Regional Hypoperfusion Predicts Decline in Everyday Functioning at Three-Year Follow-Up in Older Adults without Dementia
Bibliographic record
Abstract
BACKGROUND: Increasing evidence indicates that cerebrovascular dysfunction may precede cognitive decline in aging and Alzheimer's disease (AD). Reduced cerebral blood flow (CBF) is associated with cognitive impairment in older adults. However, less is known regarding the association between CBF and functional decline, and whether CBF predicts functional decline beyond cerebrovascular and metabolic risk factors. OBJECTIVE: To examine the association between regional CBF and functional decline in nondemented older adults. METHOD: One hundred sixty-six (N = 166) participants without dementia from the Alzheimer's Disease Neuroimaging Initiative underwent neuropsychological testing and neuroimaging. Pulsed arterial spin labeling magnetic resonance imaging was acquired to quantify resting CBF. Everyday functioning was measured using the Functional Assessment Questionnaire at baseline and annual follow-up visit across three years. RESULTS: Adjusting for age, education, sex, cognitive status, depression, white matter hyperintensity volume, cerebral metabolism, and reference (precentral) CBF, linear mixed effects models showed that lower resting CBF at baseline in the medial temporal, inferior temporal, and inferior parietal lobe was significantly associated with accelerated decline in everyday functioning. Results were similar after adjusting for conventional AD biomarkers, including cerebrospinal fluid (CSF) amyloid-β (Aβ) and hyperphosphorylated tau (p-tau) and apolipoprotein E (APOE) ɛ4 positivity. Individuals who later converted to dementia had lower resting CBF in the inferior temporal and parietal regions compared to those who did not. CONCLUSION: Lower resting CBF in AD vulnerable regions including medial temporal, inferior temporal, and inferior parietal lobes predicted faster rates of decline in everyday functioning. CBF has utility as a biomarker in predicting functional declines in everyday life and conversion to dementia.
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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 | 0.000 | 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 | 0.001 | 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".