Vascular Contributions to Neurodegeneration: Protocol of the COMPASS-ND Study
Bibliographic record
Abstract
OBJECTIVE: To describe the neuroimaging and other methods for assessing vascular contributions to neurodegeneration in the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) study, a Canadian multi-center, prospective longitudinal cohort study, including reliability and feasibility in the first 200 participants. METHODS: COMPASS-ND includes persons with Alzheimer's disease (AD; n = 150), Parkinson's disease (PD) and Lewy body dementias (LBDs) (200), mixed dementia (200), mild cognitive impairment (MCI; 400), subcortical ischemic vascular MCI (V-MCI; 200), subjective cognitive impairment (SCI; 300), and cognitively intact elderly controls (660). Magnetic resonance imaging (MRI) was acquired according to the validated Canadian Dementia Imaging Protocol and visually reviewed by either of two experienced readers blinded to clinical characteristics. Other relevant assessments include history of vascular disease and risk factors, blood pressure, height and weight, cholesterol, glucose, and hemoglobin A1c. RESULTS: Analyzable data were obtained in 197/200 of whom 18 of whom were clinically diagnosed with V-MCI or mixed dementia. The overall prevalence of infarcts was 24.9%, microbleeds was 24.6%, and high white matter hyperintensity (WMH) was 31.0%. MRI evidence of a potential vascular contribution to neurodegeneration was seen in 12.9%-40.0% of participants clinically diagnosed with another condition such as AD. Inter-rater reliability was good to excellent. CONCLUSION: COMPASS-ND will be a useful platform to study vascular brain injury and its association with risk factors, biomarkers, and cognitive and functional decline across multiple age-related neurodegenerative diseases. Initial findings show that MRI-defined vascular brain injury is common in all cognitive syndromes and is under-recognized clinically.
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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 | 0.024 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.007 |
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".