An Integrated Analysis of Risk Factors of Cognitive Impairment in Patients with Severe Carotid Artery Stenosis.
Bibliographic record
Abstract
OBJECTIVE: To investigate cognitive dysfunction in patients with carotid artery stenosis (CAS) and potential risk factors related to cognitive-especially memory-dysfunction. METHODS: Forty-seven patients with carotid artery stenosis were recruited into our study cohort. The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were adopted to assess cognitive function, the Wechsler Memory Scale (WMS) to assess memory function, high-resolution MRI and enhanced ultrasound to evaluate carotid plaques, and computed tomography perfusion (CTP) imaging to evaluate intracranial blood perfusion. Single-factor analysis and multiple-factor regression analysis were used to analyze potential risk factors of cognitive impairment. RESULTS: Mini-Mental State Examination test results showed that 22 patients had cognitive impairment, and MoCA test results showed that 10 patients had cognitive impairment. Analysis of various risk factors indicated that the average memory quotient of female patients was higher than that of males (P = 0.024). The cognitive and memory performance of those with an educational background above high school were significantly better than those of participants with high school or lower (P = 0.045). Patients with abnormal intracranial perfusion performed worse on the MMSE test (P = 0.024), and their WMS scores were significantly lower (P = 0.007). The MMSE scores and the memory quotients were significantly lower in patients with a history of cerebral infarction (MMSE, P = 0.047, memory quotient score, P = 0.018). CONCLUSION: A history of cerebral infarction and abnormal cerebral perfusion are associated with decline in overall cognitive function and memory in patients with carotid stenosis. Being female and having an educational background above high school may be protective factors in the development of cognitive dysfunction.
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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 | 0.001 | 0.001 |
| 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".