VISUAL MEDIAL TEMPORAL ATROPHY SCALES IN CLINICIAN PRACTICE
Bibliographic record
Abstract
Background: Visual atrophy scales from the medial temporal region are auxiliary biomarker methods in Alzheimer’s Disease(AD).They may correlated with progression from preclinical to clinical AD. Objective: We aimed to compare medial temporal lobe atrophy (MTA) and entorhinal cortex atrophy (ERICA) scales for magnetic resonance image as a useful tool for probable AD diagnosis and evaluate their accuracy, sensitivity and specificity, regarding clinical diagnosis and 11C-PIB-PET. Methods: 2 neurologists blinded to diagnosis classified 113 adults (over 65y) through MTA and ERICA scales and correlated with sociodemographic data, amyloid brain cortical burden through the 11C-PIB-PET and clinical cognitive status, divided into 30 cognitive unimpaired (CU) individuals, 52 MCI and 31 dementia compatible with AD (DCAD). Results: Inter-rater reliability of these atrophy scales was excellent (0.8- 1) by Cohen analysis. CU group had significantly lower MTA scores (median value 0) than ERICA (median value 1)for both hemispheres. 11C-PIB-PET was positive in 45% of the whole sample. In MCI and DCAD groups, ERICA depicted greater sensitivity and MTA greater specificity. Accuracy was under 70% for both scores in all clinical groups. Conclusion: Our study achieved a moderate sensitivity for ERICA score and could be a better screening tool for DCAD or MCI than MTA score. But, none of them could be considered a useful biomarker in preclinical AD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".