Cognitive profile in cerebral small vessel disease: comparison between cerebral amyloid angiopathy and hypertension-related microangiopathy
Bibliographic record
Abstract
Cerebral amyloid angiopathy (CAA) is recognized as a cause of cognitive impairment, but its cognitive profile needs to be characterized, also respect to hypertension-related microangiopathy (HA). We aimed at comparing difference or similarity of CAA and HA patients' cognitive profiles, and their associated factors. Participants underwent an extensive clinical, neuropsychological, and neuroimaging protocol. HA patients (n = 39) were more frequently males, with history of vascular risk factors than CAA (n = 32). Compared to HA, CAA patients presented worse performance at MoCA (p = 0.001) and semantic fluency (p = 0.043), and a higher prevalence of amnestic MCI (46% vs. 68%). In univariate analyses, multi-domain MCI was associated with worse performance at MoCA, Rey Auditory Verbal Learning Test (RAVLT), and semantic fluency in CAA patients, and with worse performance at Symbol Digit Modalities Test (SDMT) and phonemic fluency in HA ones. In multivariate models, multi-domain deficit remained as the only factor associated with RAVLT (β = - 0.574) in CAA, while with SDMT (β = - 0.364) and phonemic fluency (β = - 0.351) in HA. Our results highlight different patterns of cognitive deficits in CAA or HA patients. While HA patients' cognitive profile was confirmed as mainly attentional/executive, a complex cognitive profile, characterized also by deficit in semantic memory, seems the hallmark of CAA patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".