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Record W4231907003 · doi:10.5334/tohm.91

Clinical Assessment of the Effect of Tetrabenazine on Functional Scales in Huntington Disease: A Pilot Open Label Study

2012· article· en· W4231907003 on OpenAlexaboutno aff
Róbert Fekete, Anthony Davidson, Joseph Jankovic

Bibliographic record

VenueTremor and Other Hyperkinetic Movements · 2012
Typearticle
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsnot available
FundersH. Lundbeck A/S
KeywordsTetrabenazineChoreaStroop effectPsychologyPhysical medicine and rehabilitationRating scaleGaitCognitionHuntington's diseasePhysical therapyPsychiatryMedicineNeuroscienceDiseaseDevelopmental psychologyInternal medicine

Abstract

fetched live from OpenAlex

<strong>Background:</strong> Tetrabenazine is a monoamine depleter with a well-documented effect against chorea associated with Huntington disease (HD). There is a paucity of data about how reduction in chorea relates to better performance on motor, gait, cognitive, and psychiatric assessments. <strong>Methods:</strong> We designed an open label tetrabenazine withdrawal study to test performance using validated scales. The following instruments were used to assess cognitive, behavioral, and motor function in 10 patients with documented HD: The Montreal Cognitive Assessment, Beck Depression Inventory II, Dynamic Gait Index (DGI), Jebsen Hand Test, Timed 25-foot walk, Berg Balance Test (BBT), QuickDASH, and the Unified Huntington Disease Rating Scale (UHDRS) Motor, Stroop Color Word, Behavioral Assessment, Functional Checklist, and Independence Scale. <strong>Results:</strong> Subjects performed significantly better while on tetrabenazine as measured by the DGI (p=0.041), BBT (p=0.007), and the UHDRS Total Motor (p=0.009), Maximum Chorea (p=0.005), and Stroop Color-Word tests (p=0.028). <strong>Discussion:</strong> This pilot study demonstrates tetrabenazine’s potential effects beyond improvement in chorea.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.408

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.113
GPT teacher head0.392
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations7
Published2012
Admission routes1
Has abstractyes

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