Differential WMH progression trajectories in progressive and stable mild cognitive impairment
Bibliographic record
Abstract
Abstract Background Pathological brain changes such as white matter hyperintensities (WMHs) occur with increased age and contribute to cognitive decline. Current research is still unclear regarding the association of amyloid positivity with WMH burden and progression to dementia in people with mild cognitive impairment (MCI). Methods This study examined whether WMH burden increases differently in both amyloid-negative (Aβ-) and amyloid-positive (Aβ+) people with MCI who either remain stable or progress to dementia. We also examined regional WMHs differences in all groups: amyloid positive (Aβ+) progressor, amyloid negative (Aβ–) progressor, amyloid positive (Aβ+) stable, and amyloid negative (Aβ–) stable. MCI participants from the Alzheimer’s Disease Neuroimaging Initiative were included if they had APOE ɛ4 status and if they had amyloid measures to determine amyloid status (i.e., positive, or negative). A total of 820 MCI participants that had APOE ɛ4 status and amyloid measures were included in the study with 5054 follow-up time points over a maximum period of 13 years with an average of 5.7 follow-up timepoints per participant. Linear mixed-effects models were used to examine group differences in global and regional WMHs. Results People who were Aß– stable had lower baseline WMHs compared to both Aß+ progressors and Aß+ stable across all regions. When examining change over time, compared to Aß– stable, all groups had steeper change in WMH burden with Aß+ progressors having the largest change (largest increase in WMH burden over time). Conclusion These findings suggest that WMH progression is a contributing factor to conversion to dementia both in amyloid-positive and negative people with 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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".