Switching Outpatients With Schizophrenia and Related Disorders on Long-Acting Injectable Antipsychotics to Olanzapine: An Open-Label Naturalistic Pilot Study
Bibliographic record
Abstract
Little is known about the feasibility of switching patients with schizophrenia from long-acting injectable antipsychotics to oral olanzapine. We completed an open-label 14-week study to assess such a transition. This study included 25 stable outpatients (DSM-IV diagnosis of schizophrenia, schizophreniform disorder, or schizoaffective disorder) who were receiving long-acting injectable antipsychotics. Following a screening visit, patients began treatment with olanzapine 10 mg/day, which was initiated the day of their scheduled injection. Clinical assessments included the Clinical Global Impression-Improvement Scale (CGI-I) and the Positive and Negative Syndrome Scale (PANSS). Patient self-reports of adverse events were monitored and the Extrapyramidal Symptoms Rating Scale completed at each visit. In those completing the trial (N = 18), results revealed that a switch from injectable antipsychotics to olanzapine was associated with significant improvements on the CGI-I, negative symptoms, PANSS total scores, and parkinsonism. In considering the whole sample (last observation carried forward, N = 25), significant improvements on the CGI-I, parkinsonism, and dyskinesia were observed. Finally, those who failed to complete the trial (N = 7) did not change significantly from visit 1 to endpoint on any of the efficacy or safety measures. These results should be considered preliminary and require replication using appropriate control groups.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".