Montreal cognitive assessment and analysis of related factors for cognitive impairment in patients with chronic cerebral circulation insufficiency
Bibliographic record
Abstract
BACKGROUND: Chronic cerebral circulation insufficiency (CCCI) refers to cerebral dysfunctions that lead to cerebral vascular pathological changes. Our aim is to identify factors related to cognitive impairment in CCCI. METHODS: CCCI patients (n=102) were assessed with the Montreal cognitive assessment (MoCA) to analyze cognitive impairment. Patients were divided into two groups according to MoCA scores: (1) cognitive dysfunction and (2) normal cognitive function. We compared the clinical information with univariate and multivariate logistic regression analyses and identified major risk factors related to cognitive impairment in CCCI. RESULTS: Age (p=0.007, OR=3.768, χ2=7.173), leukoaraiosis (p=0.002, OR=6.231, χ2=9.478), a history of hypertension (p=0.021, OR=3.078, χ2=5.307), a history of hyperlipidemia (p=0.016, OR=3.429, χ2=5.795), and the number of vascular risk factors (p=0.019, χ2=9.921) were related to cognitive impairment by univariate analysis. Age (p=0.070, OR=2.689, 95% CI=0.923±7.837) and leukoaraiosis (p=0.012, OR=4.531, 95% CI=1.401±14.667) were significant by multivariate logistic regression analysis. Age (r=-0.585, p<0.01) had a marked negative correlation with MoCA scores. There were significant differences in the MoCA subscale scores, including visuospatial and executive capacity (p<0.01), attention and calculation (p<0.01), and delayed recall (p<0.01), in patients with different degrees of leukoaraiosis. Patients with CCCI had a higher incidence of cognitive impairment (78.4%). CONCLUSIONS: Changes in visuospatial and executive capacity, delayed recall, and language function represent cognitive manifestations in CCCI. Age and leukoaraiosis have the strongest effects on cognitive impairment morbidity and can aggravate cognitive impairment.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".