Dynamics of cognitive and psycho-emotional disorders in the early recovery period of ischemic stroke during rehabilitation measures using stabilometric training
Bibliographic record
Abstract
Objective: to analyze post-stroke cognitive and psycho-emotional disorders in patients in the early recovery period of ischemic stroke, to assess the dynamics of these disorders during rehabilitation measures using stabilometric training. Materials and methods. The study involved 58 patients aged 35-75 years; the average age was 60.6 years. The study was conducted on the basis of Bryansk City Hospital No. 1 in the Department of Medical Rehabilitation. Stabilometric training was carried out on a computerized stabiloanalyzer with biofeedback "Stabilan-01-2" (Taganrog). The course included 7-10 sessions of stabilotherapy. The Montreal Cognitive Scale and the Hospital Anxiety and Depression Scale were used to assess cognitive and psychoemotional status before and after rehabilitation activities. Statistical analysis of the obtained data was carried out on a personal computer using MS EXCEL and IBM Statistica 12.0 application packages. The significance of differences between the studied groups was assessed using the nonparametric Mann-Whitney test. The dynamics in each group before and after treatment was assessed using the Wilcoxon test. Results. According to the results of the study, a significant improvement in the memory indicators of patients was revealed along with a decrease in the level of anxiety and depression. Conclusion. The positive effect of the use of a stabilometric training on the intellectual-mnestic and psycho-emotional functions of patients in the early recovery period of ischemic stroke revealed during the study allows us to recommend this method not only for motor rehabilitation, also to use it as a cognitive and psycho-corrective training.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".