Comparative Analysis of Physical Therapy Outcomes in Acute Ischemic and Hemorrhagic Stroke Rehabilitation
Bibliographic record
Abstract
Background: Stroke rehabilitation demands an effective therapeutic approach to enhance functional recovery. This study aims to compare the outcomes of physical therapy in patients with acute ischemic and hemorrhagic stroke using the Motor Relearning Programme (MRP). Methodology: Based on stroke type, confirmed via CT thirty-eight participants were stratified into ischemic & hemorrhagic stroke group. Eligible participants were over 35 years old, had a Glasgow Coma Scale score above 5, and presented with hemiplegia. Exclusion criteria included trauma-induced hemorrhage, cerebellar or brainstem stroke, severe cognitive impairment, or pre-existing disabilities. The participants underwent a standardized four-week physiotherapy regimen based on the MRP, with assessments using the Motor Assessment Scale (MAS) and Functional Independence Measure (FIM) to evaluate the outcomes. Results: These results underscore the significant improvements in the functional outcomes observed in both ischemic and hemorrhagic stroke patients following physical therapy, with hemorrhagic stroke patients showing more substantial gains in both MAS and FIM scores. Conclusion: Our study contributes to a nuanced understanding of stroke rehabilitation, emphasizing that while both ischemic and hemorrhagic stroke patients significantly benefit from structured physical therapy interventions like MRP, the specifics of their recovery processes vary.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".