Cognitive decline and cerebral vasoreactivity in asymptomatic patients with severe internal carotid artery stenosis
Bibliographic record
Abstract
Abstract Background The aim of the study was to correlate cognitive decline and cerebral vasoreactivity in 150 asymptomatic right‐handed patients with severe ≥70 % unilateral internal carotid artery (ICA) stenosis and to evaluate the role of intracranial collateral circulation during cognitive testing. Methods Cognitive assessment was performed by means of Montreal Cognitive Assessment (MoCA) and Mini Mental State Exam (MMSE) scales. Cerebrovascular reactivity (CVR) and intracranial collateral circulation were evaluated by means of breath holding index (BHI) and transcranial color Doppler (TCD) sonography. Results The results were compared with 150 right‐handed controls matched for demographic variables and vascular risk factors. Patients with severe unilateral ICA stenosis had MMSE scores within a normal range, but MoCA scores were lower than normal. By examining the side of the observed stenosis, it has been noted that patients with left‐sided ICA stenosis had lower MoCA scores in categories of language and episodic memory performance, while patients with right‐sided ICA stenosis had lower MoCA scores in a category of visual–spatial skills. All patients had BHI values lower than normal. Subjects with a single intracranial collateral artery recruited had slightly better cognitive results than the patients with two or more collateral arteries activated. Conclusions Results of the study showed that altered cerebrovascular reactivity and cerebral hypoperfusion might be responsible for the reduction of specific cognitive functions ipsilateral to the ICA stenosis, therefore BHI and MoCA might be useful tools when screening for cognitive decline in asymptomatic patients with severe ICA stenosis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".