Flow-Mediated Dilation and Neurocognition
Bibliographic record
Abstract
BACKGROUND: Previous literature indicates that flow-mediated dilation (FMD) is associated with impaired cognition among patients with stroke. The relationship between FMD and cognition in individuals without cerebrovascular disease has yet to be systematically reviewed. METHODS: The literature was searched using MEDLINE. Exclusion criteria were as follows: focus on neurological disease (e.g., stroke), animal studies, no quantitative measure of endothelial function or cognition, newborn studies, articles with no original data, and articles that are irrelevant to the topic of interest. Neurocognitive tests were categorized in the following domains: executive function, memory (general, working, episodic/semantic, verbal, visual), global cognitive function, information processing speed, language, psychomotor speed, and visual-spatial ability. RESULTS: The search yielded 700 articles, of which 10 articles, consisting of 2791 participants, met the criteria for inclusion. Most studies conclude that impaired FMD is associated with poorer neuropsychological functioning, particularly in executive functioning (effect sizes: r = 0.07-0.58) and working memory tasks (effect sizes: r = 0.19-0.39). No association was found between other subdomains of memory and FMD. Visual spatial tasks, information processing speed, language tasks, and global cognition were not associated with FMD overall; however fewer studies examined these domains. CONCLUSIONS: Even in the absence of cerebrovascular disease, there are links between cognition, particularly executive tasks, and vascular function. Public health implications include the potential value of examining FMD as a predictor of cognitive decline, as well as the potential value of improving cognition through pharmacological and behavioral interventions that improve vascular function. Future studies incorporating neuroimaging measures of cerebral blood flow are warranted.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".