Microbleeds and Silent Brain Infarctions Are Differently Associated with Cognitive Dysfunction in Patients with Advanced Periventricular Leukoaraiosis
Bibliographic record
Abstract
BACKGROUND: Leukoaraiosis, microbleeds, and silent brain infarctions are phenotypes of small vessel disease. Leukoaraiosis is the most prevalent, and advanced periventricular leukoaraiosis is regarded as a strong predictor of cognitive dysfunction. Microbleeds and silent brain infarctions sometimes coexist with leukoaraiosis. This study aims to analyze the effects of microbleeds and silent brain infarctions on cognitive function of patients with advanced periventricular leukoaraiosis. METHODS: 227 patients with advanced periventricular leukoaraiosis were divided into control, MB, SBI, and MB&SBI groups. The presence and locations of microbleeds and silent brain infarctions were evaluated. Mini-Mental State Examination, Montreal Cognitive Assessment, Clock Drawing Test and Verbal Fluency Test were performed. Chi-square test and ANOVA to compare the characteristics of four groups, multiple linear regressions to identify the risk factors for cognitive dysfunction. RESULTS: The scores in all four tests were lower in the MB and MB&SBI groups while only the scores in Clock Drawing Test and Verbal Fluency Test were lower in the SBI group than in the control group. Age and the presence of microbleeds were independent risk factors for the lower scores in all four tests, whereas the presence of silent brain infarctions was the only independent risk factor for the lower scores in Clock Drawing Test and Verbal Fluency Test. Lobar microbleeds had the most significant effect on cognitive function. CONCLUSION: Microbleeds and silent brain infarctions were associated differently with cognitive impairment of patients with advanced periventricular leukoaraiosis. The effect of lobar microbleeds was the most significant.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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 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".