Clozapine in Parkinsonian Rest Tremor: A Review of Outcomes, Adverse Reactions, and Possible Mechanisms of Action
Bibliographic record
Abstract
BACKGROUND: The pathogenesis of rest tremor in Parkinson's disease (PD) is incompletely understood. This symptom can be resistant to typical anti-PD medications. Therefore, new treatments are needed given the concern that this symptom causes to patients and family. Limited experience suggests that clozapine can have an important antitremor effect in PD. The mechanism(s) underlying this effect is not well understood, but could provide insight and impetus to the development of more-effective and safer antitremor therapies. METHODS AND RESULTS: Exemplifying the antitremor effects of clozapine, we describe a patient with tremor-predominant PD who obtained prominent reduction of rest tremor with clozapine treatment. We review the responses to this treatment in another 7 of our PD patients with treatment-resistant rest tremor. We also review the published literature on clozapine for tremor in PD and discuss its potential mechanisms of action and possible adverse effects. In our case series, there was a 64% reduction of tremor score after clozapine was initiated. The mechanism of tremor reduction remains unclear with possible involvement of anticholinergic, serotonergic, antihistaminergic, antiadrenergic, and antidopaminergic effects. Clozapine does have potential serious adverse effects. CONCLUSIONS: Clozapine may be effective in controlling rest tremor in PD. Given the potential fatal side effects, if clozapine is to be initiated in PD patients, it has to be used cautiously with proper monitoring, preferably in specialized centers. We acknowledge that the number of patients in this case series is small. Further studies are needed to understand clozapine's mechanism of action in reducing tremor.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".