[Characteristics of cognitive impairment of different infarct locations among patients after acute ischemic stroke].
Bibliographic record
Abstract
OBJECTIVE: To investigate the characteristics of cognitive function changes of different infarct sites among patients after acute ischemic stroke, so as to provide theoretical basis for preventing and treating vascular cognitive dysfunction. METHODS: One hundred and five cases of acute ischemic stroke within fourteen days meeting the standard set were enrolled, and they were tested by Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). And the characteristics of cognitive changes with different infarction sites were analyzed. RESULTS: Patients with acute stroke suffered cognitive impairment.The significantly impaired cognitive domains in MMSE were: graphics execution in patients with left hemisphere infarction (P=0.027); verbal repetition in frontal infarction (P=0.003); short memory (P=0.04) and verbal repetition (P=0.007) in parietal infarction.The significantly impaired cognitive domains in MoCA were: language (P=0.002), naming (P=0.011), attention (P=0.028) and time orientation (P=0.031) in frontal infarction; delayed memory (P<0.001), attention (P=0.041), language (P=0.049) and visual space and executive ability (P=0.049) in parietal infarction; attention in temporal infarction (P=0.045); language (P=0.009) and time orientation (P=0.026) in basal ganglia region infarction. CONCLUSION: Most ischemic stroke patients at acute phase suffered cognitive impairment and the characteristics of cognitive changes differed according to different infarction sites.Comprehensive assessment of cognitive impairment after acute stroke is of great importance.
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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) | 0.002 | 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".