Cumulative Frailty in Late‐Middle Aged Men is Associated with Later Regional Abnormal White Matter and Decreased Processing Speed
Bibliographic record
Abstract
Abstract Background Frailty refers to a person’s physical and functional capabilities and increases during aging. Abnormal white matter (AWM; e.g., hyperintensities on T2‐weighted MRI) is a neuroimaging marker of small‐vessel vascular disease associated with increased risk of Alzheimer’s Disease and related dementias. While some studies have found associations between frailty indices (FIs) and global AWM, their association with accumulation of regional AWM and any related cognitive correlates is understudied. Method 342 men from the Vietnam Era Twin Study of Aging with frailty measured at study baseline (mean age = 56.4) and structural MRI scans at follow‐up (mean 5.5 years later) were included (Table 1). The FI measure was based on a cumulative deficit model[1] using an index of 37 health‐ and function‐related items. Global AWM was defined using morphological operators on multi‐channel, three‐class tissue segmentation[2]. A novel watershed routine, applied to our AWM frequency atlas, generated 5 distinct AWM parcellations: frontal, posterior, anterior periventricular, deep, and temporal stem (Figure 1A). Cognitive factor scores (memory, processing speed, executive function, fluency) were derived from normative neuropsychological test performance. Result Mixed‐effects linear regression models controlling for age, years of education and twin‐pair demonstrated that higher baseline FI was associated with greater future AWM volume in temporal stem (p = 0.03) and anterior periventricular (p = 0.02) regions, but not for global or other parcellations (Figure 1B). Baseline FI was not cross‐sectionally associated with any cognitive factor score but was associated longitudinally with decreased processing speed (p = 0.002) (Table 2). Conclusion Higher cumulative frailty in late‐middle aged men was associated with greater future AWM burden and greater decline in processing speed. These findings suggest that cumulative frailty during the 6th decade is a relevant indicator and possible predictor of future pathological structural and functional processes in the brain. Longitudinal studies may elucidate whether frailty affects AWM progression and cognitive decline along a common causal pathway. References: [1] Rockwood K. A global clinical measure of fitness and frailty in elderly people. Canadian Medical Association Journal 2005;173:489‐95. [2] Fennema‐Notestine C, et al. White matter disease in midlife is heritable, related to hypertension, and shares some genetic influence with systolic blood pressure. NeuroImage: Clinical 2016;12:737‐45.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".