Cariprazine in the treatment of Bipolar Disorder: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVES: Cariprazine is a partial agonist at D2/D3 receptors that has been approved for the treatment of mania associated with bipolar disorder (BD). This meta-analysis aimed to assess the efficacy and tolerability of cariprazine in the treatment of BD. METHODS: Randomized controlled trials investigating the efficacy of cariprazine in BD were included. Of the 391 studies yielded by search, 7 were included. The PRISMA protocol was followed and a set of analyses involving random-effects model with restricted maximum-likelihood estimator were used to synthesize effect sizes. RESULTS: Cariprazine was associated with a moderate and significant reduction of manic symptoms based on YMRS change scores (SMD: -0.52; 95%CI: -0.82 to -0.21; P = .018). Cariprazine resulted in significantly higher remission (OR: 2.05; 95%CI: 1.61-2.61; P = .006) and response rates (OR: 2.31; 95%CI: 1.35-3.95; P = .021) for manic and mixed episodes compared with placebo. Both cariprazine 1.5 mg and 3 mg doses were associated with small but significant reduction in depressive symptoms assessed with MADRS scores (SMD: -0.26, 95%CI: -0.49 to -0.02; P = .040) (SMD: -0.21, 95%CI: -0.41 to -0.01; P = .045), respectively. Cariprazine was significantly associated with the development of adverse effects but not with dropouts due to these adverse effects, when compared to placebo. CONCLUSION: Cariprazine appears to be safe and efficacious in the treatment of acute mania and mixed episodes associated with BD. Cariprazine at doses of 1.5-3 mg/day is efficacious in acute bipolar depression but the effect sizes were smaller. Controlled studies evaluating its efficacy for prophylaxis are needed.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.025 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".