Sex differences in risk factors that predict progression from mild cognitive impairment to Alzheimer’s dementia
Bibliographic record
Abstract
OBJECTIVES: To evaluate whether cerebrospinal fluid biomarkers, apolipoprotein e4, neuroimaging abnormalities, and neuropsychological data differentially predict progression from mild cognitive impairment (MCI) to dementia for men and women. METHODS: = 449) were classified as either progressing to Alzheimer's dementia at follow-up or as not progressing. Men and women were first compared using bivariate analyses. Sex-stratified Cox proportional hazard regressions were performed examining the relationship between baseline data and the likelihood of progressing to dementia. Sex interactions were subsequently examined. RESULTS: Cox proportional hazard regression controlling for age and education indicated that all variables significantly predicted subsequent progression to dementia for men and women. Sex interactions indicated that only Rey Auditory Verbal Learning Test (RAVLT) delayed recall and Functional Activities Questionnaire (FAQ) were significantly stronger risk factors for women. When all variables were entered into a fully adjusted model, significant risk factors for women were Aβ42, hippocampal volume, RAVLT delayed recall, Boston Naming Test, and FAQ. In contrast, for men, Aβ42, p-tau181, p-tau181/Aβ42, hippocampal volume, category fluency and FAQ were significant risk factors. Interactions with sex were only significant for p-tau181/Aβ42 and RAVLT delayed recall for the fully adjusted model. CONCLUSIONS: Men and women with MCI may to differ for which factors predict subsequent dementia although future analyses with greater power are needed to evaluate sex differences. We hypothesize that brain and cognitive reserve theories may partially explain these findings.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".