Abstract WMP52: Markers Of Endothelial Glycocalyx Damage In Patients Withvascular Cognitive Impairment Associated With Cerebral Small Vessel Disease
Bibliographic record
Abstract
Introduction: Cerebral small vessel disease (cSVD) involves a myriad of pathogenic mechanisms affecting small vessels of the brain, leading to a significant impact on motor and cognitive functions, and it is the main cause of Vascular cognitive impairment (VCI). The endothelial glycocalyx (EG), the layer lining the vascular endothelium, has a pivotal player in maintaining the proper function of neurovascular unit, and its degradation may be involved in VCI due to cSVD. Objectives: to investigate the relationship between markers of EG damage and VCI related to cSVD. Methods: Cross-sectional study based on clinical data and serum samples for the quantification of EG damage markers (syndecan-1, hyaluran) of VCI related to cSVD patients and of a control group derived from a dataset of healthy workers from the same institution. We used an automatic logarithm for segmentation and volumetric evaluation of white matter lesions on brain MRI of the patients. Logistic regression models and c-statistics were used to identify the independent variables related to VCI and investigate the accuracy of syndecan-1 to detect VCI. We studied the association of thebiomarkers and MoCA scores, index of independence in activities of daily living and whitematter lesion burden respectively. Results: Between July 2019 and March 2020, we studied 22 patients with VCI associated with cSVD and compared them with a dataset of 22 healthy workers from the same institution. Patients with VCI were older, had a higher prevalence of diabetesmellitus and hypertension, had a worse index of independence for daily activities, and higherlevels of syndecan-1 (78,4 vs 24; p < 0,01). There was no difference in hyaluran levels between both groups. In multivariate analysis, only age (OR 1,35;CI 1,04 - 1,76; p = 0,02) and syndecan-1 levels (OR 1,08;CI 1,01 - 1,15;p = 0,01) related to VCI. The ROC curve ofsyndecan-1 levels to predict VCI had a area under de curve of 0,78 (CI 0,64 - 0,92) and there was a correlation between syndecan-1 levels and MoCA scores (rho = - 0,34;p = 0,02). There were no correlations between syndecan-1 and hyaluran levels and index of independence and white matter lesion burden respectively. Conclusions: Syndecan-1, but not hyaluran, is a potential biomarker for VCI associated with cSVD.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.003 | 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".