Improving Outcomes in Patients With Bipolar Depression
Bibliographic record
Abstract
Only 3 medications are currently approved in the US for acute bipolar depression: 2 atypical antipsychotics and a combination atypical antipsychotic-selective serotonin reuptake inhibitor. Metabolic, neurologic, and hormonal adverse events are associated with all of the atypical antipsychotics approved for this indication. However, these agents differ in their propensity to cause weight gain or other side effects that significantly impact a patient's physical health and ability to function, and the selection of medication—which may also include a mood stabilizer—as well as other forms of treatment, will affect the outcome. It is important to design treatment based on individual needs. Evidence suggests that the collaborative care model, which incorporates individualized systematic treatment, may be more appropriate for the management of bipolar depression than the acute care model. J Clin Psychiatry 2015;76(3):e10 © Copyright 2015 Physicians Postgraduate Press, Inc. From the Department of Psychiatry and the Depression Clinical and Research Program, Harvard Medical School and Massachusetts General Hospital, Boston (Dr Nierenberg); the Departments of Psychiatry and Pharmacology, University of Toronto, and the Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Ontario, Canada (Dr McIntyre); and the Department of Psychiatry, Harvard Medical School, and the Bipolar Clinic and Research Program, Massachusetts General Hospital, Boston (Dr Sachs). PDF version of this InfoPack
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".