Effects of carotid artery stenting on cognitive function in patients with mild cognitive impairment and carotid stenosis
Bibliographic record
Abstract
Carotid stenosis is known to be an independent risk factor in the transformation process of mild cognitive impairment (MCI) to dementia and is treated by carotid artery stenting (CAS); however, the effects of CAS on cognitive function are unclear. In this study, 240 patients were prospectively assigned to a CAS or control group according to patient preference and underwent detailed neuropsychological examinations (NPEs) before and 6 months after treatment. Cerebral perfusion was assessed with computed tomography perfusion (CTP). Among the 240 patients included in the study, 208 patients completed NPEs at baseline and 6 months after therapy. The patients in the two groups did not differ with regard to baseline characteristics, educational level, vascular risk factors (VRFs) and NPEs prior to therapy. Significant improvements in the Mini-Mental State Examination (MMSE; before, 24.6±1.7 vs. after, 24.8±1.9; P=0.016), Montreal Cognitive Assessment (MOCA; before, 23.7±1.7 vs. after, 24.1±2.0; P=0.006), Fuld Object Memory Evaluation (FOME; before, 13.8±2.2 vs. after, 14.0±2.3; P=0.031) and Wechsler Adult Intelligence Scale-digital span (WAIS-DS; before, 6.7±2.1 vs. after, 6.9±2.3; P=0.040) were observed in the CAS group; however, improvements were not observed in the control group. Of the 84 patients in the CAS group who received CTP follow-up, 72 (86%) presented improvements in ipsilateral brain perfusion 6 months after the procedure; however, no improvement was observed in the control group. Close correlations were identified between the change in perfusion and the change in MMSE (r=0.575) and MOCA (r=0.574). CAS improves global cognitive function in patients with carotid stenosis and MCI and the improvement of cognition is closely related to the improvement of cerebral perfusion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".