Магнитно-резонансная морфометрия головного мозга у пациентов с постинсультными когнитивными нарушениями
Bibliographic record
Abstract
Aim. To assess the correlation between some indices of brain magnetoresonance morphometry, neurological, cognitive status and sleep quality in patients with ischemic stroke. Materials and methods. 29 patients aged 48-76 (10 men and 19 women) were examined in the acute period of stroke. Neuropsychological examination included Mini-mental State Examination (MMSE), Frontal Assessment Battery (FAB), Montreal Cognitive Assessment (MoCA), Watch Drawing Test (WDT), Words Test (5) (WT5), Schulte Table (ST) and Categoric Verbal Fluency Test (VF); sleep quality was assessed using Pittsburg Sleep Quality Index (PSQI). Margetoresonance (MR) tomography of the brain was performed; the following MR-morphometric indices were studied: brain volume ( V b), brain ventricular volume ( V v), brain volume to ventricular volume ratio (V b/ V v), leukoareosis square ( S l), infarction focus square ( S f), and hippocampus volume ( V h). Results. The results of correlation analysis of MR-morphometric indices, cognitive tests and sleep quality were received; the role of each index was estimated, morphometric differences between patients with disregulatory, disregulatory-dismnestic and dismnestic variant of cognitive disorders were studied. Conclusions. V v and V b/ V v are connected with global cognitive status and state of most cognitive spheres. Patients with disregulatory type of the postinsult cognitive disorders are characterized by the highest V v unlike patients with dismnestic variant. V f is connected with cognitive activity status as a whole, its executive component and sleep quality. V h is not associated with memory indices, but is associated with global cognitive status and regulatory-dynamic domen state. It is worthwhile to develop a complex of MR-morphometric indices which could have serve as an instrument for differential diagnosis of the postinsult cognitive disorders.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".