Psilocybin use in bipolar disorder: A comprehensive review
Bibliographic record
Abstract
INTRODUCTION: Bipolar disorder (BD) is a severe and persistent mental disorder characterized by recurrent mood episodes, with BD depression accounting for most of the illness burden. Although the mainstay treatment of BD consists of pharmacotherapy with mood stabilizers and atypical antipsychotics, a large proportion of patients with BD depression do not respond to adequate trials of medications. In addition, these medications can be associated with multiple, often significant adverse effects, highlighting the need for novel therapeutic agents that are acceptable, effective and safe for patients. METHODS: We performed a comprehensive narrative review on the use of psilocybin in BD, with a focus on clinical outcomes. RESULTS: Two small clinical trials show that psilocybin combined with psychotherapy was safe and effective for the treatment of BDII depression with large treatment effects. No serious adverse events, including treatment-emergent mania/hypomania or increased suicidality, were reported in both trials. However, other studies have raised concerns about the safety of psilocybin in BD patients, including the development or worsening of manic symptoms, sleep disruptions and anxiety. Overall, the majority of BD patients believe that psilocybin could benefit their mental health problems, but their experiences varied depending on several contextual factors, such as polysubstance use, psilocybin dose, solo versus social experiences and pre-psilocybin sleep deprivation. CONCLUSION: Despite its promising potential, the efficacy and safety of psilocybin in the treatment of BD depression remain unclear, and future research is essential to clarify its therapeutic value in 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| 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) | 0.003 | 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".