Comparison of Imaging Biomarkers in the Alzheimer Disease Neuroimaging Initiative and the Mayo Clinic Study of Aging
Bibliographic record
Abstract
OBJECTIVE: To determine whether magnetic resonance imaging measurements observed in the Alzheimer Disease Neuroimaging Initiative (ADNI) convenience sample differ from those observed in the Mayo Clinic Study of Aging (MCSA) population-based sample. DESIGN: Comparison of 2 samples. SETTING: Fifty-nine recruiting sites for the ADNI in the United States and Canada and the MCSA, a population-based cohort in Olmsted County, Minnesota. PATIENTS: Cognitively normal subjects and amnestic subjects with mild cognitive impairment were selected from the ADNI convenience cohort and MCSA population-based cohort. A simple random sample of subjects from both cohorts in the same age range was selected, and a second sample applied matching for age, sex, educational level, apolipoprotein E genotype, and Mini-Mental State Examination score. MAIN OUTCOME MEASURES: Baseline hippocampal volumes and annual percentage of decline in hippocampal volume. RESULTS: In the population-based sample, MCSA subjects were older, had less education, performed worse on the Mini-Mental State Examination, and had a family history of Alzheimer disease less often than did ADNI subjects. Baseline hippocampal volumes were larger in ADNI compared with MCSA cognitively normal subjects in the random sample, although no differences were observed after matching. Rates of decline in hippocampal volume were greater in the ADNI compared with the MCSA for cognitively normal subjects and those with amnestic mild cognitive impairment, even after matching. CONCLUSIONS: Rates of decline in hippocampal volume suggest that ADNI subjects have a more aggressive brain pathologic process than MCSA subjects and hence may not be representative of the general population. These findings have implications for treatment trials that use ADNI-like recruitment mechanisms and for studies validating new diagnostic criteria for Alzheimer disease in its various stages.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".