Carotid Atherosclerosis and Cognitive Function in a General Population Aged 63-65 Years: Data from the Akershus Cardiac Examination (ACE) 1950 Study
Bibliographic record
Abstract
BACKGROUND: Studies on the relationship between carotid atherosclerosis and cognitive function in subjects from the general population are few and results have been inconsistent. OBJECTIVE: We aimed to investigate the association between carotid atherosclerotic burden and cognitive function in a cross-sectional analysis of a population-based cohort aged 63-65 years. METHODS: All habitants born in 1950 from Akershus County, Norway were invited to participate. A linear regression model was used to assess the association between carotid atherosclerosis and cognitive function. We used carotid plaque score as a measure of carotid atherosclerotic burden and the Montreal Cognitive Assessment (MoCA) for global cognitive function. RESULTS: We analyzed 3,413 individuals aged 63-65 with mean MoCA score 25.3±2.9 and 87% visible carotid plaques. We found a negative correlation between carotid plaque score and MoCA score (r = -0.14, p < 0.001), but this association was lost in multivariable analysis. In contrast, diameter or area of the thickest plaque was independently associated with MoCA score. Lower educational level, male sex, current smoking, and diabetes were also associated with lower MoCA score in multivariable analysis. CONCLUSION: Carotid atherosclerotic burden was, unlike other measures of advanced carotid atherosclerosis, not independently associated with global cognitive function.
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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 | 0.000 |
| 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".