The impact of asymptomatic carotid stenosis on cognition
Bibliographic record
Abstract
Aims: Asymptomatic carotid stenosis (ACS), characterized by the narrowing of carotid arteries without evident symptoms, has been increasingly associated with cognitive decline, particularly in memory and executive functions. This study investigates the cognitive implications of ACS by evaluating cognitive performance using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). Methods: This retrospective study included 20 ACS patients and 15 matched healthy controls. Participants were recorded for cognitive status, age, gender, and educational background to ensure group comparability. MMSE and MoCA were used for cognitive assessment. Results: The findings revealed that while MMSE scores did not differ significantly between groups, MoCA scores were notably lower in ACS patients (19.85 ± 4.68) compared to controls (23.07±3.01, p=0.027), suggesting pronounced cognitive deficits in domains such as visuospatial ability and delayed recall. These results align with existing literature indicating that ACS may impair cerebral blood flow and disrupt connectivity in key neural networks, thereby contributing to cognitive impairment. Additionally, while the ACS group tended to be older and have fewer years of formal education, these factors did not significantly confound the observed cognitive differences (p<0.05). Conclusion: Our results underscore the importance of routine cognitive evaluations in patients with ACS, as traditional assessments may underestimate their impact on brain health. Future research should explore the efficacy of interventions such as carotid endarterectomy or stenting in mitigating cognitive decline associated with ACS. These findings advocate for a holistic approach to managing ACS, integrating cognitive assessments alongside traditional cardiovascular risk evaluations to enhance patient outcomes and quality of life.
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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 | 0.003 |
| 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".