Comparison of vascular stiffness in vascular dementia, Alzheimer dementia and cognitive impairment
Bibliographic record
Abstract
Abstract Defining the vascular component(s) of the clinical diagnosis of vascular cognitive impairment (VCI) and vascular dementia (VaD) continues to be problematic. The goal of this study was to determine whether vascular stiffness, measured by pulse wave velocity (PWV), is altered in VaD, to study the utility of PWV in differentiating VaD from Alzheimer dementia (AD) and the relationship between PWV and cognitive function. A qualitative and quantitative structured analysis of the literature was conducted until September 2010, using a search strategy based on the key words: dementia, vascular dementia, dementia of vascular origin, cognitive function and arterial stiffness or pulse wave velocity. Seventeen studies assessed large vessel vascular stiff by PWV and related it to cognitive function or dementia. Six of these studies compared PWV in 154 persons with VaD, 207 with AD and 197 controls without dementia. Mean PWV was significantly (p < 0.0001) higher in VaD compared with controls. Mean PWV was significantly (p = 0.002) higher in VaD compared with AD. Fourteen studies examined the relationship between PWV and cognitive function. The majority of studies (nine of 14) reported a significant correlation between PWV and cognitive function. Four of eight studies that evaluated the relation using univariate analysis reported a significant correlation of PWV with the Mini Mental State Exam (MMSE) or Hasegawa Dementia Scale, and the correlation with MMSE between studies showed a close agreement of correlation coefficients (0.206 to 0.27). In multivariate analysis, adjusted for a wide range of possible confounding factors, the majority or 80% (eight out of 10) studies comprising a population of 6,034 individuals found a significant inverse relationship between PWV and cognitive function. In summary, vascular stiffness is inversely related to cognitive function. Vascular stiffness is greater in VaD compared with AD, suggesting PWV may be useful in identifying VaD.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".