Correlation of MRI findings and cognitive function in multiple sclerosis patients using montreal cognitive assessment test.
Bibliographic record
Abstract
BACKGROUND: Magnetic resonance imaging (MRI) has improved the diagnosis and management of patients with multiple sclerosis (MS). Montreal Cognitive Assessment (MoCA) is a brief, sensitive test that has been recommended by National Institute of Neurological Diseases and Stroke and Canadian Stroke Network (NINDS-CSN) as a reliable tool to detect mild cognitive impairments. This study aimed to evaluate the relationship between MoCA test and its sub-items with brain abnormalities in MRI of MS patients. METHODS: Based on MRI scans of 46 MS patients, third ventricle and white matter lesions volumes were measured. Disease duration and expanded disability status scale (EDSS) were recorded in each patient. In addition, cognitive domains of the patients were evaluated by Montreal cognitive assessment (MoCA) test. We analyzed data using t-test or Mann-Whitney U test, Pearson correlation coefficient, and non-parametric Spearman test. Furthermore, multiple linear regression model was applied to evaluate the association between cognitive indices and MRI characteristics. RESULTS: Among MRI indices, only severity of atrophy showed a significant difference between cognitively impaired and cognitively preserved patients. Third ventricular volume was significantly correlated with total MoCA score (p=0.003, r=-0.42), but none of the juxtacortical or periventricular lesions volume revealed significant relation with total MoCA score. However, using multivariate linear regression after adjustment for educational level and disease duration, there was a significant negative association between juxtacortical lesions volume and total MoCA score as well as naming and attention sub-items. Also, memory score was adversely associated with the third ventricular volume (p=0.03, r=0.31). CONCLUSION: Cognitive disturbances detected by MoCA, may be associated with some pathological changes including atrophy, third ventricular volume, and juxtacortical lesion. MoCA, as a brief test, is not correlated with brain lesions volume in MS patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".