P1‐256: CAROTID ATHEROSCLEROSIS AND THE SUBSEQUENT COGNITIVE FUNCTION: A 10‐YEAR LONGITUDINAL FOLLOW‐UP
Bibliographic record
Abstract
Evidences have suggested vascular diseases contributed to cognitive impairment. However, the details of association between them are still needed to illustrated. A longitudinal study can provide more convinced results. Participants from a community cohort of 1813 subjects. Among them, 298 subjects have completed a 10-year follow-up. The 10-year follow-up included cognitive function assessment using Montreal Cognitive Assessment (MoCA). We investigate the association between baseline carotid atherosclerosis indicators (carotid intima-media thickness, carotid stiffness, and carotid plaque) and cognitive function at 10-year follow-up. In total, 298 subjects with mean age of 62.8 (8.5) years and 46.3% male were enrolled. In controlled analysis, the lowest quartile of MoCA total score were associated with carotid plaque (p=0.04); the lowest quartile of MoCA executive index score were associated with carotid stiffness (p=0.029 for pressure-strain elastic modulus, p=0.021 for beta index, p=0.006 for pulse wave velocity); the lowest quartile of MoCA visuospatial index score wre associated with carotid plaque (p=0.043); and the lowest quartile of MoCA language index score were associated with carotid stiffness (p=0.016 for pressure-strain elastic modulus, p=0.036 for beta index, p=0.006 for pulse wave velocity). Findings from this study suggested that carotid atherosclerosis were correlated with cognitive function at 10-year follow-up. Different carotid atherosclerosis index contributed to executive, visuospatial and language domains of 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".