Аpplication of rehabilitation technologies to improve cognitive functions in patients with ischemic stroke
Bibliographic record
Abstract
BACKGROUND: Currently, the development and implementation of new effective comprehensive programs for medical rehabilitation of patients who have undergone acute cerebrovascular accident is an important and urgent medical problem. AIMS: To study the effect of combined methods of medical rehabilitation in patients with post-stroke spasticity on cognitive functions and psychoemotional status. MATERIAL AND METHODS: The study involved 60 patients who underwent ischemic stroke with movement disorders in the form of hemiparesis with increased muscle tone in the form of spasticity in the long-term period. Patients of the control group (30 people) underwent standard drug therapy and medical rehabilitation, patients of the main group (30 people), against the background of standard drug therapy and medical rehabilitation, used combined physiotherapy methods from the Alpha LED Oxy Light Spa apparatus. Subjective indicators of cognitive impairment (Montreal Cognitive Assessment Scale) and psychoemotional defects (Hospital Anxiety and Depression Scale) were assessed. RESULTS: Immediately after treatment on day 14, cognitive functions significantly improved and the degree of psychoemotional defect decreased, which was confirmed by the MOCA and HADS scales. CONCLUSION: The inclusion of combined physiotherapy methods in the standard complex of medical rehabilitation and treatment of patients after ischemic stroke with movement disorders in the form of hemiparesis contributes to a significant improvement in cognitive functions and a decrease in the degree of psychoemotional impairment.
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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) | 0.003 | 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".