Frailty Predicts Dementia and Death in Older Adults Living in Long-Term Care
Bibliographic record
Abstract
OBJECTIVES: To investigate how the accumulation of deficits traditionally related and not traditionally related to dementia predicts dementia and mortality. DESIGN: A retrospective cohort study with up to 9 years of follow-up. SETTING AND PARTICIPANTS: Long-term care residents aged ≥65 with or without dementia. METHODS: Frailty indices based on health deficit accumulation were constructed. The FI-t consisted of 27 deficits traditionally related to dementia; the FI-n consisted of 27 deficits not traditionally related to dementia; the FI-a consisted of all 54 deficits taken from the FI-t and the FI-n. RESULTS: In this long-term care sample (n = 29,758; mean age = 84.6 ± 8.0; 63.8% female), 91% of the residents had at least 1 impairment in activities of daily living, 61% had a diagnosis of dementia, and the vast majority were frail (53% had FI-a > 0.2). Residents with dementia had a higher FI-t compared with those without dementia (0.278 ± 0.110 vs. 0.272 ± 0.108), whereas residents without dementia had a higher FI-n (0.143 ± 0.082 vs. 0.136 ± 0.079). Within 9 years, 97% of the sample had died; a 0.01 increase of the FI-a was associated with a 4% increase of the mortality risk, adjusting for age, sex, admission year, stay length, and dementia type. Residents who developed dementia after admission to long-term care had higher baseline FI-t and FI-a (P's < .003) than those who remained without dementia. CONCLUSIONS AND IMPLICATIONS: Frailty is highly prevalent in older adults living in long-term care, irrespective of the presence or absence of dementia. Accumulation of deficits, either traditionally related or unrelated to dementia, is associated with risks of death and dementia, and more deficits increases the probability. Our findings have implications for improving the quality of care of older adults in long-term care, by monitoring the degree of frailty at admission, managing distinct needs in relation to dementia, and enhancing frailty level-informed care and services.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".