Frailty, neuropathological burden and clinical severity: A cross‐sectional analysis of data from the National Alzheimer’s Coordinating Center
Bibliographic record
Abstract
Abstract Background Within the National Alzheimer’s Coordinating Center (NACC) dataset, we quantified the associations of frailty and global neuropathological burden with clinical dementia severity, and explored whether frailty influences the expression of dementia at a given level of neuropathology. Method The sample included 2,621 individuals who had available clinical data and had undergone autopsy within 24 months of their last study visit. A 32‐item frailty index (FI) was calculated retrospectively using the deficit accumulation approach, and a measure of global neuropathological burden (NP) was calculated using a similar index approach from 12 markers of brain disease (e.g. neurofibrillary tangle Braak stage, density of neocortical neuritic plaques, severity of cerebral amyloid angiopathy, presence of microinfarcts). Linear models were used to model the change in the 18‐point Clinical Dementia Rating Scale sum of boxes score (CDR‐SB) per 10% increase in either the FI score or NP score, after adjusting for age, sex, education level, primary language, time from clinical assessment to autopsy, and APOE ε4 allelic status. Result The analytical sample was 80.8 years old (SD = 9.4 years, range = 60 – 100 years), on average. Each 10% increase in either measure was associated with a significantly higher CDR‐SB (FI: 2.41 points [95% CI = 2.27, 2.56]; NP: 0.87 points [95% CI = 0.73, 1.01]). A significant interaction indicated that the relationship between NP and CDR‐SB became weaker for each 10% increase in FI (P = .001). The largest increase in CDR‐SB due to a 10% increase in NP was observed among the least frail individuals (FI < 0.3; 1.15 points [95% CI = 0.91, 1.39]), with smaller and similar increases in CDR‐SB observed in both medium (FI ≥ 0.3; 0.77 points [95% CI = 0.47, 1.07]) and high frailty (FI ≥ 0.5, 0.73 points [95% CI = 0.39, 1.07]) groups. Conclusion An increasing degree of frailty and neuropathology are each independently associated with more severe impairment. Among the least frail individuals, neuropathological burden is closely related to clinical function, whereas clinical impairment may occur even at a low level of neuropathology in those who are more frail.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".