand tremor disappeared immediately, and we observed neither Vf nor S‐ICD‐related complications during the procedure. MRgFUS thalamotomy may be feasible as one of the therapeutic options for ET patients even with S‐ICD.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.316
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), 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

Citations2
Published2021
Admission routes1
Has abstractyes

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