Antidepressants for the Acute Treatment of Bipolar Depression
Bibliographic record
Abstract
OBJECTIVE: The role of antidepressants in the acute treatment of bipolar depression remains a contentious issue. A previous meta-analysis of randomized controlled trials (RCTs) concluded that antidepressants were effective and safe for bipolar depression. Several trials published since then suggest that antidepressants may not be as beneficial as previously concluded. The current systematic review and meta-analyses reexamine the efficacy and safety of antidepressant use for the acute treatment of bipolar depression. DATA SOURCES: EMBASE, MEDLINE, CINAHL, PsycINFO, and the Cochrane Central Register of Controlled Trials databases were searched for double-blind RCTs published from 2003 to 2009 using the following diagnostic medical subject heading (MESH) terms: bipolar disorder, bipolar depression, bipolar I disorder, bipolar II disorder, bipolar III disorder, bipolar mania, cyclothymia, manic depressive psychosis, mixed mania and depression, and rapid cycling and bipolar disorder. Databases of trial registries were also searched for unpublished RCTs. These searches were supplemented by hand searches of relevant articles and review articles. STUDY SELECTION: Trials that compared acute (< 16 wk) antidepressant treatment with either an active drug or a placebo comparator in adult bipolar patients, depressive phase were eligible for inclusion. Main outcome measures were clinical response, remission, and affective switch. DATA SYNTHESIS: Six RCTs (N = 1,034) were identified since publication in 2004 of the first meta-analysis that assessed antidepressant use in the acute treatment of bipolar depression. These studies were combined with earlier studies for a total of 15 studies containing 2,373 patients. Antidepressants were not statistically superior to placebo or other current standard treatment for bipolar depression. Antidepressants were not associated with an increased risk of switch. Studies that employed more sensitive criteria to define switch did report elevated switch rates for antidepressants. CONCLUSIONS: Although antidepressants were found to be safe for the acute treatment of bipolar depression, their lack of efficacy may limit their clinical utility. Further high-quality studies are required to address the existing limitations in the literature.
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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 | 0.008 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.005 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".