Safety and Efficacy of Tetrabenazine and Use of Concomitant Medications During Long-Term, Open-Label Treatment of Chorea Associated with Huntington’s and Other Diseases
Bibliographic record
Abstract
BACKGROUND: Although tetrabenazine, a drug that depletes presynaptic dopamine by inhibiting vesicular monoamine transporter 2 (VMAT2), was approved by the U.S. Food and Drug Administration in 2008 for the treatment of chorea associated with Huntington's disease (HD), there is a paucity of data on its long-term efficacy and safety. METHODS: Approximately 2,000 patients with a variety of hyperkinetic movement disorders had been treated with open-label tetrabenazine at the Movement Disorders Clinic, Baylor College of Medicine, since 1979. Tetrabenazine was usually started at 12.5 mg/day, and the dosage was gradually increased (up to 300 mg/day). Responses were rated by the investigator 1-5, with 1 = marked chorea reduction, excellent improvement in function; 2 = moderate chorea reduction, very good improvement in function; 3 = fair chorea improvement, only mild improvement in function; 4 = poor or no response for chorea and function; and 5 = worsening chorea, some functional deterioration. Efficacy and safety were analyzed retrospectively. RESULTS: By 2004, 98 HD chorea patients had received tetrabenazine for a mean of 3.1 years (range ≤1-11.4 years). Of those with valid ratings, 75% had either marked or very good responses (rating 1 or 2) at their optimal dosages. The most common adverse events occurring in ≥5% of the patients were somnolence (39%), insomnia (33%), depression (31%), accidental injury (26%), and dysphagia (19%). Efficacy and safety were comparable to results for non-HD chorea patients. DISCUSSION: Tetrabenazine treatment was associated with long-term improvement in chorea. Adverse event rates were comparable to those reported from controlled trials.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".