Neuropsychological Profile of Early Cognitive Impairment in Cerebral Small Vessel Disease
Bibliographic record
Abstract
INTRODUCTION: The neuropsychological feature of vascular mild cognitive impairment is a deficit of the frontal-subcortical circuit; however, the features in the early stage are not consistent. In the present study, we aimed to investigate the neuropsychological features of the very early stage of cognitive impairment with cerebral small vessel disease (CSVD) and to elucidate the cognitive differences among CSVD subtypes. METHODS: A comprehensive neuropsychological test battery was applied to nondemented subjects scoring below the cutoff point 26 of the Japanese version of the Montreal Cognitive Assessment. After factor analysis was conducted to identify covert cognitive factors in the battery, correlation analyses were performed between the factors and CSVD subtypes: white matter hyperintensity (WMH), lacunar infarcts (LIs), cerebral microbleeds (CMBs), perivascular spaces, and cortical atrophy. RESULTS: Among the 465 recruited patients, 139 underwent a full neuropsychological test battery. Through factor analysis, the following three factors were extracted: executive function, memory, and attention. Of the CSVD features, total WMH was correlated with executive function and memory, whereas deep WMH was correlated with memory alone. Of the CSVD subtypes, LIs and CMBs were correlated only with executive function. Frontal and posterior atrophy were correlated with memory and attention, whereas medial temporal atrophy was correlated with memory alone. CONCLUSIONS: Executive dysfunction accompanied by subtle impairment of memory and processing speed was the main feature of neuropsychological profiles in the subjects with CSVD, even in the very early stage. Furthermore, each CSVD feature and focal cerebral atrophy are associated with cognitive impairment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| 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) | 0.004 | 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".