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Record W2041462105 · doi:10.1017/s0317167100003401

Pallidal Deep Brain Stimulation in Cervical Dystonia: Clinical Outcome in Four Cases

2004· article· en· W2041462105 on OpenAlexaffvenueabout
Hazem Eltahawy, Jean A. Saint‐Cyr, Yu‐Yan Poon, Elena Moro, Anthony E. Lang, Andrés M. Lozano

Bibliographic record

VenueCanadian Journal of Neurological Sciences / Journal Canadien des Sciences Neurologiques · 2004
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsDeep brain stimulationSpasmodic TorticollisCervical dystoniaDystoniaMedicineBotulinum toxinTorticollisStimulationAnesthesiaSurgeryGlobus pallidusParkinson's diseaseInternal medicineBasal gangliaDiseaseCentral nervous system

Abstract

fetched live from OpenAlex

OBJECTIVE: Report on the clinical results following bilateral globus pallidus interna deep brain stimulation in four patients (one female and three males) with severe cervical dystonia, mean age 48 years (range 37-67). METHODS: All four patients had failed extensive medical and botulinum toxin treatment. The mean duration of the disease was nine years (range 4-15 years). Patients were assessed pre and postoperatively using the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS). Pre-operatively, the mean TWSTRS total score was 43.2 (range 28-60.5). Posteroventral pallidal deep brain stimulators were inserted using MRI and microelectrode recording guidance. Last follow-up was 15 months for the four patients. RESULTS: Mean reduction in the TWSTRS total scores at last follow- up was 73% (range 61- 85%). Improvement in pain occurred soon after deep brain stimulation surgery. Motor improvement was delayed and prolonged over several months. Frequent adjustment in the stimulation parameters was necessary in the first three months. CONCLUSION: Bilateral pallidal stimulation is effective in management of selected cases of intractable 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)0.004
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.002
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 head0.091
GPT teacher head0.357
Teacher spread0.266 · 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 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

Citations73
Published2004
Admission routes3
Has abstractyes

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