Cerebral Ischemia is Associated With Corneal Nerve Loss and Brain Atrophy in Mild Cognitive Impairment and Dementia
Bibliographic record
Abstract
Abstract BackgroundThe prevalence of cerebral ischemia increases with age and is a risk factor for cognitive impairment and dementia. This study assessed the association of brain ischemic lesions with the severity of neurodegeneration utilizing brain volumetric MRI and corneal confocal microscopy (CCM) in patients with mild cognitive impairment (MCI) and dementia.MethodsSubjects with MCI and dementia without diabetes underwent cognitive screening, CCM, assessment of ischemic lesions and quantitative brain MRI.ResultsOf 63 subjects with MCI (n=44) and dementia (n=19), 11 had no ischemia, 32 had subcortical ischemia and 20 had both cortical and subcortical ischemia. Subjects with MCI and dementia had comparable percentage of cerebral ischemia (P=0.25). Global cognitive function was significantly impaired in subjects with both cortical and subcortical ischemia (P<0.05) but not in those with subcortical ischemia (P=0.10) compared to those without ischemia. Corneal nerve fiber density (CNFD)(P<0.01), branch density (CNBD) (P<0.05) and fiber length (CNFL) (P<0.01) were significantly lower in subjects with both cortical and subcortical ischemia compared to those without ischemia and CNFD (P<0.05), CNBD (P<0.05) and CNFL (P<0.05) were significantly lower in subjects with both cortical and subcortical ischemia compared to those with subcortical ischemia. In subjects with both cortical and subcortical ischemia whole brain (P<0.01) and hippocampal volume (P<0.001) were significantly lower and ventricle volume was higher (P<0.05) compared to those without ischemia and hippocampal volume (P<0.01) was lower and ventricle volume was higher (P<0.01) in subjects with both cortical and subcortical ischemia compared to those with subcortical ischemia.ConclusionsThe presence of cortical and subcortical ischemia is associated with cognitive impairment, corneal nerve loss and brain atrophy in patients with MCI and dementia.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.008 |
| 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".