Hippocampal grading is sensitive to changes in cognition in early MCI
Bibliographic record
Abstract
Abstract Background Increased age and cognitive decline are both associated with changes in the hippocampus. These associations are often measured using hippocampal volume measurements and changes in episodic memory. Some studies have also observed a relationship between hippocampal volume and global cognition. However, these studies often only find associations in progressed stages of cognitive decline. This study examined (1) if hippocampal grading is associated with global cognition in cognitively normal controls (NC), early MCI (eMCI), late (lMCI), and Alzheimer’s disease (AD), and (2) whether these associations differ across diagnostic cohorts. Methods Participants for this study were selected from the Alzheimer’s Disease Neuroimaging Initiative. They were included if they completed baseline MRI scans and the Alzheimer’s disease Assessment Scale (ADAS‐13) and Clinical Dementia Rating – Sum of Boxes (CDR‐SB) cognitive tests. A total of 1620 older adults met the inclusion criteria and were included (495 CN, 262 eMCI, 545 lMCI, and 318 AD). Linear regressions examined the association between hippocampal grading and cognitive scores. Results Lower global cognition (measured by increased ADAS‐13 scores) was associated with hippocampal grading scores in in NC, eMCI, lMCI and AD cohorts. Lower global cognition (measured by increased CDR‐SB scores) was associated with hippocampal grading scores in lMCI and AD, but not in eMCI or NC groups. Conclusion Hippocampal grading was associated with changes in global cognition in healthy controls and in disease cohorts when there is sufficient dynamic range in the cognitive test. No correlation between CDR‐SB and NC was found because the NC group only had CDR‐SB scores of 0 and 1. Hippocampal grading may, thus, be a useful measure that is sensitive to progressive changes early in the disease course. Future research should determine if this method is associated with longitudinal changes in cognition.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".