Risk of VMAT2 inhibitors on suicidality and parkinsonism: report utilizing the United States Food and Drug Administration adverse event reporting system
Bibliographic record
Abstract
Prescription of vesicular monoamine transporter 2 (VMAT2) inhibitors, valbenazine, deutetrabenazine, and tetrabenazine, is becoming increasingly common in persons treated with antipsychotics. Reported suicidality and parkinsonism are safety concerns with VMAT2 inhibitors. Herein, we aim to evaluate the aforementioned safety outcomes using the FDA Adverse Event Reporting System. Reporting odds ratios (RORs) and lower limits of 95% confidence intervals of information components (IC 025 ) were calculated to quantify VMAT2 inhibitor-associated adverse events. Acetaminophen was the reference agent. Suicidal ideation was significantly associated with VMAT2 inhibitors, with RORs ranging from 2.38 to 10.67 and IC 025 ranging from 0.73 to 2.39. Increased odds of suicidal behavior was observed with tetrabenazine (ROR 3.011, IC 025 0.0087), but not deutetrabenazine or valbenazine. Decreased odds of suicide attempts and completed suicide were observed with VMAT2 inhibitors, with RORs ranging from 0.011 to 0.10 (all IC 025 < 0). Increased odds of parkinsonism were reported for all VMAT2 inhibitors, with RORs and IC 025 ranging from 19.49 to 25.37 and 1.66 to 2.93, respectively. The mixed results with VMAT2 inhibitor-associated suicidality and parkinsonism do not establish causal relationships. The parameters of suicidality may be explained by underlying psychiatric disorders.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".