Effectiveness of antipsychotic polypharmacy for patients with treatment refractory schizophrenia: an open‐label trial of olanzapine plus risperidone for those who failed to respond to a sequential treatment with olanzapine, quetiapine and risperidone
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effectiveness of antipsychotic polypharmacy in a methodologically sound manner. METHODS: In this open-label study, 17 patients with treatment-refractory schizophrenia, who failed to respond to a sequential monotherapy with olanzapine, quetiapine and risperidone, were subsequently treated with a combination therapy with olanzapine plus risperidone for at least 8 weeks. RESULTS: Seven responded according to the primary endpoint defined as the post-treatment Brief Psychiatric Rating Scale being less than 70% of the pretreatment values, and they were classified as such an average of 10 weeks after the initiation of polypharmacy. Two of them were successful in a later conversion to monotherapy. None dropped out prematurely. Four (out of 13 inpatients) got better enough to be discharged from the hospital, while six patients did not show any response. The Global Assessment of Functioning score improved from 37.1 to 53.0 in responders (mean maximum dose: olanzapine 12.9 mg; risperidone 3.14 mg), while it showed non-significant changes among others (mean maximum dose: olanzapine 14.5 mg; risperidone 5.50 mg). Body weight, prolactin, and total cholesterol increased significantly. CONCLUSIONS: Antipsychotic polypharmacy might be sometimes helpful for difficult populations but at the cost of adverse effects. More studies of antipsychotic combination therapy versus clozapine, augmentation strategies or tenacious longer- term monotherapy are warranted for refractory schizophrenia.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".