Aripiprazole Once-Monthly in the Treatment of Acute Psychotic Episodes in Schizophrenia
Bibliographic record
Abstract
BACKGROUND: Long-acting injectable antipsychotics are treatment options for acute and long-term treatment of patients with schizophrenia. In a previously published 12-week randomized, double-blind, placebo-controlled clinical trial of patients with schizophrenia experiencing an acute psychotic episode, aripiprazole once-monthly 400 mg (AOM 400) produced significantly greater improvement than placebo on the primary endpoint, Positive and Negative Syndrome Scale (PANSS) total score at week 10. METHODS: To examine the efficacy of AOM 400 across a broader representation of schizophrenia symptoms, including agitation, a post hoc analysis of this trial was carried out to assess the change in PANSS Marder factor domains (positive symptoms, negative symptoms, disorganized thought, uncontrolled hostility/excitement, and anxiety/depression) and the PANSS excited component (equivalent to Marder factor domain uncontrolled hostility/excitement plus the tension item) by comparing differences in change from baseline between AOM 400 and placebo using a mixed model for repeated measures. RESULTS: The differences between treatment and placebo for all factors were statistically significant, with improvements seen as early as week 1 or 2, and maintained through week 12. Thus, AOM 400, supplemented with oral aripiprazole in the first 2 weeks, showed significantly greater efficacy versus placebo in acutely ill patients with schizophrenia in all 5 Marder illness domains, as well as in agitation as conceptualized by the PANSS excited component score. CONCLUSIONS: These findings indicate that AOM 400 is efficacious across the spectrum of schizophrenia symptoms in acutely ill patients, with implications for both short-term and, by extension, long-term patient outcomes.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".