Review of Evidence for Use of Antidepressants in Bipolar Depression
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Depressive episodes predominate over the course of bipolar disorder and cause considerable functional impairment. Antidepressants are frequently prescribed in the treatment of bipolar depression, despite concerns about efficacy and risk of switching to mania. This review provides a critical examination of the evidence for and against the use of antidepressants in bipolar depression. DATA SOURCES: English-language peer-reviewed literature and evidence-based guidelines published between January 1, 1980, and March 2014, were identified using PubMed, MEDLINE, PsycINFO/PsycLIT, and EMBASE. All searches contained the terms antidepressants, bipolar depression, depressive episodes in bipolar disorder, and treatment guidelines for bipolar depression. Meta-analyses, randomized controlled trials, systematic reviews, and practice guidelines were included. Bibliographies from these publications were used to identify additional articles of interest. DATA EXTRACTION: Studies involving treatment of bipolar depression with antidepressant monotherapy, adjunctive use of antidepressant with a mood stabilizer, and meta-analysis of such studies combined were reviewed. CONCLUSIONS: The body of evidence on the use of antidepressant monotherapy to treat patients with bipolar depression is contentious, but the recommendations from evidence-based guidelines do not support antidepressant monotherapy for bipolar depression. Only when mood stabilizer or atypical antipsychotic monotherapy has failed should adjunctive treatment with an antidepressant be considered.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it