Study of the Correlation between the Cognitive Impairment and White Matter Changes in Patients with Acute Ischemic Stroke
Bibliographic record
Abstract
Objective To investigate the correlation between the cognitive impairment and leukoaraiosis in patients with acute ischemic stroke. Methods One hundred and seven emergency patients with acute ischemic stroke(onset within 7 days)were included in this study.The cognitive function was assessed with Montreal Cognitive Assessment(MoCA).Two trained raters evaluated computer tomography(CT)and magnetic resonance imaging(MRI)scans using CT(Blennow)and MR1(Fazekas and Cholinergic Pathways Hyperlntensities Scale[CHIPS])rating scales for white matter changes.Correlations between the cognitive impairment and leukoaraiosis were evaluated. Results High correlations were observed between MoCA and Blennow and CHIPS rating scales (Spearman's coefficient were-0.300 and-0.316,respectively,P0.01).There was no significant correlation between MoCA and Fazekas rating scale(Spearman's coefficient was-0.159,P0.05). Conclusion The present findings support the view that a good correlation exists between the cognitive impairment and severity of white matter changes in patients with acute ischemic stroke The MRI rating scale for white matter lesions,in cholinergic pathways,CHIPS rating scale,is effective,reliable and shows stronger correlations with cognitive performance.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".