Frailty in Older Adults with Mild Dementia: Dementia with Lewy Bodies and Alzheimer’s Disease
Bibliographic record
Abstract
Introduction: The aim of the study is to describe the frequency of frailty in people with a new diagnosis of mild dementia due to Alzheimer’s disease (AD) and dementia with Lewy bodies (DLB). Methods: This is a secondary analysis of the Dementia Study of Western Norway (Demvest). For this study, we analysed a sample of 186 patients, 116 with AD and 70 with DLB. Subjects were included at a time in which mild dementia was diagnosed according to consensus criteria after comprehensive standardized assessment. Frailty was evaluated retrospectively using a frailty index generated from existing data. The cut-off value used to classify an older adult as frail was 0.25. Results: The prevalence of frailty was 25.81% (n = 48). In the DLB group, 37.14% (n = 26) were classified as frail, compared to 18.97% (n = 22) of those with AD (p < 0.001). The adjusted multivariate analysis revealed an OR of 2.45 (1.15–5.23) for being frail in those with DLB when using AD as the reference group. Conclusion: Frailty was higher than expected in both types of dementia. The prevalence of frailty was higher in those with DLB compared to AD. This new finding underscores the need for a multi-systems approach in both dementias, with a particular focus on DLB.
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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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".