Longitudinal Cognitive Changes in Cerebral Small Vessel Disease
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: White matter hyperintensities (WMHs) are the commonest imaging marker of cerebral small vessel disease (SVD) and a major cause of cognitive decline and vascular dementia. WMHs typically accumulate over time, but recent studies show they can also regress, but potential clinical benefits have received little attention. We examined progressing, stable, and regressing WMH in people with stroke-related SVD and the effect on cognitive outcomes. METHODS: We recruited patients with minor nondisabling ischemic stroke (modified Rankin score ≤2) from stroke services into our prospective longitudinal observational study. Participants underwent cognitive assessment and brain MRI within 3-month poststroke and 1 year later. We gathered information on vascular risk factors, stroke severity, global cognition (Montreal Cognitive Assessment [MoCA]), processing speed and executive functioning (Trail Making Test [TMT] A and B, and the B/A ratio with ratio ≥3 reflecting executive dysfunction), and the Letter Digit Substitution Test. We measured WMH volumes at baseline and 1 year and categorized net WMH volume change into quintiles: Q1 (most regression), Q3 (stable), and Q5 (most progression). We applied repeated-measures linear mixed models to analyze longitudinal WMH and cognitive changes, adjusting for age, sex, premorbid intelligence, stroke severity, disability, white matter structural integrity, and baseline WMH volume. RESULTS: One hundred ninety-eight of 229 participants had WMH volumes available at both time-points. At baseline, the mean age was 67.5 years (SD = 10.9), with 33% female. Mean net WMH volume change per quintile was Q1 -1.79 mL (SD = 1.54), Q2 -0.27 mL (0.20), Q3 0.35 mL (0.18), Q4 1.43 mL (0.48), and Q5 5.31 mL (3.07). MoCA deteriorated the most in participants with most WMH progression (Q5) (estimated β -0.428 [95% CI -0.750 to -0.106]), compared with stable WMH (Q3), with no clear deterioration in those with most WMH regression (Q1). TMT B/A ratio improved in participants with most WMH regression (Q1; -0.385 [-0.758 to -0.012]). DISCUSSION: WMH regression was associated with preserved global cognition and improved executive function, compared with stable WMH, while WMH progression was associated with global cognitive decline. Cognitive benefits of WMH regression suggest that WMH-affected tissue can recover, may explain variance in cognitive outcomes, offer an important intervention target, and should be assessed in other populations and longer follow-up times.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".