Effectiveness of mood stabilizers and antipsychotics in the maintenance phase of bipolar disorder: a systematic review of randomized controlled trials
Bibliographic record
Abstract
BACKGROUND: Bipolar disorder (BD) is a leading cause of disability. Systematic reviews of randomized trials for the treatment of the maintenance phase of BD are lacking. OBJECTIVES: To determine the efficacy and tolerability of mood stabilizers and antipsychotics in the maintenance treatment of BD. METHODS: We systematically reviewed randomized controlled trials of licensed medications for the treatment of any phase of BD. We included randomized controlled trials comparing a medication to placebo or another medication. Comprehensive searches of electronic databases were conducted to March 2005. Outcomes investigated were relapse due to mania, depression or any mood episode, and withdrawal due to any reason or due to an adverse event. Data were combined through meta-analysis. RESULTS: Fourteen studies (n = 2,526) met the inclusion criteria. Lithium, lamotrigine, olanzapine and valproate semisodium each demonstrated evidence to support long-term use. Compared with placebo, all medications were more effective at preventing relapse because of any mood episode. Hazard ratios (HR) were 0.68 [95% confidence interval (CI) = 0.53-0.86] for lithium, 0.68 (95% CI = 0.55-0.85) for lamotrigine, and 0.82 (95% CI = 0.57-1.20) for valproate semisodium; for olanzapine, the risk ratio (RR) was 0.58 (95% CI = 0.49-0.69). Lithium and olanzapine significantly reduced manic relapses (HR = 0.53; 95% CI = 0.35-0.79 and RR = 0.37; 95% CI = 0.24-0.57, respectively). Lamotrigine and valproate semisodium significantly reduced depressive relapses (HR = 0.65; 95% CI = 0.46-0.91 and RR = 0.40; 95% CI = 0.20-0.82, respectively). Lithium significantly reduced manic relapses compared with lamotrigine (HR = 0.56; 95% CI = 0.34-0.92) and olanzapine significantly reduced manic relapses compared with lithium (RR = 1.69; 95% CI = 1.12-2.55). Withdrawal due to an adverse event was approximately twice as likely with lithium compared with valproate semisodium (RR = 1.81; 95% CI = 1.08-3.03) and lamotrigine (RR = 2.20; 95% CI = 1.31-3.70). There were few data for carbamazepine or medications given as adjunct therapy. CONCLUSIONS: Mood stabilizers have differing profiles of efficacy and tolerability, suggesting complementary roles in long-term maintenance treatment.
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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 | 0.025 | 0.080 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.015 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".