The Canadian Network for Mood and Anxiety Treatments (Canmat) Task Force Recommendations for the Management of Patients with Mood Disorders and Comorbid Anxiety Disorders
Bibliographic record
Abstract
Background Comorbid mood and anxiety disorders are commonly seen in clinical practice. The goal of this article is to review the available literature on the epidemiologic, etiologic, clinical, and management aspects of this comorbidity and formulate a set of evidence- and consensus-based recommendations. This article is part of a set of Canadian Network for Mood and Anxiety Treatments (CANMAT) Comorbidity Task Force papers. Methods We conducted a PubMed search of all English-language articles published between January 1966 and November 2010. The search terms were bipolar disorder and major depressive disorder, cross-referenced with anxiety disorders/symptoms, panic disorder, agoraphobia, generalized anxiety disorder, social phobia, obsessive-compulsive disorder, and posttraumatic stress disorder . Levels of evidence for specific interventions were assigned based on a priori determined criteria, and recommendations were developed by integrating the level of evidence and clinical opinion of the authors. Results Comorbid anxiety symptoms and disorders have a significant impact on the clinical presentation and treatment approach for patients with mood disorders. A set of recommendations are provided for the management of bipolar disorder (BD) with comorbid anxiety and major depressive disorder (MDD) with comorbid anxiety with a focus on comorbid posttraumatic stress disorder, use of cognitive-behavioral therapy across mood and anxiety disorders, and youth with mood and anxiety disorders. Conclusions Careful attention should be given to correctly identifying anxiety comorbidities in patients with BD or MDD. Consideration of evidence- or consensus-based treatment recommendations for the management of both mood and anxiety symptoms is warranted.
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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 | 0.027 | 0.112 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.017 | 0.016 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".