Lithium vs valproate in the maintenance treatment of bipolar I disorder: A post- hoc analysis of a randomized double-blind placebo-controlled trial
Bibliographic record
Abstract
OBJECTIVE: Lithium and valproate are commonly used either in monotherapy or in combination with atypical antipsychotics in maintenance treatment of bipolar I disorder; however, their comparative efficacy is not well understood. This study aimed to compare the efficacy of valproate and lithium on mood stability either in monotherapy or in combination with atypical antipsychotics. METHODS: We performed a post hoc analysis using data from a 52-week randomized double-blind, placebo-controlled trial, that recruited 159 patients with recently remitted mania during treatment with lithium or valproate and adjunctive atypical antipsychotic therapy. Patients were randomized to discontinue adjunctive atypical antipsychotic at 0, 24 or 52 weeks. RESULTS: No significant differences in efficacy were observed between valproate and lithium (hazard ratio: 0.99; 95% confidence interval: [0.66, 1.48]) in time to any mood event. Valproate with 24 weeks of atypical antipsychotic was significantly superior to valproate monotherapy in preventing any mood relapse (hazard ratio: 0.46; 95% confidence interval: [0.22, 0.97]) while lithium with 24 weeks of atypical antipsychotic was superior to lithium monotherapy in preventing mania (hazard ratio: 0.27; 95% confidence interval: [0.09, 0.85]) but not depression. CONCLUSION: Overall, this study did not find significant differences in efficacy between the two mood-stabilizing agents when used as monotherapy or in combination with atypical antipsychotics. However, study design and small sample size might have precluded from detecting an effect if true difference in efficacy existed. Further head-to-head investigations with stratified designs are needed to evaluate maintenance therapies.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".