Adjunctive tianeptine treatment for bipolar disorder: A 24-week randomized, placebo-controlled, maintenance trial
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to assess the efficacy and tolerability of tianeptine as an adjunctive maintenance treatment for bipolar depression. METHODS: This is a multicenter double-blind randomized placebo-controlled maintenance trial of adjunctive tianeptine 37.5 mg/day. Participants ( n=161) had a Montgomery-Asberg Depression Rating Scale ⩾12 at entry. After eight weeks of open-label tianeptine treatment, those who responded to tianeptine ( n=69) were randomized to adjunctive tianeptine ( n=36) or placebo ( n=33) in addition to usual treatment. Kaplan-Meier estimates and the Mantel-Cox log-rank test were used to evaluate differences in time to intervention for a mood episode between the tianeptine and placebo groups. We also assessed overall functioning, biological rhythms, quality of life, rates of manic switch and serum brain-derived neurotrophic factor levels. RESULTS: There were no differences between adjunctive tianeptine or placebo regarding time to intervention or depression scores in the 24-week double-blind controlled phase. Patients in the tianeptine group showed better performance in the letter-number sequencing subtest from the Wechsler Adult Intelligence Scale at the endpoint ( p=0.014). Tianeptine was well tolerated and not associated with higher risk for manic switch compared to placebo. CONCLUSION: Tianeptine was not more effective than placebo in the maintenance treatment of bipolar depression. There is preliminary evidence suggesting a pro-cognitive effect of tianeptine in working memory compared to placebo.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".