Research on the Effect of Individualized Therapy on Cognitive Function in Patients with Vascular Cognitive Impairment Based on Brain Rehabilitation Health Measurement System (Preprint)
Bibliographic record
Abstract
BACKGROUND Background: Vascular cognitive disability (VCI) includes various degrees of mental decline related to cerebrovascular disease. It refers to the basic pathological process of the formation of Alzheimer's disease. Its early diagnosis and treatment are beneficial to improve the prognosis of patients. OBJECTIVE Objective: To explore the effect of individualized therapy based on brain rehabilitation health measurement system on the cognitive function and event-related potential (ERP) P300 of patients with vascular cognitive impairment no dementia (VCIND). METHODS Methods: Sixty patients with non-dementia vascular cognitive impairment were randomly divided into a training group and a control group. Both groups were given conventional medication and traditional rehabilitation training. Based on it, the training group added cognitive training of the brain rehabilitation health measurement system, 40 minutes/time, once a day, 5 times a week for 4 weeks. Then, the mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), Barthel Index (BI) and myoelectric evoked potential were used to measure and evaluate the cognitive function, daily life activities and P300 of the two groups of patients. RESULTS Results: After treatment, the MoCA score, MMSE, BI score, visual space and executive function, attention, language function, and delayed memory of the training group were significantly improved compared with the control group, and the difference was significant (P <0.05). The incubation period of P300 in the training group was shorter than that in the control group, and the amplitude was higher than that in the control group, the difference was statistically significant (P <0.05). CONCLUSIONS Conclusions: Brain rehabilitation health measurement system assisted cognitive training can effectively improve the cognitive function and daily activities of VCIND patients. CLINICALTRIAL
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".