Amisulpride augmentation of clozapine for treatment-refractory schizophrenia: a double-blind, placebo-controlled trial
Bibliographic record
Abstract
Background: A second antipsychotic is commonly added to clozapine to treat refractory schizophrenia, notwithstanding the limited evidence to support such practice. Methods: The efficacy and adverse effects of this pharmacological strategy were examined in a double-blind, placebo-controlled, 12-week randomized trial of clozapine augmentation with amisulpride, involving 68 adults with treatment-resistant schizophrenia and persistent symptoms despite a predefined trial of clozapine. Results: There were no statistically significant differences between the amisulpride and placebo groups on the primary outcome measure (clinical response defined as a 20% reduction in total Positive and Negative Syndrome Scale score) or other mental state measures. However, the trial under recruited and was therefore underpowered to detect differences in the primary outcome, meaning that acceptance of the null hypothesis carries an increased risk of type II error. The findings suggested that amisulpride-treated participants were more likely to fulfil the clinical response criterion, odds ratio 1.17 (95% confidence interval 0.40–3.42) and have a greater reduction in negative symptoms, but these numerical differences were not statistically significant and only evident at 12 weeks. A significantly higher proportion of participants in the amisulpride group had at least one adverse event compared with the control group ( p = 0.014), and these were more likely to be cardiac symptoms. Conclusions: Treatment for more than 6 weeks may be required for an adequate trial of clozapine augmentation with amisulpride. The greater side-effect burden associated with this treatment strategy highlights the need for safety and tolerability monitoring, including vigilance for indicators of cardiac abnormalities, when it is used in either a clinical or research setting.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Randomized trial | low |
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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, unvalidatedLabeled directly by 2 models reading the full record.
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".