Pharmacotherapy of bipolar mixed states
Bibliographic record
Abstract
OBJECTIVE: Mixed episodes comprise up to 40% of acute bipolar admissions. They are difficult-to-treat, complex clinical pictures. This review provides an overview of the available literature on the pharmacotherapy of manic-depressive mixed states and suggests treatment options. METHOD: Literature was identified by searches in Medline, Embase and the Cochrane Controlled Trials Register. Studies were considered relevant if they contained the keywords mixed mania, mixed state(s), mixed episode(s), treatment, therapy, study or trial. RESULTS: Overall, there were very few double-blind, placebo-controlled studies specifically designed to treat manic-depressive mixed states. Rather, patients with mixed states comprised a sub-group of the examined patient cohorts. Nevertheless, the data show that acute mixed states do not respond favourably to lithium. Instead, valproate and olanzapine are drugs of first choice. Carbamazepine may play a role in the prevention of mixed states. Antidepressants should be avoided, because they may worsen intraepisodic mood lability. Lamotrigine may be useful in treating mixed states with predominantly depressive symptoms. CONCLUSIONS: More treatment studies specifically designed to treat the complex clinical picture of mixed states are clearly needed. Current treatment recommendations for clinical practice based on the available literature can only target select aspects of these episodes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".