Abstract W P156: Arterial Stiffness in Older Adults With and Without Stroke
Bibliographic record
Abstract
Introduction: Silent cerebrovascular infarcts resulting from vascular disease can manifest as a decline in cognitive function. These silent events are also associated with increased risk of clinically overt stroke. Arterial stiffness is a marker that represents atherosclerotic progression and is a predictor of cardiovascular events and mortality. This study examined the relationship between arterial stiffness and cognitive impairment between adults aged 50-80 years old with and without stroke. Hypothesis: We hypothesized that elevated arterial stiffness would be observed in individuals with stroke, and also be associated with increased cognitive impairment across all participants. Methods: Cognition was assessed using the Montreal Cognitive Assessment (MoCA). Arterial stiffness was quantified using carotid-femoral pulse wave velocity (cfPWV, in m/s), calculated as cfPWV=D/Δt, where D was the distance measured between arterial sites and Δt was the pulse transit time. Higher values represent increased stiffness, and values >10 m/s are associated with increased risk for cardiovascular events. Results: Twenty-five participants were assessed: 11 participants 4.7±2.4 years post-stroke and 14 older adults without stroke. The non-stroke group was older (73.1±3.9 vs. 65.2±9.4 years, P=0.009), while the stroke group had lower MoCA scores (21.2±3.2 vs. 24.4±2.8, P=0.01). There were no between-group differences in cfPWV (stroke 9.4 m/s vs. older adults 9.9 m/s, P=0.49), when controlling for age and MoCA scores. In backward regression analysis, age explained 21% of the variance of cfPWV (P=0.03), while MoCA was not a contributor. Conclusions: In conclusion, these results suggest that age is a significant correlate of arterial stiffness, regardless of the presence of stroke or cognitive impairment. Ongoing work will examine whether stroke history also contributes to arterial stiffness when groups are matched for age.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".