Identifying Common Characteristics of Frailty Across Seven Scales
Bibliographic record
Abstract
OBJECTIVES: To determine whether commonly used frailty scales exhibit shared characteristics when applied to a representative sample of middle-aged and older Europeans. DESIGN: Secondary analysis of the Survey of Health, Ageing, and Retirement in Europe (SHARE). SETTING: Eleven European countries. PARTICIPANTS: Community-dwelling adults (N = 27,527; mean age 65.3 ± 10.5, 55% female). MEASUREMENTS: Frailty was assessed using SHARE-operationalized versions of seven frailty scales: Edmonton Frail Scale, FRAIL scale, Groningen Frailty Indicator, frailty phenotype, Tilburg Frailty Indicator, a 70-item frailty index (FI), and a 44-item frailty index based on Comprehensive Geriatric Assessment. RESULTS: All frailty scales demonstrated right-skewed density distributions. On all scales, frailty scores increased nonlinearly with age, between 1% (FRAIL) and 3.6% (FI) per year on a log scale. Frailty scores on all scales exhibited dose-response relationships with 5-year mortality. On all scales, women had higher frailty scores than men of the same age but demonstrated better survival than did men with the same frailty score. On all scales except the frailty phenotype, 99% of participants had scores below the scale's theoretical maximum. CONCLUSION: On each frailty scale, frailty score increased nonlinearly with age, mortality risk increased with frailty score, and women had higher scores than men but demonstrated better survival. Each scale except the frailty phenotype demonstrated an upper limit to frailty below the scale's theoretical maximum. Across commonly used frailty scales, these characteristics are common in nature but differ in magnitude.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".