Bibliographic record
Abstract
Less than half of patients with schizophrenia obtain full response to antipsychotic drugs and, while clozapine represents the treatment of choice for refractory psychosis, a significant number of individuals remain only partially responsive. Despite a need for augmentation in this subpopulation, to date clear choices have not been forthcoming. Because clozapine, along with the majority of second-generation agents (SGAs), are linked to metabolic disturbances, augmentation strategies that do not further exacerbate these side effects are needed. Topiramate, unlike other anticonvulsants used for augmentation purposes, has been associated with weight loss. This article reviews the safety and efficacy of topiramate in treatment-refractory schizophrenia, including effects on metabolic disturbances, which burden this population. While current evidence specifically examining improvements in psychopathology demonstrates small to moderate benefits with topiramate augmentation, a growing body of evidence suggests that topiramate may have beneficial effects on antipsychotic-induced weight gain. We conclude that topiramate's metabolic profile, taken together with a current lack of evidence supporting a particular augmentation strategy, argues for further well-controlled studies examining its potential as an augmentation strategy in schizophrenia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".