Melancholic Features in Bipolar Depression and Response to Lamotrigine
Bibliographic record
Abstract
BACKGROUND: A pilot study suggested lamotrigine may be more effective for bipolar depression with melancholic features. We tested this hypothesis in a pooled analysis of 5 randomized double-blind placebo-controlled trials of lamotrigine for acute bipolar depression. METHODS: The pooled sample consisted of 1072 adult outpatients. Depressive symptoms were assessed for 7 to 10 weeks with the Hamilton Depression Rating Scale and the Montgomery-Åsberg Depression Rating Scale. The outcome measure was end-trial response (score reduction ≥ 50%). Melancholic features were assessed with both the Structured Clinical Interview for DSM-IV and baseline depression scale items, according to DSM criteria. RESULTS: The item-based melancholic specifier was associated with numerically larger treatment effects, although subgroup-treatment interactions in logistic regression models did not reach statistical significance. The small subgroup of patients with severe psychomotor retardation also appeared to benefit from lamotrigine. However, the Structured Clinical Interview for DSM-IV melancholic specifier was not associated with larger treatment effects. Baseline depression severity was inconsistently associated with response, depending on which scale was used to define severity. The 2 melancholia variables had poor agreement despite having similar prevalences. CONCLUSIONS: Our results do not clearly support the original hypothesis but do reinforce the importance of replicating secondary analyses of clinical trials with additional data.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".