Relationship Between the Japanese Version of the Montreal Cognitive Assessment and PET Imaging in Subjects with Mild Cognitive Impairment
Bibliographic record
Abstract
BACKGROUND: The Montreal Cognitive Assessment (MoCA) test has high sensitivity and specificity for detecting mild cognitive impairment or early dementia. How the MoCA score relates to findings of positron emission tomography imaging, however, remains unclear. OBJECTIVE: This prospective study examined the relationship between the Japanese version of the MoCA (MoCA-J) test and brain amyloid deposition or cerebral glucose metabolism among subjects with mild cognitive impairment. METHODS: A total of 125 subjects with mild cognitive impairment underwent the MoCA-J test, and amyloid- and 18F-fluorodeoxyglucose- positron emission tomography. Linear correlation analysis and multiple linear regression analysis were conducted to investigate the relationship between the MoCA-J score and demographic characteristics, amyloid deposition, and cerebral glucose metabolism. Moreover, Statistical Parametric Mapping 8 was used for a voxel-wise regression analysis of the MoCA-J score and cerebral glucose metabolism. RESULTS: The MoCA-J score significantly correlated with age, years of education, and the Mini-Mental State Examination score. After adjusting for age, sex, and education, the MoCA-J score significantly correlated negatively with amyloid retention (β= -0.174, p= 0.031) and positively with cerebral glucose metabolism (β= 0.183, p= 0.044). Statistical Parametric Mapping showed that Japanese version of MoCA score correlated with glucose metabolism in the bilateral frontal and parietal lobes, and the left precuneus. CONCLUSION: The total MoCA-J score correlated with amyloid deposition and frontal and parietal glucose metabolism in subjects with mild cognitive impairment. Our findings support the usefulness of the MoCA-J test for screening subjects at high risk for Alzheimer's disease.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".