Association between cerebral small vessel disease and plasma levels of LDL cholesterol and homocysteine: Implications for cognitive function
Bibliographic record
Abstract
Background: Investigate the correlation between low-density lipoprotein (LDL) cholesterol, homocysteine and cognitive function in patients with cerebral small vessel disease (CSVD). Methods: 240 patients with CSVD confirmed by head MRI in the Department of Neurology from January 2020 to December 2023 were retrospectively included in the study. All the patients had complete blood biochemical examination, and their cognitive function was evaluated by Montreal Cognitive Assessment Scale (MoCA), and after correcting for the factor of years of education, the patients were divided into a group of normal cognition (MoCA 26, 70 patients) and a group of cognitive function (MoCA 26, 70 patients) according to the scores. After correcting for the factor of years of education, the patients were divided into the normal cognitive function group (70 cases with MoCA 26) and the cognitive dysfunction group (170 cases with MoCA <26) according to their scores. The general information of the two groups and the patients' cognitive function characteristics, including visuospatial and executive ability, naming, attention and calculation, language, abstraction, delayed memory, and orientation, were compared, and the independent influences on the occurrence of cognitive dysfunction in patients with CSVD were analyzed by two-category multifactorial logistic regression. Results: Compared with the group with normal cognitive function, the cognitive dysfunction group had lower years of education and higher homocysteine, and the differences were statistically significant (P < 0.05). Compared with the group with normal cognitive functioning, the cognitive dysfunction group had lower MoCA total scores, lower visuospatial and executive ability, naming, attention and calculation, language, abstraction, delayed memory, and orientation scores, and the differences were statistically significant (P < 0.05). Two-category multifactorial logistic regression analysis showed that low-density lipoprotein cholesterol (OR=2.756, 95% CI: 0.673-0.938, P=0.012) and homocysteine (OR=1.859, 95% CI: 1.024-1.324, P=0.016) were the independent factors influencing cognitive dysfunction in CSVD patients. The lower the risk of cognitive impairment in CSVD patients, the higher the plasma LDL cholesterol and homocysteine levels, the higher the risk of cognitive impairment in CSVD patients. Conclusions: Plasma LDL cholesterol and homocysteine levels are associated with and may be predictors of cognitive dysfunction in patients with CSVD.
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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 | 0.002 |
| 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) | 0.000 | 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".