Add-on Quetiapine for Bipolar Depression: A 12-Month Open-Label Trial
Bibliographic record
Abstract
OBJECTIVES: Bipolar disorder (BD) is a disabling and often chronic condition. Patients with BD suffer from depression at least one-third of the time, but they do not always respond well to conventional mood stabilizers. Attempts to treat them with antidepressants can provoke a switch to mania or increased cycling. Our open-label trial aimed to assess the long-term response of patients with bipolar depression to the addition of quetiapine to their usual treatment. Our study also sought to assess the safety and tolerability of quetiapine in patients with BD. METHOD: To meet inclusion criteria for the study, patients had a DSM-IV diagnosis of type I or II BD, were aged 18 years and older, currently suffered from depression with a score of > 18 on the Hamilton Depression Rating Scale (HDRS), and had no change in antidepressant use for at least 3 weeks prior to the study. We added quetiapine to patients' medication and attempted to increase the dosage to at least 400 mg daily. Outcome was measured at baseline and once monthly for 12 months on the HDRS, the Young Mania Rating Scale, the Clinical Global Impression Scale (CGI), and the Abnormal Involuntary Movement Scale. RESULTS: There were 19 patients enrolled in the study (6 men and 13 women), 2 of whom dropped out because they could not tolerate the drug. Seventeen completed at least 2 assessments, and 7 patients completed the full 12-month trial. Data for the 17 patients (that is, last observation carried forward) at 12 months shows HDRS scores reduced from 27.2 to 12.1 and CGI scores reduced from 4.7 to 2.6. CONCLUSIONS: Quetiapine seems to be helpful to and relatively well tolerated by patients with bipolar depression when it is added to their usual treatment. There is, however, a need for controlled trials.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".