Cross-sectional and longitudinal differences in peak skeletonized white matter mean diffusivity in cerebral amyloid angiopathy
Bibliographic record
Abstract
OBJECTIVES: To test the hypotheses that peak skeletonized mean diffusivity (PSMD), a measure of cerebral white matter microstructural disruption, is 1) increased in patients with cerebral amyloid angiopathy (CAA) compared to normal control (NC), mild cognitive impairment (MCI), and Alzheimer's disease (AD); 2) associated with neuropsychological test performance among CAA patients; and 3) increased more quickly over one year in CAA than in AD, MCI, and NC. METHODS: Ninety-two participants provided a medical history, completed a neuropsychological assessment, and had a magnetic resonance (MR) exam including diffusion tensor imaging (DTI) from which PSMD was calculated. A 75-minute neuropsychological test battery was used to derive domain scores for memory, executive function, and processing speed. Multivariable analyses controlling for age and sex (and education, for cognitive outcomes) were used to test the study hypotheses. RESULTS: /s) groups (p < .01). Among CAA patients, higher PSMD was associated with slower processing speed (estimated -0.22 standard deviation (SD) change in processing speed z score per SD increase in PSMD, 95% CI -0.42 to -0.03, p = .03), higher WMH volume [β = 0.74, CI 0.48 to 1.00], and higher CAA SVD score [β = 0.68, CI 0.24 to 1.21] but was not associated with MMSE, executive function, memory, CMB count, or cortical thickness. PSMD increased over 1-year in all groups (p < .01) but without rate differences between groups (p = .66). CONCLUSIONS: PSMD, a simple marker of diffuse global white matter heterogeneity, is increased in CAA. Our findings further support a role for white matter disruption in causing cognitive impairment in CAA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.002 |
| 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 teacher head, 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".