The Effect of Quetiapine on Cannabis Use in 8 Psychosis Patients with Drug Dependency
Bibliographic record
Abstract
Dear Editor: Approximately one-half of all patients with schizophrenia abuse or depend on psychoactive substances at some point during their lives (1), but few studies to date have proposed an integrated pharmacologie treatment for this schizophrenia-addiction comorbidity. Because of their strong dopamine D^sub 2^ receptor antagonism, conventional antipsychotics such as haloperidol should in theory be the treatment of choice for comorbid schizophrenia and substance abuse. In practice, however, such treatment has not been demonstrated to be consistently effective and has only controlled drug abuse in special cases (2). A few pilot studies suggest that, among the conventional antipsychotics, flupenthixol may reduce cravings in schizophrenia patients with cocaine addiction (3). To date, the most promising results have been obtained with clozapine, a prototype of the atypical antipsychotics (4). Sharing certain key properties with clozapine (for example, 5-HT^sub 2^- D^sub 2^ ratio) (5), quetiapine may also reduce drug cravings in psychosis patients with addictions. A pilot study of 12 patients suffering from bipolar disorder (BD) and cocaine addiction appears to support this hypothesis (6). To expand on this promising result, we report case histories for 8 psychosis patients whose cannabis use habits significantly improved after treatment with quetiapine. Case Report The group of patients (5 men and 3 women) included 4 patients with schizophrenia and 4 with affective BD. All patients had cannabis dependency, and 2 also had a cocaine use disorder, according to DSM-IV criteria. Their mean age was 38.5 years (range 25 to 46 years). Before quetiapine was initiated, they received antipsychotics (5 patients), anti-depressants (2 patients), lithium (2 patients), clonazepam (2 patients), and procyclidine (1 patient). All 8 patients were given quetiapine for an average of 5.8 months, at dosages ranging between 100 and 1200mg daily. Concomitantly, 4 patients received antidepressants, 2 received gabapentin, and 1 was on methadone maintenance treatment. Overall, an average 97.3% reduction in their weekly cannabis use was observed with an average quetiapine dosage of 388 mg daily. When interviewed, patients reported consuming an average of 35.6 g weekly of cannabis (range 18 to 56 g) before quetiapine introduction. After quetiapine treatment, patients reported an average cannabis consumption of 1.1 g weekly. Like clozapine, quetiapine has proven benefits when compared with conventional antipsychotics (7,8). First, clozapine and quetiapine have a beneficial effect on mood. Showing mesolimbic selectivity, these agents do not appear to cause extrapyramidal symptoms. Further, these medications produce little or no neuroleptic-induced dysphoria. …
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".