Correlation of Cognitive Impairment and Areas of Middle Cerebral Artery Territory Infarction
Bibliographic record
Abstract
Objective To explore the correlation of cognitive impairment and areas of middle cerebral artery(MCA) territory infarction.Methods The Montreal Cognitive Assessment(MoCA) was used to evaluate neuropsychological statuses in the patients who developed first-time acute cerebral infarction for 2 weeks. MoCA scores and sub-scores were recorded. 132 patients were selected with MCA occlusion, scores of MoCA were more than 15, and cognitive impairment in at least one domain, and then subgrouped by infarction site. The correlation between the results of neuropsychological cognitive assessment and the sites of infarction was analyzed. Results MCA occlusion was correlated with the impairments of visual spatial/executive, attention, language and memory(B=-1.875~-1.094, P0.05). Infarction in frontal lobe was correlated with the impairments of visual spatial/executive, attention, abstract and memory(B=-1.760~-1.329, P0.05),temporal lobe with visual spatial/executive and memory impairment(B=-1.849~-1.735, P0.05), parietal lobe with visual spatial/executive, attention and memory impairment(B=-1.695~-1.482, P0.05), basal ganglia with visual spatial/executive, attention, language and memory impairment(B=-1.932~-1.041, P0.01). Conclusion The characteristics of impairment in cognitive function is different with infarction sites in MCA territory.
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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 | 0.003 |
| 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".