New Insights in the Pharmacotherapy of Psychosis: The Example of Parkinson's Disease Psychosis
Bibliographic record
Abstract
Introduction With 10 million of patients across the world, Parkinson's disease is the second most common form of neurodegeneration, after Alzheimer's. Among half of patients develop psychotic symptoms, such as visual hallucinations and delusions, which are correlated with higher rate of placement in nursing home, are difficult to treat and severely affect quality of life, making Parkinson's disease psychosis (PDP) a major public health issue. Objectives The aim of this study is to identify treatment options that could be used to treat PDP and clarify underlying pathophysiology. Method We conducted a literature review on Pubmed, Goggle scholar and Cochrane library, using a combination of the following: “Parkinson's disease Psychosis” “visual hallucinations” “Pimavanserin” “Clozapine” “atypical anti-psychotics” 120 articles were screened. Results Considering that hallucinations arise from overactivation of dopaminergic receptors, treatment options include reducing the dopaminergic drugs used to control motor symptoms; using atypical anti-psychotics such as Risperidone, Olanzapine, Quetiapine, which often results in the worsening of extra-pyramidal symptoms. Another option is the use of low doses of Clozapine, which has been proven efficient with no worsening of non-motor symptoms, suggesting the implication of other pathways, such as serotonin. Finally, Pimavanserin, a 5-HT2A receptor inverse agonist, without any dopaminergic activity, has been demonstrated to be effective in the treatment of PDP, well tolerated and easy to use. Conclusion Serotonin inverse agonists represent a major breakthrough in the pharmacotherapy of PDP, and may lead the way to changes in the treatment of schizophrenia and other psychotic disorders. Disclosure of interest The authors have not supplied their declaration of competing interest.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".