Exploring the Link Between Cerebral Perfusion during Sit-to-Stand and Cognitive Function in People After Stroke
Bibliographic record
Abstract
Introduction.People post-stroke have an increased risk of cognitive impairment, potentially linked to cerebral blood flow (CBF) dysregulation.While CBF impairment is associated with dementia, its response to physiologic challenges like sit-to-stand transitions and its relationship to cognitive function remains unexplored in chronic stroke.We hypothesized that people poststroke would show a decreased CBF response during a sit-to-stand transition and would show a positive correlation between CBF during sit-to-stand and cognition.Methods.We conducted a retrospective analysis from existing data.We assessed CBF as the mean middle cerebral artery velocity (MCAv) during sit-to-stand.Montreal Cognitive Assessment (MoCA) assessed cognition.Results.Forty-eight individuals with chronic stroke and 27 age-similar healthy adults were included.Participants with chronic stroke showed significantly lower MoCA scores than healthy controls (p <0.0001).No between group differences existed for the drop or minimum value in MCAv after standing.Controls showed a moderate positive correlation between minimum MCAv and MoCA (p = 0.013), while individuals with chronic stroke showed no correlation between minimum MCAv and MoCA. Conclusions.In healthy adults, a moderate positive correlation was observed between minimum MCAv and MoCA, suggesting a potential link between cerebral blood flow regulation and cognition.However, this relationship was absent in individuals with chronic stroke, indicating that cerebrovascular responses to orthostatic stress may not contribute to cognitive function in this population.These findings highlight potential differences in cerebrovascular regulation poststroke and its relevance to cognitive impairment.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".