Antidepressant-Associated Mania in Bipolar Disorder: A Review and Meta-analysis of Potential Clinical and Genetic Risk Factors
Bibliographic record
Abstract
PURPOSES/BACKGROUND: Antidepressants (ADs) play a valuable role in treating the depressive episodes of bipolar disorder. However, 14% of these individuals taking ADs experience AD-associated mania (AAM) within a few weeks of starting treatment. Numerous studies have suggested potential clinical and genetic risk factors. We aimed to conduct a comprehensive systematic review and meta-analysis that integrates the past literature with the recent studies and identifies important predictors for AAM. METHODS/PROCEDURES: The review was limited to experimentally designed studies that contain the relevant search terms in PubMed and PsychInfo. After removing studies that were in discordance with our criteria, the review included 24 reports examining clinical risk factors and 10 investigating genetic risk factors. Our meta-analysis was conducted on 5 clinical risk factors, each of which had at least 4 articles with extractable data. FINDINGS/RESULTS: The only clinical factors in the literature that have been shown to be more indicative of AAM risk are AD monotherapy and tricyclic ADs. Among genetic factors, the serotonin transporter gene polymorphism may play a minor role in AAM. Our meta-analysis provided support for the number of prior depressive episodes. IMPLICATIONS/CONCLUSION: Prevention of AAM may be served by early detection of recurrent depression episodes. Further large-scale longitudinal studies are required to determine the underpinnings of AAM.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.018 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".