Clozapine and visuospatial processing in treatment-resistant schizophrenia
Bibliographic record
Abstract
INTRODUCTION: Clozapine, the most widely used option in treatment-resistant schizophrenia, has been shown to be superior to other antipsychotic medications in improving cognitive function in patients. However, the results have not been consistent and the mechanisms underlying this effect have not been elucidated. Thus, the purpose of the present study was to evaluate verbal and nonverbal cognition (using visuospatial processing tests) in patients treated with clozapine (initially treatment resistant) and those treated with other second-generation antipsychotics, relative healthy control subjects. Furthermore, we examined neural correlates of visuospatial processing in the three groups. METHODS: Twenty schizophrenia patients treated with clozapine (TR-C group), 23 patients stabilised with atypical antipsychotics other than clozapine (NTR group), and 21 healthy control participants completed a battery of verbal and visuospatial cognitive tests. In addition, participants underwent functional magnetic resonance imaging (fMRI) while performing one of the visuospatial tests (the mental rotation task). The fMRI data were analysed separately in each group using Statistical Parametric Mapping software (SPM5). RESULTS: Overall, schizophrenia patients exhibited deficit on verbal and nonverbal processing relative to the healthy controls, but we observed some interesting differences between the two groups of patients. Specifically, the NTR group performed better than the TR-C group on the Block Design and the Raven's Progressive Matrices. With respect to brain function during mental rotation, the NTR group showed significant activations in regions of the temporal and occipital cortex, whereas the TR-C patients did not. The relative deactivations associated with the task were also more robust in NTR compared to the other group of patients, despite a similar performance. CONCLUSION: Present results suggest better visuospatial processing in the NTR relative to the TR-C group. This difference could be attributed to the treatment resistance itself or a lack of beneficial effect of clozapine relative to other atypical antipsychotics in ameliorating nonverbal abilities. Future studies of the relationship between clozapine and cognition, as well as between treatment resistance and cognition, are warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".