Cognitive Performance in Asymptomatic Patients With Advanced Carotid Disease
Bibliographic record
Abstract
OBJECTIVE: : In the absence of stroke or transient ischemic attack, patients with advanced carotid stenosis or occlusion (ICAs/o) are considered asymptomatic, yet they are prone to mostly subtle cognitive impairment. BACKGROUND: : The Mini-Mental State Examination (MMSE) often fails to detect mild cognitive impairment. The Montreal Cognitive Assessment (MoCA) is more sensitive in recognizing such changes. METHODS: : Scores on the MoCA and MMSE were compared in 70 asymptomatic patients with ICAs/o and 70 controls matched for demographic variables and vascular risk factors. RESULTS: : MMSE scores fell mostly within the normal range in both patients and controls. Differences were significant for total MoCA scores (P<0.001). Patients with ICAs/o performed worse on visuospatial and executive function (P=0.018), abstraction (P<0.001), and delayed recall (P<0.001). Lower MoCA scores were associated with diabetes (odds ratio=6.41; 95% confidence interval, 1.277-32.220; P=0.024) and older age (odds ratio=0.86; 95% confidence interval, 0.780-0.956; P=0.004). Patients with diabetes performed worse on delayed recall (P<0.001), and patients with hypertension were worse on the MoCA naming subtest (P=0.04). CONCLUSIONS: : The MoCA successfully identified reduced cognitive status in patients with ICAs/o. The MoCA subtest scores revealed a pattern of cognitive impairment similar to that documented in other studies using more extensive neuropsychological tests. MoCA could be used as part of the clinical evaluation of patients with ICAs/o.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".