Quetiapine May Induce Mania: A Case Report
Bibliographic record
Abstract
Inducing manic or hypomanic symptoms is a well-documented risk during anti- depressive treatment with different classes of antidepressants. Recently, several case reports and a critical review have demonstrated a similar risk induced by atypical antipsychotics, such as olanzapine and risperidone. A serotonin (5-HT) receptor occupancy (5-HT2 and 5-HTD2) hypothesis has been proposed to explain olanzapine and risperidone effects on mood, but other mechanisms are likely involved in the manic switch that is associated with these 2 atypical antipsychotics. \nWe report a case of possible induction of manic episode associated with quetiapine treatment in a patient with a schizofreniform disorder. The gradual onset of manic symptoms during quetiapine treatment and the rapid remission with discontinuation of the drug in a patient without a history of mania and without past or current substance abuse seems to support the possibility that quetiapine was responsible for inducing the manic episode. In our case manic symptoms appeared slowly at a moderate quetiapine dosage. This seems to support the hypothesis proposed for risperidone, with which quetiapine shares biochemical features; specifically, at high dosages, dopaminergic blockade action shows antimanic properties, while, conversely, at smaller dosages, the mania-inducing effects could result from the 5-HT2 antagonistic action, as well as the ensuing dopamine disinhibiting effects.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".