Decreased Peripheral Endothelial Function is Associated with Mild Cognitive Impairment and Lower Performance on Memory and Language
Bibliographic record
Abstract
Abstract Background The association between cardiovascular risk factors and cognitive decline is known, but the underlying mechanisms remain unclear. We investigated whether peripheral microvascular and endothelial function, measured by pulsatile arterial tonometry (EndoPAT), is associated with cognitive performance and mild cognitive impairment (MCI). Method This study is based on data from 340 participants (150 with MCI, 190 with normal cognition (NC); mean age 64.9 (SD: 7.7) years, 61% female, 48% African American) enrolled in the VAScular ContribUtors to prodromaL AlzheimeR’s disease (VASCULAR) study. Peripheral microvascular function was assessed using EndoPAT (Itamar Inc.), and a reactive hyperemic index (RHI) was derived after a 5‐minute arterial occlusion period and includes a continuous or discrete (dichotomous or tertile) variable. Cognitive assessment and diagnostic categorization performed at the baseline visit included Montreal Cognitive Assessment (MoCA), Boston Naming Test, Hopkins Verbal Learning Test‐Revised (HVLT‐R), and Trail Making Test. Groups were compared with a t‐test and multivariable logistic and linear regression analyses were performed to adjust for demographic and risk factor covariates. Result Participants with MCI had lower RHI, indicative of greater peripheral microvascular and endothelial dysfunction, compared to NC (mean 1.9 (SD: 1.4) vs 2.2 (0.7) AU, p=0.014), which remained significant after adjustment for age, education, sex, race, systolic blood pressure, history of diabetes, hyperlipidemia, and smoking (OR: 3.91 for each 1‐unit change in RHI (95% CI: 1.00, 7.08), p=0.03). When analyzed in tertiles, a lower RHI (<1.75 AU) was also associated with poorer expressive language (Boston Naming Test, p=0.03), and verbal memory performance (HVLT‐R delayed recall, p=0.01; HVLT‐R retention, p=0.02). Executive function (Trail Making Test) and overall cognitive status (MoCA) were not significantly associated with RHI. Conclusion Peripheral microvascular endothelial dysfunction, measured as RHI, was associated with MCI and with lower performances on measures of language and memory. These data highlight the importance of systemic microvascular health in cognitive health. Strategies targeting microvascular endothelial function may need further investigation in cognitive therapeutics.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| 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".