Early neurological bedside rehabilitation intervention on the recovery of activities of daily living in stroke patients
Bibliographic record
Abstract
Background Stroke is a common neurological disorder that leads to severe functional impairments and reduced quality of life. Early bedside rehabilitation plays a crucial role in recovery, but research on its effectiveness is limited.Methods This study aimed to assess the impact of early bedside rehabilitation on stroke patients. A total of 150 patients were randomly assigned to an intervention group (n = 75) and a control group (n = 75). The intervention group received physical therapy, occupational therapy, and speech therapy within 48 h of stroke onset. The control group received standard care. Assessments included activities of daily living (ADL), motor function, cognitive function, and quality of life.Results The intervention group showed significantly better outcomes in ADL, motor function, cognitive function, and quality of life compared to the control group. The intervention group had higher Barthel Index, modified Rankin Scale, Fugl-Meyer Assessment, Montreal Cognitive Assessment (MoCA), and Stroke-Specific Quality of Life Scale (SS-QOL) scores (p < 0.001).Conclusion Early bedside rehabilitation in the neurology department significantly improves stroke patients’ recovery, including ADL, motor function, cognitive function, and quality of life. These findings highlight the importance of early rehabilitation and a comprehensive, multidisciplinary approach in stroke care, which can improve recovery outcomes and overall quality of care.
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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) | 0.001 | 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".