Common Carotid Flow Velocity is Associated with Cognition in Older Adults
Bibliographic record
Abstract
AIMS: To assess the relationship between carotid flow velocity and cognitive impairment in patients with mild-moderate (<50%) carotid artery disease. METHODS: We studied 407 participants with available carotid ultrasound and cognitive measures. We related peak systolic velocity (PSV) and end diastolic velocity (EDV) of internal carotid artery (ICA) and common carotid artery (CCA) and intimal medial thickness (IMT) to Mini Mental State Examination (MMSE), Clock Draw Test (CDT), Activities of Daily Living Scale (ADL)and Montreal Cognitive Assessment (MoCA). RESULTS: EDV of CCA was significantly different in higher and lower MoCA (MMSE) groups. Multiple regression analysis demonstrated that lower EDV was significantly associated with lower MoCA (+0.459 per standard deviation (SD), p<0. 01 for the left; +0.539 per SD, p<0. 01 for the right) and CDT (odds ratio (OR) 0.093, p< 0.05 for the left; OR) 0.120, p<0. 01 for the right) scores. PSV of left CCA (-0.205 per SD, p<0.05) and IMT (+42.536 per SD, p< 0.001) were associated with ADL. PSV of right CCA was associated with MMSE (+0.081 per SD, p<0.001). No significant relationship between ICA flow velocity and cognitive performance was observed. CONCLUSIONS: Our preliminary data show that common carotid artery flow velocity was associated with cognitive performance.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".