Sex differences in risk factors, burden, and outcomes of cerebrovascular disease in Alzheimer’s disease populations
Bibliographic record
Abstract
Abstract Background White matter hyperintensity (WMH) accumulation is associated with vascular risk factors such as hypertension, diabetes, smoking, and obesity. Increased WMH burden results in increased cognitive decline and progression to mild cognitive impairment (MCI) and dementia. However, research has been inconsistent when examining whether sex differences influence the relationship between vascular risk factors, WMH accumulation, and cognition. Methods A total of 2119 participants (987 females) with 9847 follow-ups from the Alzheimer’s Disease Neuroimaging Initiative met inclusion criteria for this study. Linear regressions were used to examine the association between vascular risk factors (individually and as a composite score) and WMH burden in males and females. When controlling for vascular risk factors, linear mixed models were also used to investigate whether the relationship between WMHs and longitudinal cognitive scores differed between males and females. Results Males had overall increased occipital ( p <.001), but lower frontal ( p <.001), total ( p =.01), and deep ( p <.001) WMH burden compared to females. For males, history of hypertension was the strongest contributor to WMH burden. On the other hand, the vascular composite score was the strongest factor for WMH in females. Greater increase in WMH accumulation was observed in males with a history of hypertension in the frontal region ( p =.014) and males with high systolic blood pressure in the occipital region ( p =.029) compared to females. With respect to cognition, WMH burden was more strongly associated with longitudinal decreases in global cognition, executive functioning, and functional activities of daily living in females compared to males. Discussion These findings show that controlling hypertension is important to reduce WMH burden in males. Conversely, minimizing WMH burden through vascular risk factors requires controlling many factors for females (e.g., hypertension, diabetes, smoking, alcohol abuse, etc.). The results have implications for therapies and interventions designed to target cerebrovascular pathology and the subsequent cognitive decline.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".