Abstract WP226: Topography of Dilated Perivascular Spaces in Patients with Markers of Cerebral Amyloid Angiopathy and Hypertensive Vasculopathy
Bibliographic record
Abstract
Objectives: To investigate whether the topography of dilated perivascular spaces (DPVS) corresponds with markers of particular small vessel diseases such as cerebral amyloid angiopathy (CAA) and hypertensive vasculopathy. Methods: Patients were recruited from an ongoing single-center prospective longitudinal cohort study of patients evaluated in a memory clinic. All patients underwent structural, high-resolution MRI, and had a clinical assessment performed within 1 year of scan. DPVS were rated in basal ganglia (BG-DPVS) and white matter (WM-DPVS) on T1 sequences, using an established 4-point semi-quantitative score. DPVS degree was classified as high (score >2) or low (score ≤ 2). Independent risk factors for high degree of BG-DPVS and WM-DPVS were investigated. Results: Eighty-nine patients were included (mean age 72.7 ± 9.9 years, 57% female). High degree of WM-DPVS was more frequent than low degree in patients with presence of strictly lobar MB (45.5% versus 28.4% of subjects). High BG-DPVS degree was associated with older age, hypertension, and higher WMH volumes. In multivariate analysis increased lobar MB count was an independent predictor of high degree of WM-DPVS [OR 1.53 (95% CI 1.06-2.21), p=0.02]. By contrast, hypertension was an independent predictor of high degree of BG-DPVS [OR 9.4 (95% (CI 1-85.2), p=0.04]. Conclusions: The associations of WM-DPVS with lobar MB and BG-DPVS with hypertension raise the possibility that the distribution of DPVS may indicate the presence of underlying small vessel diseases such as CAA and HV, in patients with cognitive impairment.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".