P1‐316: THE CLINICAL CHARACTERISTICS OF COGNITIVE IMPAIRMENT IN PATIENTS WITH VASCULAR MILD COGNITIVE IMPAIRMENT
Bibliographic record
Abstract
To investigate the characteristics of the cognitive impairment in patients with vascular mild cognitive impairment (VaMCI). Seventy-five patients with VaMCI and 38 age, gender-matched healthy subjects were recruited from the department of Neurology, Beijing Chaoyang Hospital, Capital Medical University between Jan 2016 and June 2016. All the participant underwent the neuropsychological tests. The Fazekas scale was used to assess the severity of white matter lesions, and the medial temporal lobe atrophy (MTA) to evaluate the atrophic severity of medial temporal lobe. The results of our study showed that patients with VaMCI were associated with comprehensive cognitive function deficits, including MMSE [25.7±2.3 vs 28.4±2.0] MoCA [22.8±3.9 vs 26.3±3.7], AVLD-I [5.1±1.0 vs 8.9±1.9], AVLT-D [3.7±1.0 vs 9.8±1.5] and AVLT-R [7.6±1.9 vs 12±1.5] (P＜0.05) . Correlation analysis showed that the scale of medial temporal lobe atrophy had a negative relationship with the performance of MoCA (r=−0.434, P=0.002). Our findings demonstrate patients with VaMCI were closely correlated to cognitive impairment, especially with memory decline, which may be attributed to white matter lesions and the atrophy of medial temporal lobe.
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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 | 0.002 |
| 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 | 0.001 |
| 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".