Therapeutic Tolerance and Rebound Psychosis During Quetiapine Maintenance Monotherapy in Patients With Schizophrenia and Schizoaffective Disorder
Bibliographic record
Abstract
A 3-year open-label study was conducted to determine the long-term safety and efficacy of quetiapine monotherapy in schizophrenia and schizoaffective disorder.Twenty-three male outpatients previously stable but with inter-episode residual symptoms on classical antipsychotics and/or risperidone and who had complained of side effects were selected. To initiate quetiapine, patients were hospitalized for 13 days and then treated as outpatients. Quetiapine dosage was adjusted according to therapeutic effects. Only five patients (21.7%) completed 77 to 96 weeks of the study. Initial dose was 261 +/- 65.6 mg/day (mean +/- S.D.) administered in divided doses, with an ending dose of 487 +/- 209.6 mg/day, corresponding with an 86.6% dose increase over the course of the study. For those completing 12 weeks or less (n = 11), mean ending dose was 362 +/- 184.8 mg/day a 38.7% dose increase over baseline. For those completing 25 weeks or more (n = 12), mean ending dose was 592 +/- 178.2 mg/day, a 126.8% dose increase over baseline. Six of the seven patients who relapsed after being stabilized on quetiapine for at least three months met criteria for supersensitivity psychosis (SSP).Therapeutic tolerance and rebound psychosis were found to develop with quetiapine in male patients with a history of chronic treatment with classical antipsychotics. Seeman and Tallerico3 have proposed pharmacologic explanations for quetiapine and clozapine drug-induced rebound phenomena.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".