Regional White Matter Hyperintensities Relate to Specific Cognitive Abilities in Older Adults Without Dementia
Bibliographic record
Abstract
INTRODUCTION: White matter hyperintensities (WMHs) are magnetic resonance imaging markers of small vessel cerebrovascular disease that are associated with cognitive decline and clinical Alzheimer disease. Previous studies have often focused on global or total WMH; less is known about associations of regional WMHs and cognitive abilities among older adults without dementia. METHODS: A total of 610 older adults with normal cognition (n=302) or mild cognitive impairment (n=308) from the Alzheimer's Disease Neuroimaging Initiative underwent neuropsychological testing and magnetic resonance imaging. Linear regression models examined associations between regional WMH volumes and cognition, adjusting for age, sex, education, apolipoprotein E ε4 allele frequency, and pulse pressure. RESULTS: Among all participants, greater regional WMH volume in all lobes was associated with poorer performance on memory and speed/executive functioning. Among participants with normal cognition, greater temporal and occipital WMH volumes were associated with poorer memory, whereas no regional WMH volumes were associated with speed/executive function. DISCUSSION: Results show that greater regional WMH volume relates to poorer cognitive functioning-even among those with normal cognition. Together with results from previous studies, our findings raise the possibility that WMH may be a useful therapeutic target and/or important effect modifier in treatment or prevention dementia trials.
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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 | 0.002 |
| 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 | 0.000 | 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".