Supplementary Material for: 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.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.808 | 0.227 |
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".