CEREBRAL HYPOPERFUSION DURING OVER-GROUND WALKING IS RELATED TO ARTERIAL STIFFNESS IN OLDER ADULTS
Bibliographic record
Abstract
Posture-related cerebral hypoperfusion is thought to contribute to a large proportion of falls in older adults (OA). Impaired vascular health, which might alter cerebrovascular hemodynamics, can increase the risk of cerebral hypoperfusion. The present study sought to examine posture-related reductions of cerebral tissue oxygenation (tSO2) during a transition to walking and its association to indices of vascular stiffness. Twenty-three OA (87 ± 5yrs) performed postural transitions from supine-to-walking over-ground with a walker. Near infrared spectroscopy measured tSO2 at 3 time points: baseline, the lowest point upon walking (nadir) and between 40s to 60s during walking. Arterial stiffness was assessed from carotid pulse pressure (cPP) and compliance coefficient (cCC). K-cluster-analysis (clustering variables: ΔtSO2 and cPP) divided participants into good- and poor-cerebrovascular-regulation (CVR: n=16 and n=7, respectively). A one-way-ANOVA compared group difference with significance set to p≤0.05. tSO2 at baseline, nadir and walking were significantly lower (p<0.001) in the poor-CVR group versus the good-CVR group during the baseline 61 ± 7% vs. 67 ± 5%, nadir 54 ± 8% vs. 65 ± 5%, and walking 58 ± 10% vs. 66 ± 5%. The poor-CVR group had stiffer carotid arteries compared to the good-CVR group as indicated by higher cPP (71 ± 16mmHg vs. 49 ± 9mmHg, p<0.001) and lower cCC (0.36 ± 0.11mm2/Kpa vs. 0.51 ± 0.14mm2/Kpa, p=0.027). This is the first study to show differences in tSO2 in OAs during a transition to walking. Importantly, this study reveals that OAs with poor-CVR have significantly stiffer vessels and lower cerebral oxygenation during rest, upon standing and during walking, which may be placing them at greater risk of a future fall.
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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".