Cognitive outcome after carotid artery stenting in patients with cerebral ischemia.
Bibliographic record
Abstract
Background: Chronic cerebral hypoperfusion may lead to cognitive decline in patients with chronic stenosis or occlusion of the cervicocerebral vessels, and the effects of stent placement on neurocognitive function have been controversial. Methods: A series of 105 patients, who were identified with arterial stenosis or occlusion and abnormal cerebral perfusion in the area of the stenotic vessel based on computed tomography (CT) angiography or magnetic resonance angiography (MRA) and magnetic resonance (MR) or CT perfusion were selected to investigate. A battery of neuropsychological tests, including the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), were assessed 1 week before and 90 days after the cervicocerebral vessel stenting, or conventional angiography without intervention. Results: Patients were subdivided into 2 groups (n=83 carotid artery stents [CAS]); no intervention (n=22) serving as a control group. Significant improvements in MMSE (CAS 23.9 [4.9] vs 25.4 [4.7] for before vs after the procedures; P<0.01) and in MoCA (CAS 19.9 [6.4] vs 22.0 [6.0] for before vs after the procedures; P<0.01) were observed in the intervention groups. Orientation, delayed recall and abstraction were also improved. Conclusions: Successful cervicocerebral vessel stenting improve cognitive function in patients with cervicocerebral vessels stenosis or occlusion with a corresponding perfusion abnormality.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".