The effect of internal carotid stenosis on white matter lesion and cognition function of Binswanger disease
Bibliographic record
Abstract
Objective To investigate the influence of the different degree of internal carotid stenosis on the white matter lesion and cognition of Binswanger disease. Methods A total of 108 elderly patients with Binswanger disease from Department of Geriatric Neurology of Qilu Hospital were recruited during December 2013 and June 2014. At the end of follow-up, 6 cases showed acute cerebrovascular disease, 39(<10%)had no internal carotid stenosis, 31(10%-49%)had mild internal carotid stenosis, 32(50%-70%)had moderate internal carotid stenosis through B ultrasound examination and MRI and MRA examination on internal carotid artery and brain. The B ultrasound examination of internal carotid artery included intima-media thickness (IMT), plaque index and the peak systolic velocity (PSV). Cognitive function of Binswagner disease was assessed by Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MOCA). The white matter lesion was assessed by reformed visual Scheltens scale. The relationship among IMT, plaque index, PSV, white matter lesion, and cognitive function was investigated. The variation of cognition was observed after 1 year. Results There were statistically significant differences in IMT, PSV, plaque index, reformed Scheltens scale scores between groups of non, mild, moderate internal carotid stenosis (all P 0.05). There were positive correlation between PSV and reformed Scheltens scale scores (r=0.630, P=0.020). There were negative correlation between PSV and MMSE scores (r=-0.970, P=0.040). The scores of MMSE and MOCA both were declined after 1 year in three groups (0.61±0.60, 0.68±0.81), (0.70±0.60, 0.93±0.69), (1.06±0.68, 1.13±0.76). The declination of MMSE and MOCA of BD patients was higher in moderate internal carotid stenosis group than in non internal carotid stenosis group (P 0.05). Conclusions Internal carotid stenosis is one of risk factors for the cognitive impairment of BD, the abnormal IMT and PSV are both correlated with white matter lesion and cognitive impairment in BD. Early standardized therapy can postpone the rate of cognitive impairment in BD. Key words: Carotid stenosis; Cerebrovascular disorders; Cognition disorders; Binswanger disease
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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 | 0.000 |
| 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) | 0.001 | 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".