Influence of Amyloid-β on Cognitive Decline After Stroke/Transient Ischemic Attack
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: We hypothesized that comorbid amyloid-beta (Aβ) deposition played a key role in long-term cognitive decline in subjects with stroke/transient ischemic attack. METHODS: We recruited 72 subjects with cognitive impairment after stroke/transient ischemic attack to receive Carbon-11-labeled Pittsburgh compound B positron emission tomography. We excluded subjects with known clinical Alzheimer's disease. Those with and without Alzheimer's disease-like Aβ deposition were classified as mixed vascular cognitive impairment (mVCI, n=14) and pure VCI (pVCI, n=58), respectively. We performed Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment to evaluate global cognition and cognitive domains (memory, visuospatial function, language, attention, and executive function) at 3 to 6 months (baseline) and annually for 3 years after the index event. We compared cognitive changes between mVCI and pVCI using linear mixed models and analysis of covariance adjusted for age and education. RESULTS: Over 3 years, there were significant differences between mVCI and pVCI on change of MMSE score over time (group×time interaction, P=0.007). We observed a significant decline on MMSE score (P=0.020) in the mVCI group but not in the pVCI group (P=0.208). The annual rates of decline on MMSE (P=0.023) and Montreal Cognitive Assessment score (P=0.003) were greater in the mVCI group than in the pVCI group. Memory, visuospatial, and executive function domain scores on the Montreal Cognitive Assessment were related to Aβ deposition. CONCLUSIONS: Compared with subjects without Alzheimer's disease-like Aβ deposition, those with Aβ deposition experienced a more severe and rapid cognitive decline over 3 years after stroke/transient ischemic attack. Aβ was associated with changes in multiple cognitive domains.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".