Frailty prevalence and efficient screening in primary care-based memory clinics
Bibliographic record
Abstract
BACKGROUND: Little is known about the prevalence of frailty among patients with memory concerns attending a primary care-based memory clinic. OBJECTIVE: This study aims to describe the prevalence of frailty among patients attending a primary care-based memory clinic and to determine if prevalence rates differ based on the screening tool that is used. METHODS: We conducted a retrospective medical record review for all consecutive patients assessed in a primary care-based memory clinic over 8 months. Frailty was measured in 258 patients using the Fried frailty criteria, which relies on physical measures, and the Clinical Frailty Scale (CFS), which relies on functional status. Weighted kappa statistics were calculated to compare the Fried frailty and the CFS. RESULTS: The prevalence of frailty was 16% by Fried criteria and 48% by the CFS. Agreement between Fried frailty and CFS was fair for CFS 5+ (kappa = 0.22; 95% confidence interval: 0.13, 0.32) and moderate for CFS 6+ (kappa = 0.47; 0.34, 0.61). Dual-trait measures of hand grip strength with gait speed were found to be a valid proxy for Fried frailty phenotype. CONCLUSIONS: Among primary care patients with memory concerns, frailty prevalence rates differed based on the measure used. Screening for frailty in this population using measures relying on physical performance may be a more efficient approach for persons already at risk of further health instability from cognitive impairment. Our findings demonstrate how measure selection should be based on the objectives and context in which frailty screening occurs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".