Frailty is associated with the clinical expression of neuropsychological deficits in older adults
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The aim was to determine whether frailty is associated with the relationship between neuropsychological markers and global cognition in older adults. METHODS: Cross-sectional analyzes were conducted of baseline data from three large cohort studies: National Alzheimer's Coordinating Center (NACC), Rush Memory and Aging Project (MAP) and Alzheimer's Disease Neuroimaging Initiative (ADNI). Studies recruited North American participants along the spectrum of cognitive functioning (44% no cognitive impairment at baseline). A frailty index was computed in each dataset. Frailty indices, neuropsychological tests (including measures of processing speed, episodic, semantic and working memory) and Mini-Mental State Examination (MMSE) scores were the variables of interest, with age, sex, education and apolipoprotein E ε4 evaluated as confounders. RESULTS: Across all studies, 23,819 participants aged 55-104 (57% female) were included in analyzes. Frailty index scores were significantly and inversely associated with MMSE scores and significantly moderated relationships between neuropsychological test scores and MMSE scores. In participants with higher frailty index scores, lower neuropsychological test scores were more strongly associated with lower MMSE scores (standardized interaction coefficients ranged from -0.19 to -1.17 in NACC, -0.03 to -2.27 in MAP and -0.04 to -0.38 in ADNI, depending on the neuropsychological test). These associations were consistent across the different databases and were mostly independent of the composition of frailty indices (i.e., after excluding possible symptoms of dementia). CONCLUSIONS: Amongst older Americans, frailty is associated with the cognitive expression of neuropsychological deficits. Implementation of frailty assessment in routine neurological and neuropsychological practice should be considered to optimize care outcomes for older adults.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".