Internal Carotid Artery Stenting: Predictive Screening of Cognitive Function
Bibliographic record
Abstract
Abstract Carotid artery stenting is a common method of stroke prevention. The aim of this work was to examine the relationship between carotid angioplasty with stenting (CAS) of the internal carotid artery (ICA) and cognitive function (CF), based on two years of patient follow-up data (after stenting), including clinical assessment and neuroimaging using magnetic resonance imaging (MRI). This prospective study included 137 patients (64% men) aged 47 to 85 years (with a median age of 66 years), who had undergone CAS for atherosclerotic stenosis. The inclusion criterion was stenosis (symptomatic or asymptomatic) of the internal carotid artery, which was confirmed on ultrasound. The exclusion criteria were patients with stroke (whose neurological deficits included aphasia and/or neglect), severe cognitive and mental disorders, contraindications to antiplatelet drugs and statins, and patients with ICA restenosis after prior carotid endarterectomy. The Montreal Cognitive Assessment (MoCA) Test was used for cognitive function screening before stenting, and 6, 12, and 24 months after the vascular intervention. Diffusion-weighted MRI was used to assess the presence (before CAS and 24 hours after surgery) of focal cerebral changes, specifically intraoperative acute embolic lesions (AEL). Patients with previously identified AEL were re-examined using 3D-FLAIR MRI after 6 months. The number of patients with cognitive impairment, who had scored less than 26 points on the MoCA, was 23/137 (17%) prior to the CAS. When measured 6, 12 and 24 months after stenting, there was no statistically or clinically significant change in cognitive function in 125/137 (91%) patients, cognitive function improved in 12/137 (9%) (3 of whom had reduced CF before stenting), and there were no instances of deterioration. No association was found between asymptomatic foci due to intraoperative AEL, and postoperative cognitive abilities.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".