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Record W2169514606 · doi:10.1002/mds.24949

Epidural premotor cortical stimulation in primary focal dystonia: Clinical and <sup>18</sup> F‐fluoro deoxyglucose positron emission tomography open study

2012· article· en· W2169514606 on OpenAlexaboutno aff
Stefania Lalli, Sylvie Piacentini, Angelo Franzini, A. Panzacchi, Chiara Cerami, Giuseppe Messina, F. Ferrè, Daniela Perani, Alberto Albanese

Bibliographic record

VenueMovement Disorders · 2012
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCervical dystoniaDystoniaSpasmodic TorticollisDeep brain stimulationPositron emission tomographyMedicinePsychologySurgeryNuclear medicineAnesthesiaParkinson's diseaseInternal medicineNeuroscience

Abstract

fetched live from OpenAlex

The aim of this study was to evaluate the efficacy and safety of epidural premotor stimulation in patients with primary focal dystonia. Seven patients were selected: 6 had cervical dystonia and 1 had right upper limb dystonia. In 2 patients, sustained muscle contractions led to a prevalently fixed head posture. Patients with cervical dystonia received a bilateral implant, whereas the patient with hand dystonia received a unilateral implant. Neurological and neuropsychological evaluations were performed before surgery (baseline), and 1, 3, 6, and 12 months afterward. The Burke-Fahn-Marsden scale (BFMS) and the Toronto Western spasmodic torticollis rating scale (TWSTRS) were administered at the same time points. Patients underwent resting (18)F-fluorodeoxyglucose (FDG) positron emission tomography (PET) scans, before and 12 months after surgery. No adverse events occurred. An overall improvement was observed on the BFMS and TWSTRS after surgery. Patients with prevalently fixed cervical dystonia had a reduced benefit. Presurgical neuroimaging revealed a significant bilateral metabolic increase in the sensorimotor areas, which was reduced after surgery.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.031
GPT teacher head0.332
Teacher spread0.301 · 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

Citations26
Published2012
Admission routes1
Has abstractyes

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