Cariprazine in the Treatment of Bipolar Disorder: Within and Beyond Clinical Trials
Bibliographic record
Abstract
Bipolar disorder (BD) is chronic psychiatric disorder associated with significant impairment in psychosocial functioning and quality of life. Although current pharmacological treatments for BD have improved its clinical management, many patients do not achieve remission, particularly those suffering from bipolar depression. In addition, available treatments are associated with a myriad of potential adverse effects, which highlights the need for novel therapeutic agents that can be effective for both phases of the illness with a reduced side effect burden. Cariprazine is a novel antipsychotic that is a dopamine D2/D3 partial agonist with a preference for D3 receptors. In this review, we examine the pharmacological properties, clinical efficacy and tolerability profile of cariprazine in patients with BD, taking into account the latest clinical trials data. We also review post hoc analyses addressing clinically relevant subgroups and symptom domains in BD. Current evidence suggests efficacy for cariprazine 3–12 mg/day in the treatment of acute manic and mixed episodes; for bipolar depression, the efficacy of cariprazine appears to be dose-related, with doses of 1.5–3 mg/day beneficial as monotherapy. Cariprazine is overall well-tolerated by patients in both manic and depressive episodes. Its most common side effects relative to placebo include akathisia, extrapyramidal symptoms and nausea. There are no metabolic concerns reported with cariprazine use. In summary, the latest evidence suggests that cariprazine is an effective and safe treatment option for BD.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".