Antipsychotic-Induced Dopamine Supersensitivity Psychosis: Pharmacology, Criteria, and Therapy
Bibliographic record
Abstract
The first-line treatment for psychotic disorders remains antipsychotic drugs with receptor antagonist properties at D2-like dopamine receptors. However, long-term administration of antipsychotics can upregulate D2 receptors and produce receptor supersensitivity manifested by behavioral supersensitivity to dopamine stimulation in animals, and movement disorders and supersensitivity psychosis (SP) in patients. Antipsychotic-induced SP was first described as the emergence of psychotic symptoms with tardive dyskinesia (TD) and a fall in prolactin levels following drug discontinuation. In the era of first-generation antipsychotics, 4 clinical features characterized drug-induced SP: rapid relapse after drug discontinuation/dose reduction/switch of antipsychotics, tolerance to previously observed therapeutic effects, co-occurring TD, and psychotic exacerbation by life stressors. We review 3 recent studies on the prevalence rates of SP, and the link to treatment resistance and psychotic relapse in the era of second-generation antipsychotics (risperidone, paliperidone, perospirone, and long-acting injectable risperidone, olanzapine, quetiapine, and aripiprazole). These studies show that the prevalence rates of SP remain high in schizophrenia (30%) and higher (70%) in treatment-resistant schizophrenia. We then present neurobehavioral findings on antipsychotic-induced supersensitivity to dopamine from animal studies. Next, we propose criteria for SP, which describe psychotic symptoms and co-occurring movement disorders more precisely. Detection of mild/borderline drug-induced movement disorders permits early recognition of overblockade of D2 receptors, responsible for SP and TD. Finally, we describe 3 antipsychotic withdrawal syndromes, similar to those seen with other CNS drugs, and we propose approaches to treat, potentially prevent, or temporarily manage SP.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".