The Triad of Post-Stroke Fatigue, Cognition, and Motor Performance: A Study in Chronic Stroke Survivors
Bibliographic record
Abstract
Background: In chronic stroke survivors, post-stroke fatigue (PSF) is a common but underdiagnosed illness that has a major impact on recovery, motor function, and cognitive function. Comprehending these associations is crucial for focused rehabilitation tactics. Methods: 41 chronic stroke survivors between the ages of 46 and 65 participated in a cross-sectional study. The Montreal Cognitive Assessment (MoCA), Fugl-Meyer Assessment (FMA), the 6-Minute Walk Test (6MWT), and the Fatigue Scale for Motor and Cognitive Functions (FSMC) were among the tests used. The PHQ-9 was used to screen for depression. For data analysis, Pearson's correlation was used. Result: The findings showed that fatigue was significantly correlated negatively with walking endurance (r = -0.428, p = 0.000128), upper limb motor performance (r = -0.4389, p = 0.000082), and cognitive function (r = -0.5973, p < 0.00001). Compared to motor exhaustion, cognitive fatigue was more strongly associated with these outcomes. Discussion: According to the results, cognitive fatigue has a significant influence on both physical recovery and cognitive function in chronic stroke survivors. To enhance functional outcomes, effective rehabilitation should incorporate cognitive retraining, endurance-building exercises, and fatigue management techniques. Conclusion: Cognitive function, motor function, and endurance are all greatly impacted by post-stroke fatigue. Chronic stroke survivors' quality of life and rate of recovery can be improved by including fatigue management techniques into rehabilitation programs. Key words: Chronic Stroke, Cognitive Impairment, Motor Performance, Post-Stroke Fatigue, Stroke Rehabilitation.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".