Current perspectives on prevention of vascular cognitive impairment and promotion of vascular brain health
Bibliographic record
Abstract
INTRODUCTION: The true global burden of vascular cognitive impairment (VCI) is unknown. Reducing risk factors for stroke and cardiovascular disease would inevitably curtail VCI. AREAS COVERED: The authors review current diagnosis, epidemiology, and risk factors for VCI. VCI increases in older age and by inheritance of known genetic traits. They emphasize modifiable risk factors identified by the 2020 Lancet Dementia Commission. The most profound risks for VCI also include lower education, cardiometabolic factors, and compromised cognitive reserve. Finally, they discuss pharmacological and non-pharmacological interventions. EXPERT OPINION: By virtue of the high frequencies of stroke and cardiovascular disease the global prevalence of VCI is expectedly higher than prevalent neurodegenerative disorders causing dementia. Since ~ 90% of the global burden of stroke can be attributed to modifiable risk factors, a formidable opportunity arises to reduce the burden of not only stroke but VCI outcomes including progression from mild to the major in form of vascular dementia. Strict control of vascular risk factors and secondary prevention of cerebrovascular disease via pharmacological interventions will impact on burden of VCI. Non-pharmacological measures by adopting healthy diets and encouraging physical and cognitive activities and urging multidomain approaches are important for prevention of VCI and preservation of vascular brain health.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".