Analysis of cognitive status in patients with different nosologies and clinical variants of very late manifesting schizophreniform psychosis
Bibliographic record
Abstract
OBJECTIVE: To study and compare the features of cognitive functioning in patients with very late-manifesting schizophreniform psychosis (VLMSP) depending on the clinical variants of the disease. MATERIAL AND METHODS: The study included 61 patients (58 females, 3 males) aged 63 to 78 years. All patients met the ICD-10 criteria for psychosis and had no signs of dementia. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA) score and the Mini-Mental State Examination (MMSE). Statistical analysis was performed using non-parametric methods. RESULTS: <0.05), which partially improved after treatment, but remained below the reference values (MMSE on Day 28 was 24.5 [22; 26] points, MoCA on Day 28 was 18.5 [17; 22] points). In patients with paranoid symptoms, cognitive impairment was less pronounced (MMSE on Day 0 was 26 [24; 28] points, MoCA on Day 0 was 0 [17; 24.5] points) and stable (MMSE on Day 28 was 27 [25.5; 29.5] points, MoCA on Day 28 was 21 [17; 25] points). In the group where affective-delusional symptoms prevailed, the cognitive deficit was minimal (MMSE on Day 0 was 27.5 [27; 28.5] points, MoCA on Day 0 was 24 [23; 26.5] points) and completely reduced after treatment (MMSE on Day 28 was 29 [28; 30] points, MoCA on Day 28 was 26 [25; 28] points). CONCLUSION: The study showed significant differences in cognitive status in patients with VLMSP depending on the clinical variant of the disease. The results emphasize the need for an individualized approach to diagnosing and treating VLMSP and the importance of monitoring cognitive functions for early detection of neurodegenerative processes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".