A cross‐sectional comparison of the use of frailty assessment tools in older people living with <scp>HIV</scp>
Bibliographic record
Abstract
OBJECTIVES: Advancements in the management of HIV have resulted in an increasing aging population with rising rates of frailty. Frailty represents a state of vulnerability to stressor events. There is a lack of consensus regarding the most appropriate assessment tool for frailty in this population. Our aim was to compare a number of frailty assessment tools among a sample population of older people living with HIV. METHODS: Two hundred and fifty three participants aged over 50 years (median 59.6 years) were recruited between October 2014 and September 2015. Frailty was defined by modified Fried Frailty Phenotype (FFP). Participants were assessed via seven further screening tools (Clinical Frailty Scale, Edmonton Frailty Score, FRAIL scale, Gait Speed, SHARE-FI, Study of Osteoporotic Fractures Index and Timed Up and Go [TUG]). We evaluated the diagnostic performance of each tool by generating ROC curves and calculating specificity and sensitivity. RESULTS: Using the FFP tool, 48/253 met frailty criteria, reflecting a prevalence of 19% (95% CI 14.6-24.3). A total of 32% of individuals were identified as frail by any of the eight tools. Sensitivity of the tools was highly variable, though all showed good specificity. Timed Up and Go (TUG) assessment performed most closely to FFP (AUROC 0.82 [95% CI 0.753-0.889]). CONCLUSIONS: TUG is a potentially useful frailty screening tool in the assessment of older people living with HIV. Strengths include an objective measure with high sensitivity and specificity and relatively low resource cost. Further exploration in this field is required to assess the correlation between frailty assessment and clinically significant outcomes, including morbidity and mortality.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".