Tetrabenazine Augmentation in Treatment-Resistant Schizophrenia
Bibliographic record
Abstract
Evidence linking schizophrenia to alterations in presynaptic dopamine (DA) grows, although treatments to date have largely focused on postsynaptic D2 receptor blockade. This study examined augmenting response in treatment-resistant schizophrenia through the addition of tetrabenazine (TBZ), a presynaptic vesicular monoamine transporter (VMAT2) inhibitor. Participants included 41 outpatients (mean age, 43.5 years) with treatment-refractory schizophrenia, stabilized on their present antipsychotic treatment (clozapine, 73%) for more than 3 months. Individuals were randomly assigned to TBZ augmentation (12.5-75 mg/d), titrated according to a fixed, flexible schedule, or placebo over 12 weeks. Twenty subjects received TBZ, and 21 received placebo; doses of 18 of the 20 TBZ-treated individuals were titrated up to the maximum of 75 mg/d, and 16 (80%) of them completed the trial. Tetrabenazine was well tolerated and not linked to increased adverse effects, including those that have been reported more frequently (eg, parkinsonism, depression, and sedation) with higher doses (>100 mg/d) used in the treatment of hyperkinetic movement disorders. However, there was no indication of clinical improvement as measured using the Brief Psychiatric Rating Scale, the Clinical Global Impression scale, and the Global Assessment of Functioning scale. In examining those receiving TBZ-clozapine specifically, there was no indication of drug-drug interactions or difference in response compared to the overall sample. Tetrabenazine was not effective, as used here, in augmenting clinical response in treatment-resistant schizophrenia. It may be premature, however, to discount the potential benefits of VMAT2 inhibitors in treating psychosis in light of what is presently understood regarding presynaptic DA's role and evidence that "endogenous sensitization" may occur over the course of the illness.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.002 | 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 teacher head, 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".