Glymphatic function, deep medullary veins, and cognitive impairment in cerebral small vessel disease: A mediation analysis
Bibliographic record
Abstract
BACKGROUND: The glymphatic system and deep medullary veins (DMV) are closely linked to cognitive impairment in patients with cerebral small vessel disease (CSVD). This study aims to elucidate these complex associations through mediation analysis. METHODS: Patients who underwent multimodal magnetic resonance imaging (MRI) scans and the Montreal Cognitive Assessment (MoCA) were recruited. Glymphatic function was assessed using the diffusion tensor imaging along the perivascular space (DTI-ALPS) index. DMV was identified on susceptibility-weighted imaging (SWI), and a total DMV score was calculated based on segmental continuity and visibility. Regression models were employed to estimate the impact of the DMV score and DTI-ALPS index on cognitive impairment. Mediation analysis was conducted to examine the effect of the DTI-ALPS on DMV score and cognitive function. RESULTS: A total of 152 participants were included, of whom 65 had normal cognitive function and 87 had cognitive impairment. After adjusting for confounding factors, both the DMV score (OR=1.182, 95 % CI: 1.067-1.308, p = 0.005) and DTI-ALPS index (OR=0.496, 95 % CI: 0.306, 0.806, p = 0.005) were independently associated with cognitive impairment. Mediation analysis revealed that the DTI-ALPS index partially mediated the relationship between the DMV score and cognitive impairment, with an indirect effect of 0.040 (95 % CI: 0.011-0.084, p < 0.001). CONCLUSION: Both the DMV score and DTI-ALPS index are independent risk factors for cognitive impairment in patients with CSVD. The DTI-ALPS index significantly and partially mediates the relationship between the DMV score and 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".