A Double-Blind Randomized Trial of Mood Stabilizer Augmentation Using Lamotrigine and Valproate for Patients With Schizophrenia Who Are Stabilized and Partially Responsive
Bibliographic record
Abstract
OBJECTIVE: To compare the efficacy of mood stabilizer augmentation of an antipsychotic for patients with schizophrenia who are both stabilized and partially responsive. METHOD: Adult patients who met the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria for schizophrenia or schizoaffective disorder were enrolled in a 12-week, double-blind randomized trial. Patients were stabilized on an antipsychotic, and dose remained constant. Patients were randomly assigned to 1 of 3 adjunctive treatments: (1) with lamotrigine, (2) with divalproex sodium, or (3) with placebo. Efficacy assessments included the Positive and Negative Syndrome Scale, the Calgary Depression Scale for Schizophrenia, a Demoralization Scale, and the Clinical Global Impression severity and improvement scores. The Lehman quality of life improvement scale was used to assess quality of life and social functioning. Ratings were done at each study visit, including the last visit when they had been tapered off the adjunctive treatment. RESULTS: There were no differences in global outcomes, symptoms, quality of life, or demoralization among the 3 groups. Short-term adverse effects were minimal. CONCLUSIONS: Augmenting antipsychotics with the mood stabilizers of lamotrigine or divalproex sodium for most partially responsive patients with chronic schizophrenia did not seem to be a useful treatment strategy for improving the residual symptoms. The small sample size limits firm conclusions.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".