Acute and maintenance treatment of bipolar mania: the role of atypical antipsychotics
Bibliographic record
Abstract
Bipolar disorder is a complex condition including depression, mania, and in many cases associated with comorbid anxiety symptoms and substance abuse. Mood stabilizers including lithium and divalproex have been considered standard therapy for the treatment of patients with bipolar disorder, but remission rates remain inadequate. Conventional antipsychotics have demonstrated efficacy for acute mania, but they appear to have little role in the maintenance treatment of bipolar disorder. Despite substantial evidence of efficacy and recent guideline recommendations, atypical antipsychotics remain underused for the treatment of bipolar disorder. Data from double-blind, controlled trials are available for a number of clinically meaningful efficacy measures, including improvement in manic symptoms, onset of action, response rates, remission rates, improvement in comorbid depressive symptoms, and induction/worsening of mania or depression. Atypical antipsychotics are effective both as alternatives to lithium or divalproex as monotherapy, or in combination with these mood stabilizers, in the acute and likely the maintenance treatment of mania. The atypical antipsychotics represent an effective and relatively safe addition to our armamentarium for the treatment of bipolar disorder.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".