A neuropsychological study of patients with mild cognitive impairment
Bibliographic record
Abstract
Objective To explore the neuropsychological features of patients with mild cognitive impairment (MCI). Methods Forty-two patients with MCI and 50 normal controls were examined with a series of neuropsychoiogieai tests. These test included mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), clinical dementia rating scale (CDR), rapid verbal retrieve (RVR), activity of daily living scale (ADL), Wechsler intelligence scale (WAIS-RC) and its sub-tests (digit span[DS], blocks design test [BD], similarity test), Wechsler memory scale (WMS-R) and its sub-tests (logical memory, associative learning, visual recognition, picture recall). The difference of these data were compared and analyzed. Results The patients with MCI had significantly lower MMSE total score, MoCA total score, RVR score, WAIS-RC score and its sub-tests scores, WMS-R score and its sub-test scores than healthy controls (P 0.05). For the MoCA sub-items, the patients with MCI had significantly lower scores than healthy controls in all the cognitive function measures except fixed orientation (P<0.05). Conclusions In addition to memory impairment, naming, visuospatial ability and executive function may also be impaired in patients with MCI; delayed recall, calculation and attention are obviously impaired in patients with MCI. MoCA, covering the important cognitive domains, can comprehensively assess the cognitive functions of patients with MCI and has its value in the clinical application. Key words: Mild cognitive impairment; Neuropsycbological testes; Montreal cognitive assessment
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".