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Record W4225005357 · doi:10.1136/jnnp-2021-327524

Functional tremor developing after successful MRI-guided focused ultrasound thalamotomy for essential tremor

2022· article· en· W4225005357 on OpenAlexaff
Sohaila Alshimemeri, Daniel Vargas-Méndez, Robert Chen, Nir Lipsman, Michael L. Schwartz, Andrés M. Lozano, Alfonso Fasano

Bibliographic record

VenueJournal of Neurology Neurosurgery & Psychiatry · 2022
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsHealth Sciences CentreUniversity of TorontoOntario Brain InstituteSunnybrook Health Science CentreToronto Western Hospital
Fundersnot available
KeywordsEssential tremorThalamotomyMedicineMovement disordersPhysical medicine and rehabilitationDeep brain stimulationThalamic stimulatorNeurosciencePsychologyParkinson's diseaseDiseasePathology

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe a case of functional tremor occurring after a successful MR-guided focused ultrasound thalamotomy (MRgFUS) for essential tremor. METHODS: A 71-year-old right-handed man with essential tremor was referred to us for consideration of deep brain stimulation surgery for worsening bilateral upper limb tremor after a successful left MRgFUS for essential tremor. RESULTS: On clinical exam, signs compatible with a functional tremor were noted, including entertainability and suppressibility. Electrophysiological studies were consistent with essential tremor and superimposed tremor fulfilling the laboratory-supported criteria for functional tremor. DISCUSSION: We describe the first reported case of a functional movement disorder occurring after successful MRgFUS procedure for essential tremor. Recognising this entity and its development after such therapeutic interventions is essential to avoid further unnecessary invasive therapies.

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)0.005
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
Metaresearch0.0000.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.271
Teacher spread0.248 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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