GP.01 The relationship between carotid stenosis, cerebral cortex thickness and cognitive function in community dwelling older individuals
Bibliographic record
Abstract
Background: Carotid atherosclerosis is a significant risk factor for stroke and has been associated with cognitive decline and dementia. Methods: We assessed 554 community-dwelling subjects from the Lothian Birth Cohort of 1936 (LBC1936) who underwent brain MRI and carotid Doppler ultrasound studies at age 73 years. The relationship between carotid stenosis and cerebral cortical thickness was examined cross-sectionally, controlling for gender, extensive vascular risk factors (VRFs), and IQ at age 11 (IQ-11). The association between carotid stenosis and a composite measure of fluid intelligence was also investigated. Results: A widespread negative association was identified between carotid stenosis and cerebral cortical thickness at age 73 years, independent of the side of carotid stenosis, other carotid measures, VRFs, or IQ-11. This association increased in an almost dose-response relationship from mild to severe degrees of carotid stenosis. A negative association was also noted between carotid stenosis and fluid intelligence, which appeared partly mediated by carotid stenosis-related thinning of the cerebral cortex. Conclusions: Carotid stenosis is associated with thinner cerebral cortex and lower fluid cognitive abilities at age 73. The findings suggest that carotid stenosis represents a marker of vascular processes that accelerate cortical aging with a negative impact on cognition, independent of measurable VRFs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".