Marked gender differences in progression of mild cognitive impairment over 8 years
Bibliographic record
Abstract
Abstract Introduction This study examined whether, among subjects with mild cognitive impairment (MCI), women progressed at faster rates than men. Methods We examine longitudinal rates of change from baseline in 398 MCI subjects (141 females and 257 males) in the Alzheimer's Disease Neuroimaging Initiative‐1, followed for up to 8 years (mean, 4.1 ± 2.5 years) using mixed‐effects models incorporating all follow‐ups (mean, 8 ± 4 visits). Results Women progressed at faster rates than men on the Alzheimer's disease assessment scale‐cognitive subscale (ADAS‐Cog; P = .001) and clinical dementia rating‐sum of boxes (CDR‐SB; P = .003). Quadratic fit for change over time was significant for both ADAS‐Cog ( P = .001) and CDR‐SB ( P = .004), and the additional acceleration in women was 100% for ADAS‐Cog and 143% for CDR‐SB. The variability of change was greater in women. The gender effect was greater in apolipoprotein E ( APOE ) ε4 carriers. Discussion Women with MCI have greater longitudinal rates of cognitive and functional progression than men. Studies to confirm and uncover potential mechanisms appear to be warranted. Trial Registration ADNI ClinicalTrials.gov identifier: NCT00106899 .
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 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 | 0.000 | 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) | 0.003 | 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".