Nursing effects of finger exercise on cognitive function and others for cerebral ischemic stroke patients.
Bibliographic record
Abstract
OBJECTIVE: To investigate the nursing effects of finger exercise training on cognitive function and others for patients with cerebral ischemic stroke (CIS). METHODS: A total of 200 patients with CIS were selected in this prospective study. According to the random number table method, they were divided into control group (n=100, routine nursing) and research group (n=100, routine nursing combined with finger exercise training). Various scales were used to evaluate the cognitive function, hand function, upper limb motor function, wrist flexor muscle tone, degree of neurological impairment and ability of daily living (ADL) in the two groups before and after intervention. And the incidence of mild vascular cognitive impairment (VCI) after intervention was compared. RESULTS: After intervention, Montreal Cognitive Assessment (MoCA), Mini Mental State Examination (MMSE), hand function, Fugl-meyer Assessment (FMA) and ADL scores in both groups were significantly increased, and those in the research group were significantly higher than those in the control group (all P<0.05). There were opposite trends in the Neurologic Functional Defect (NIHSS) and Modified Ashworth Scale (MAS) for wrist flexor scores (all P<0.05). The incidence of mild VCI in the research group was significantly lower than that in the control group (P<0.05). CONCLUSION: On the basis of early rehabilitation nursing, combined finger exercise training can improve cognitive function, hand function, upper limb function and ADL for patients with CIS.
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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) | 0.001 | 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".