Long-term effectiveness of aripiprazole once monthly on functioning and quality of life in schizophrenia: results of year 2 of the ReLiAM study
Bibliographic record
Abstract
BACKGROUND: Aripiprazole once-monthly (AOM) has proven effective in the treatment of schizophrenia, although little is known about its impact on global functioning and quality of life beyond 1 year. Here, we investigate the continued impact of AOM on the participants of the ReLiAM study during the second year of follow-up. METHODS: The participants who were evaluated at ≥ 1 time point during the second year of the ReLiAM study (months 15, 18, 21, and 24; year 1 completers) were assessed via the GAF scale. Secondary outcomes were reported on the SOFAS, CGI-S, and QLS. RESULTS: 109 (86%) completed at least 1 post-12-month visit and 33 (30.3%) patients completed the final assessment at month 24. The improvements observed in the year 1 completers in GAF total score were maintained through to year 2 completers. The improvements in CGI-S and SOFAS that were observed at the end of year 1 were also maintained through the end of the second year. Similar trends of sustained improvement in GAF total score, CGI-S score, and SOFAS were observed in the post-hoc analyses of the year 2 completers. Seventy-four percent (74.3%) of year 1 completers experienced mild treatment-emergent adverse events during the second year, the most frequently reported being weight gain, akathisia, and insomnia. Seventeen percent (17.4%) experienced serious adverse events. Similar findings regarding effectiveness and tolerability were reported in the year 1 completers and in year 2 completers. CONCLUSIONS: These findings suggest that the favorable effectiveness, including tolerability observed during the first year following AOM initiation, are maintained and may even continue to improve during the second year of treatment. TRIAL REGISTRATION: ClinicalTrials.gov NCT02131415, first posted on May 6, 2014. Overall trial status: Terminated.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".