Progressive Hippocampus Atrophy in Persons with Mild Cognitive Impairment: A Longitudinal MRI Study (P6.329)
Bibliographic record
Abstract
Background: We hypothesized that hippocampus atrophy is a relatively common occurrence in mild cognitive impairment (MCI) and maybe associated with neurocognitive decline and structural changes in particular regions of the brain. Methods: We analyzed clinical and neuroimaging data collected as part of Alzheimer’s Disease Neuroimaging Initiative from individuals with MCI recruited at approximately 50 sites in the United States and Canada. All participants underwent 1.5 T structural magnetic resonance imaging (MRI) at specified intervals (6 or 12 month) for 2-3 years. We used the serial volumetric measurement of hippocampus to identify persons with progression of atrophy (>5% volume loss over 12 months). We determined the factors and neuropsychological correlates associated with progression of atrophy. Results: A total of 192 persons with MCI were included [mean (±SD) 72±6 years, 126 were men]. Of the 192 persons, 49 (26%) had progression of atrophy within 12 months. The proportion of women was higher among those with progression (23 of 49 versus 43 of 143, p=0.04). There were no significant differences in the rates of cardiovascular risk factors or alleles of APO E4 gene among persons with or without progressive atrophy. The annual % increase in clinical dementia rating scale was significantly higher among those with progressive atrophy (39.2±21.5 versus 28.0±9.1. p=0.005) There was significantly higher volume loss in those with progressive hippocampus atrophy in middle temporal lobes (p=0.05) and entorhinal cortex (p=0.02). The ventricular volume increased significantly among those with progressive hippocampus atrophy (p=0.0005). Conclusions: The association of progressive atrophy of hippocampus with neurocognitive performance in persons with MCI and concurrent atrophy in selected regions of brain may provide new insights into pathophysiology of MCI.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".