The adverse effects of reduced cerebral perfusion on cognition and brain structure in older adults with cardiovascular disease
Bibliographic record
Abstract
BACKGROUND: It is well established that aging and vascular processes interact to disrupt cerebral hemodynamics in older adults. However, the independent effects of cerebral perfusion on neurocognitive function among older adults remain poorly understood. We examined the associations among cerebral perfusion, cognitive function, and brain structure in older adults with varying degrees of vascular disease using perfusion magnetic resonance imaging (MRI) arterial spin labeling (ASL). MATERIALS AND METHODS: 52 older adults underwent neuroimaging and were administered the Mini Mental State Examination (MMSE), the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and measures of attention/executive function. ASL and T1-weighted MRI were used to quantify total brain perfusion, total brain volume (TBV), and cortical thickness. RESULTS: Regression analyses showed reduced total brain perfusion was associated with poorer performance on the MMSE, RBANS total index, immediate and delayed memory composites, and Trail Making Test B. Reduced frontal lobe perfusion was associated with worse executive and memory function. A similar pattern emerged between temporal lobe perfusion and immediate memory. Regression analyses revealed that decreased total brain perfusion was associated with smaller TBV and mean cortical thickness. Regional effects of reduced total cerebral perfusion were found on temporal and parietal lobe volumes and frontal and temporal cortical thickness. DISCUSSION: Reduced cerebral perfusion is independently associated with poorer cognition, smaller TBV, and reduced cortical thickness in older adults. CONCLUSION: Prospective studies are needed to clarify patterns of cognitive decline and brain atrophy associated with cerebral hypoperfusion.
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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 | 0.000 | 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 | 0.000 |
| 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".