Do cerebral microbleeds affect cognition in patients with symptomatic small vessel disease?
Bibliographic record
Abstract
Abstract Background Dementia and cognitive impairment are becoming increasingly a major health problem, pronounced by increased life expectancy. Cerebral small vessel disease (cSVD) is among the major causes of cognitive deterioration, yet cerebral microbleeds (CMBs) which are a common association of cSVD are still not sure to be related to cognition. Aim of the study The study aims to determine whether the number and localization of CMBs correlate with cognition in patients with symptomatic small vessel disease (SVD), according to Montreal Cognitive Assessment (MoCA) test. Subjects and methods This cross-sectional study included 85 Egyptian patients with symptomatic SVD, from the neuropsychiatry clinic of the Main Suez Hospital in Suez City, in the period between February 2017 and February 2018. Subjects were classified according to CMB presence into CMB-positive and CMB-negative groups. Both groups are assessed using MRI imaging and MoCA test for cognitive function. Results In our study, CMBs recorded a high prevalence rate of SVD patients. Subjects with MBs were mainly males and significantly older, with higher white matter lesion volume and more lacunar infarcts. MoCA test detected significant impairment in visuospatial/executive function, attention, and total scores in CMB-positive group. Both frontal and parietal MBs showed independent association with visuospatial/executive impairment. Deep MBs in the basal ganglia were proved to be independent risk factor for attention affection. Conclusion Number and localization of MBs proved to be important in determining cognitive consequences. The relations with cognitive performance were mainly driven by frontal, parietal, and deep located MBs in the basal ganglia. Memory affection in frontal MBs was dependent to severe white matter intensities and lacunes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".