Canadian Network for Mood and Anxiety Treatments (CANMAT) guidelines for the management of patients with bipolar disorder: update 2007
Bibliographic record
Abstract
In 2005, the Canadian Network for Mood and Anxiety Treatments (CANMAT) published guidelines for the management of bipolar disorder. This update reviews new evidence since the previous publication and incorporates recommendations based on the most current evidence for treatment of various phases of bipolar disorder. It is designed to be used in conjunction with the 2005 CANMAT Guidelines. The recommendations for the management of acute mania remain mostly unchanged. Lithium, valproate and several atypical antipsychotics continue to be recommended as first-line treatments for acute mania. For the management of bipolar depression, new data support quetiapine monotherapy as a first-line option. Lithium and lamotrigine monotherapy, olanzapine plus selective serotonin reuptake inhibitors (SSRI), and lithium or divalproex plus SSRI/bupropion continue to remain the other first-line options. First-line options in the maintenance treatment of bipolar disorder continue to be lithium, lamotrigine, valproate and olanzapine. There is recent evidence to support the combination of olanzapine and fluoxetine as a second-line maintenance therapy for bipolar depression. New data also support quetiapine monotherapy as a second-line option for the management of acute bipolar II depression. The importance of comorbid psychiatric and medical conditions cannot be understated, and this update provides an expanded look at the prevalence, impact and management of comorbid conditions in patients with 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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".