Quetiapine in patients with comorbid schizophrenia-spectrum and substance use disorders: an open-label trial
Bibliographic record
Abstract
BACKGROUND: Preliminary evidence suggests that clozapine relieves the craving for psychoactive substances in schizophrenia patients. Quetiapine shares crucial pharmacological properties with clozapine. Promising results have been described with quetiapine therapy in patients with psychosis and substance use disorder. METHODS: Based on Diagnostic and Statistical Manual of Mental Disorders - fourth edition (DSM-IV) criteria, patients were diagnosed with comorbid schizophrenia-spectrum and substance use disorders. Patients were switched to quetiapine for a 12-week open-label trial. Craving, quantities used, days of consumption, and severity of substance abuse were assessed every 3 weeks. Alcohol and Drug Use Scales were administered on baseline and end-point. Psychiatric symptoms, depressive symptoms, extrapyramidal symptoms, and cognition were also assessed at baseline, week 6 and week 12. RESULTS: Twenty-four schizophrenia-spectrum patients were included in the last observation carried forward (LOCF) analyses, responding to one or more of the following substance use disorders: cannabis (15 patients), alcohol (10 patients), and other psychoactive substances (nine patients). Overall, severity of substance abuse improved during the study. Less weekly days were spent on drugs of abuse. A decrease in the weekly Canadian dollars spent on psychoactive substances was also observed. Cognition, psychiatric, depressive, and extrapyramidal symptoms also significantly improved (p < 0.05). CONCLUSIONS: In this open-label, uncontrolled trial, significant improvements were noted in substance abuse, psychiatric symptoms, extrapyramidal symptoms, and cognition during quetiapine therapy. The study suffered from three main limitations: (1) the open-label design of the study; (2) the patients' poor compliance; and (3) the small sample size involved. Controlled studies on the use of quetiapine in dual diagnosis schizophrenia are warranted to confirm that the effects are drug-related.
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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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".