Small and Large Magnetic Resonance Imaging–Visible Perivascular Spaces in the Basal Ganglia of Parkinson's Disease Patients
Bibliographic record
Abstract
BACKGROUND: Although previously thought to be asymptomatic, recent studies have suggested that magnetic resonance imaging-visible perivascular spaces (PVS) in the basal ganglia (BG-PVS) of patients with Parkinson's disease (PD) may be markers of motor disability and cognitive decline. In addition, a pathogenic and risk profile difference between small (≤3-mm diameter) and large (>3-mm diameter) PVS has been suggested. OBJECTIVE: The aim of this study was to examine associations between quantitative measures of large and small BG-PVS, global cognition, and motor/nonmotor features in a multicenter cohort of patients with PD. METHODS: We performed a cross-sectional study examining the association between large and small BG-PVS with Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Parts I-IV and cognition (Montreal Cognitive Assessment) in 133 patients with PD enrolled in the Ontario Neurodegenerative Disease Research Initiative study. RESULTS: Patients with PD with small BG-PVS demonstrated an association with MDS-UPDRS Parts I (P = 0.008) and II (both P = 0.02), whereas patients with large BG-PVS demonstrated an association with MDS-UPDRS Parts III (P < 0.0001) and IV (P < 0.001). BG-PVS were not correlated with cognition. CONCLUSIONS: Small BG-PVS are associated with motor and nonmotor aspects of experiences in daily living, while large BG-PVS are associated with the motor symptoms and motor complications. © 2022 International Parkinson and Movement Disorder Society.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".