Assessment and management of frailty in individuals living with dementia: expert recommendations for clinical practice
Bibliographic record
Abstract
Frailty complicates the care of individuals with dementia, increasing their vulnerability to adverse outcomes. This Personal View presents expert recommendations for managing frailty in individuals with dementia, aimed at health-care providers, particularly those in primary care. We conducted a rapid literature review followed by a consensus process involving 18 international experts on dementia and frailty. The experts identified key areas, including diagnosis of frailty, assessment of nutritional status and nutritional management, physical activity, prevention of falls, and polypharmacy management. The recommendations emphasise early identification of frailty and a comprehensive, interdisciplinary approach to care that aims to maintain the individual's daily functioning, quality of life, and independence. The recommendations highlight the importance of tailored interventions, regular monitoring, and the integration of psychosocial support into the therapeutic approach. These recommendations address a crucial gap in existing clinical guidelines, offering practical guidance for clinicians managing frailty in individuals with dementia.
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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 | 0.010 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".