Cerebrovascular and Alzheimer disease: fellow travelers or partners in crime?
Bibliographic record
Abstract
In this review, we will discuss the progressive decline in cognitive and intellectual performance in late life that has led to great challenges for medical and community services. The term 'vascular cognitive impairment' is defined as any cognitive impairment that is caused by or associated with vascular factors. It can occur alone or in association with Alzheimer disease. The good news is that because vascular risk factors are treatable, it should be possible to prevent or delay some dementias. Since vascular cognitive impairment may often go unrecognized, many experts recommend screening with brief tests to assess memory, thinking, and reasoning for everyone considered to be at high risk for this disorder. Up to 64% of persons 65 years or older who have experienced a stroke have some degree of cognitive impairment with up to one third developing dementia. Postmortem studies indicate that up to 34% of dementia cases show significant vascular pathology. It suggests that ischemic stroke triggers additional pathophysiological process that may lead to a secondary degenerative process that may interact with Alzheimer disease pathology thus accelerating the ongoing primary neurodegeneration. Mechanisms could include hypoperfusion, hypoxia, and neuroinflammation, one of the links between the two pathologies. Stroke and dementia share the same risk and protective factors. Since stroke interact with dementia of all types it may already be possible to reduce or delay some dementias by a number of interventions known to prevent stroke. This article is part of the Special Issue "Vascular 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".