Differences in Cortical Thickness in Healthy Controls, Subjects with Mild Cognitive Impairment, and Alzheimer's Disease Patients: A Longitudinal Study
Bibliographic record
Abstract
In this study, we analyzed differences in cortical thickness (CTH) between healthy controls (HC), subjects with stable mild cognitive impairment (S-MCI), progressive MCI (P-MCI), and Alzheimer's disease (AD), and assessed correlations between CHT and clinical disease severity, education, and apolipoprotein E4 (APOE) genotype. Automated CTH analysis was applied to baseline high-resolution structural MR images of 145 subjects with a maximum followup time of 7.4 years pooled from population-based study databases held in the University of Kuopio. Statistical differences in CTH between study groups and significant correlations between CTH and clinical and demographic factors were assessed and displayed on a cortical surface model. Compared to HC group (n = 26), the AD (n = 21) group displayed significantly reduced CTH in several areas of frontal and temporal cortices of the right hemisphere. Higher education and lower MMSE scores were correlated with reduced CTH in the AD group, whereas no significant correlation was found between CDR-SB scores or APOE genotype and CTH. The P-MCI group demonstrated significantly reduced CTH compared to S-MCI in frontal, temporal and parietal cortices even after statistically adjusting for all confounding variables. Ultimately, analysis of CTH can be used to detect cortical thinning in subjects with progressive MCI several years before conversion and clinical diagnosis of AD dementia, irrespective of their cognitive performance, education level, or APOE genotype.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".