Different types of long-term use of antipsychotics on cognitive function in survey
Bibliographic record
Abstract
Objective To investigate the effects of Long-term use of different types of antipsychotics on cognitive function in schizophrenia.Methods Using the Montreal Cognitive Assessment Scale(MoCa),Simple Intelligent mental state examination(MMSE) assessed cognitive function in patients with schizophrenia who continued taking typical,atypical antipsychotics or two types of drugs combined with 10 years,with Using the Brief Psychiatric Rating scale(BPRS) to assess its psychotic symptoms.Results The scores of MoCa and MMSE in three groups were decreased,and there were no significantly differences among the three groups.Conclusion The harm of cognitive function in patients with schizophrenia showed no significant relation with Long-term use of different types of antipsychotics,while it may be associated with the disease outcome.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| 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) | 0.000 | 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 teacher head, 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".