Efficacy and safety of valbenazine in the treatment of cervical dystonia: a pilot study
Bibliographic record
Abstract
Background Vesicular monoamine transporter-2 inhibitors have provided on-label success in the treatment of tardive dyskinesia (TD) and Huntington’s disease chorea (HDC). A similar pathophysiological pathway for cervical dystonia suggests valbenazine (VBZ) could be beneficial in this condition. Objective To determine the efficacy of VBZ in reducing symptoms of pain and posturing and improving quality of life in subjects with cervical dystonia. Methods This was an open-label, prospective study of subjects with a clinical diagnosis of cervical dystonia currently being treated with botulinum neurotoxin (BoNT) for >6 months. Valbenazine was titrated to 80 mg per day with no change in BoNT dosage or muscle location. Evaluations were performed 4 weeks prior to the subject’s scheduled BoNT treatment date BoNTmax/-VBZ (time 1) compared to 4 weeks prior to the subject’s next BoNT treatment date BoNTmax/+VBZ (time 4). TheBoNT injection treatment date BoNTmin/VBZ dispensing (time 2) and the next BoNT injection treatment date BoNTmin/+VBZ (time 5) were compared. Efficacy was assessed using the Toronto Western Spasmodic Torticollis Rating Scale (TWSTR), Neck Pain Disability Index (NPDI). Visual analog scale (VAS, 0–10) for pain/pulling/jerking, Pittsburgh Sleep Quality Index (PSQI), Clinical Global Impression of Change (CGIC) and Patient Global Impression of Change (PGIC) Scales. Results Fourteen subjects were enrolled and followed for a total of 16 weeks. TWSTRS Total Score was significantly improved at time 4 compared to time 1 (p = 0.02), as well as VAS 0–10 scores for 24 Hour (p = 0.001), Past Week Pull (p = 0.0001), and Past Week Jerk (p = 0.04). TWSTRS Total Score was significantly improved at time 5 compared to time 2 (p = 0.02) as well as 24 Hour Pull (p = 0.01), 24 Hour Jerk (p = 0.04), Past Week Pull (p = 0.002), and Past Week Jerk (p = 0.02). Subjective improvement was reported at times 3, 4 and 5 on CGIC and PGIC Scales. No significant improvements were seen in the PSQI and NPDI. The medication was tolerated well with fatigue as the most common adverse effect. Conclusion This exploratory study demonstrates a potential benefit in the addition of VBZ for the treatment of cervical dystonia associated with severe pain and posturing.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
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".