Switch to mania after acute antidepressant treatment for bipolar depression: a systematic review and network meta-analysis of randomised controlled trials
Bibliographic record
Abstract
Background: The potential for antidepressants to induce a switch to mania remains a major concern in the treatment of bipolar depression, but the specific risk associated with different antidepressants remains unclear. This systematic review and network meta-analysis (NMA) assessed this risk by comparing individual antidepressants with each other and with a common placebo. Methods: In this systematic review and network meta-analysis, we searched ClinicalTrials.gov, CENTRAL, PsycINFO, PubMed, Scopus, and Web of Science from database inception up to Feb 19, 2025, with no language restrictions, for randomised controlled trials (RCTs) assessing acute antidepressant treatment in bipolar depression. The primary outcome was the rate of switch to mania after antidepressant treatment. A frequentist NMA estimated risk ratios (RRs) and 95% confidence intervals. Sensitivity analyses were performed based on treatment regimen (monotherapy or add-on), baseline severity, switch to mania definition, study setting, psychiatric comorbidity, treatment duration, non-pharmacological combinations, industry sponsorship, and risk of bias. Certainty of evidence was assessed using the CINeMA framework. The protocol was preregistered on the Open Science Framework. Findings: Of 2434 records screened, 13 RCTs (1362 patients; 818 [60.1%] female, 511 [37.5%] male, and 33 [2.4%] not disclosed) were included in the NMA. Although some evidence of increased risk of switching to mania was observed, no antidepressant was associated with a significantly higher risk of switch to mania compared to placebo. Venlafaxine showed the highest risk estimate among antidepressants, though not statistically significant RR (4.53 [95% CI 0.47-43.25]), and was the only compound with consistent signals of increased switch in individual studies. The evidence base was larger for add-on therapy, while fewer data were available for monotherapy. Sensitivity analyses confirmed the results. Heterogeneity was low. Overall confidence in the evidence was rated as low. Interpretation: Antidepressants remain a treatment option for acute bipolar depression, particularly as add-on therapy. Their use should be individualised, considering patient-specific profiles and other potential risks, in line with a precision psychiatry approach. Further studies are needed to clarify long-term safety. Funding: None.
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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 | 0.042 | 0.103 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.050 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| 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".