The relationship of white matter lesions location and cognitive function in leukoaraisosis patients
Bibliographic record
Abstract
Objective To study the effect of white matter lesions location on cognitive function by comparing the correlation between the anatomical location of white matter lesions and cognitive function in leukoaraisosis(LA) patients. Methods A total of 75 LA patients with different degrees of white matter lesion were randomly recruited.The modified Scheltens scale, Manolio scale and Fazekas scale were utilized to assess the severity of white matter lesions (WMLs) by two physicians.Montreal cognitive assessment (MoCA) was used to evaluate the cognitive function.The correlation between WMLs location and cognitive function was analyzed by spearman rank correlation analysis.The t-test was used to test the differences of periventricular white matter lesions with cognitive impairment (PWMLs-CI) and periventricular white matter lesions with cognitive normal(PWMLs-CN) in each goup. Results For Fazekas scale, PWMLs were significantly correlated with the decrease scores of MoCA score (r=-0.388, P=0.007), visuospatial and executive(r=-0.466, P=0.000), delayed recall (r=-0.461, P=0.001), abstraction (r=-0.355, P=0.011) and orientation (r=-0.337, P=0.016)(P 0.05). Compared with PWMLs-CN, executive function (42.13±0.89), attention (16.36±1.24) and visuospatial (2.25±0.31) in PWMLs-CI had statistical significance (P <0.05). Conclusion White matter lesions location affect cognitive function, PWMLs are more closely related to cognitive impairement, characterized by executive function, attention and visuospatial aspects. Key words: White matter lesions location; Visual rating scale; Cognitive impairment
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 teacher head, 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".