The cognitive dysfunction related to Alzheimer disease or cerebral small vessel disease
Bibliographic record
Abstract
ABSTRACT: Alzheimer disease (AD) and sporadic cerebral small vessel disease (CSVD) are common cognitive disorders. Both AD and CSVD have mental symptoms including chronic progressive cognitive impairment, dysfunction, and behavioral abnormalities. However, the differences on the cognitive dysfunction of AD and CSVD remain unclear. It is necessary to elucidate the cognitive dysfunction differences of AD and CSVD, and to identify the potential risk factors.AD or sporadic CSVD patients treated in our hospital from December 1, 2018 to May 31, 2019 were included. And we selected healthy participants as controls. The mini-mental state examination and Montreal Cognitive Assessment Scale were used for neuropsychological assessment, and related medical information were collected and compared.A total of 190 patients were included. The total mini-mental state examination scores in AD, CSVD group were significantly less than that of control group, there were significant differences in the domains of directional ability, attention and computing ability, delayed recall, and visual perception (all P < .05); the total Montreal Cognitive Assessment Scale scores in AD, CSVD group were significantly less than that of control group. There were significant differences in the domains of visual space and execution, immediate remember, attention and computing ability, language, delayed recall, and directional ability (all P < .05); diabetes was a risk factor both for AD (hazard ratio = 1.63, 95% confidence interval: 1.35-1.97) and CSVD (hazard ratio = 1.15, 95% confidence interval: 1.08-1.27).The cognitive dysfunctions of AD are difference to that of CSVD patients, and diabetes is the risk factor both for AD and CSVD, future studies are needed to further identify the prevention and treatment of AD and CSVD.
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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 | 0.000 | 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) | 0.003 | 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".