P2‐265: THE CLINICAL CHARACTERISTICS OF COGNITIVE IMPAIRMENT IN PATIENTS WITH SMALL VESSEL DISEASE
Bibliographic record
Abstract
To explore the clinical characteristics of the cognitive disorders in patients with small vessel disease (SVD). A total of 60 patients with SVD and 50 age, gender-matched healthy subjects were recruited consecutively from the department of Neurology, Beijing Chaoyang Hospital. All the participants were performed by a battery of neuropsychological tests. The Fazekas scale was utilized to assess the severity of white matter lesions, and the scale of medial temporal lobe atrophy (MTA) was to evaluate the severity of medial temporal lobe. Patients with SVD were associated with global cognitive function deficits, including the general tests of MMSE (25.9±2.4 vs 28.1±1.7) and MoCA (23.0±3.7 vs 26.2±3.0), and also with performances of AVLD-I, AVLT-D, AVLT-R, TMT-B, Stroop B, Stroop C and DST (P<0.05). The score of MOCA was related negatively with Fazekas scale (r=−0.361, P=0.04). The severity of Fazekas had a positive relationship with the scores of MTA (r=0.449, P=0.032). Patients with SVD are closely correlated to general cognitive impairment, especially with memory decline, attention and executive function, which may be attributed to the impairment of frontal-subcortical circle.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".