Association Between Vascular Pathology and Rate of Cognitive Decline Independent of Alzheimer's Disease Pathology
Bibliographic record
Abstract
OBJECTIVES: To examine the association between vascular pathology and rate of cognitive decline in older adults independent of Alzheimer's disease (AD) pathology. DESIGN: Prospective cohort study. SETTING: Community sample. PARTICIPANTS: Individuals from the Einstein Aging Study autopsy series (N = 62). MEASUREMENTS: The Blessed Information-Memory-Concentration (BIMC) test was used to assess global cognitive status. AD pathology was quantified according to Braak stage (<3 vs ≥ 3). Vascular pathology was quantified using a previously reported macrovascular lesion (MVL) score. The association between vascular pathology and antemortem rates of cognitive decline adjusted for level of AD pathology was assessed using linear mixed-effects models. RESULTS: Mean age was 81.8 at enrollment and 89.0 at death. Participants with more than two MVLs had faster cognitive decline than those with no MVLs (difference in annual rate of change in BIMC 0.74 points/yr, P = .03). Braak stage was also associated with cognitive decline (difference 0.57 points/yr, P = .03). The difference in rate of cognitive decline between those with more than two MVLs and those free of vascular lesions persisted after adjustment for AD pathology (difference in rate of change in BIMC 0.68 points/yr, P = .04). The effect of vascular pathology on cognitive decline was not significantly different according to AD pathology. CONCLUSION: Vascular brain pathology is associated with rate of cognitive decline after adjusting for level of AD pathology.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".