Virchow-Robin Spaces: Correlations with Polysomnography-Derived Sleep Parameters
Bibliographic record
Abstract
STUDY OBJECTIVES: To test the hypothesis that enlarged Virchow-Robin space volumes (VRS) are associated with objective measures of poor quality sleep. DESIGN: Retrospective cross-sectional study. SETTING: Sunnybrook Health Sciences Centre. PATIENTS: Twenty-six patients being evaluated for cerebrovascular disease were assessed using polysomnography and high-resolution structural magnetic resonance imaging. MEASUREMENTS AND RESULTS: Regionalized VRS were quantified from three-dimensional high-resolution magnetic resonance imaging and correlated with measures of polysomnography-derived sleep parameters while controlling for age, stroke volume, body mass index, systolic blood pressure, and ventricular cerebrospinal fluid volume. Sleep efficiency was negatively correlated with total VRS (rho = -0.47, P = 0.03) and basal ganglia VRS (rho = -0.54, P = 0.01), whereas wake after sleep onset was positively correlated with basal ganglia VRS (rho = 0.52, P = 0.02). Furthermore, VRS in the basal ganglia were negatively correlated with duration of N3 (rho = -0.53, P = 0.01). CONCLUSIONS: These preliminary results suggest that sleep may play a role in perivascular clearance in ischemic brain disease, and invite future research into the potential relevance of Virchow-Robin spaces as an imaging biomarker for nocturnal metabolite clearance.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".