Augmenting antipsychotic treatment with lamotrigine or topiramate in patients with treatment-resistant schizophrenia: a naturalistic caseseries outcome study
Bibliographic record
Abstract
The glutamate hyperfunction hypothesis of schizophrenia has been proposed largely on the basis of studies in post-mortem brain and the lack of efficacy of glutamate agonists as antipsychotic drugs. Recent reports have also suggested that the addition of lamotrigine, a glutamate excess release inhibitor, can cause a dramatic improvement in clozapine treatment-resistant patients, as well as attenuate the neuropsychiatric effects of ketamine in healthy volunteers. To explore the glutamate hyperfunction hypothesis, patients with schizophrenia who were treatment-resistant to current antipsychotic medications were augmented with either lamotrigine (n = 17) or topiramate (a glutamate kainate/alpha-amino-3-hydroxy-5-methyl-4-isoxazolaproprionate antagonist that potentiates GABA function) (n = 9) for 24 weeks. Patients receiving lamotrigine augmentation of clozapine had a significant decrease in Brief Psychiatric Rating Scale score after 2 weeks of treatment. There was no significant improvement when lamotrigine was added to risperidone, haloperidol, olanzapine or fluphenthixol. There was also no significant improvement observed with topiramate augmentation of clozapine, olanzapine, haloperidol and fluphenthixol. These preliminary data support previous evidence that lamotrigine is an effective augmentation agent for clozapine. Although limited by sample size, the findings also suggest glutamate hyperfunction in schizophrenia may have a presynaptic basis and that atypicals with low dopamine receptor occupancy may have antagonistic actions on glutamate function which confer additional antipsychotic activity.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".