The impact of medial temporal and parietal atrophy on cognitive function in dementia
Bibliographic record
Abstract
Although medial temporal atrophy (MTA) and parietal atrophy (Koedam score) have been used to diagnose Alzheimer's disease (AD), early detection of other dementia types remains elusive. The study aims to investigate the association between these brain imaging markers and cognitive function in dementia. This cross-sectional study collected data from the Memory Clinic of Dr. Sardjito General Hospital Yogyakarta, Indonesia from January 2020 until December 2022. The cut-off value of MTA and Koedam score was set with Receiver Operating Curve. Multivariate analysis was performed to investigate the association between MTA and Koedam score with cognitive function. Of 61 patients, 22.95% had probable AD, 59.01% vascular dementia, and 18.03% mixed dementia. Correlation test showed that MTA and Koedam score were negatively associated with Montreal Cognitive Assessment-Indonesian Version (MoCA-INA) score. MTA score ≥ 3 (AUC 0.69) and Koedam score ≥ 2 (AUC 0.67) were independently associated with higher risk of poor cognitive function (OR 13.54, 95% CI 1.77-103.43, p = 0.01 and OR 5.52, 95% CI 1.08-28.19, p = 0.04). Higher MTA and Koedam score indicate worse cognitive function in dementia. Future study is needed to delineate these findings as prognostic markers of dementia severity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".