Development and validation of a frailty index based on Australian Aged Care Assessment Program data
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: To develop and validate a frailty index, derived from aged care eligibility assessment data. DESIGN: Retrospective cohort study; analysis of the historical national cohort of the Registry of Senior Australians (ROSA). PARTICIPANTS: 903 996 non-Indigenous Australians aged 65 years or more, living in the community and assessed for subsidised aged care eligibility during 2003-2013. MAIN OUTCOME MEASURES: 44-item frailty index; summary statistics for frailty index score distribution; predictive validity with respect to mortality and entry into permanent residential aged care during the five years after assessment. RESULTS: The mean frailty index score during 2003-2013 was 0.20 (SD, 0.07; range, 0-0.41); the proportion of assessed older people with scores exceeding 0.20 increased from 32.1% in 2003-2005 to 75.0% in 2012-2013. The risks of death and entry into permanent residential aged care at one, three and five years increased with frailty index score level (at one year, high [over 0.35] v low scores [under 0.05]: hazard ratio for death, 5.99; 95% CI, 5.69-6.31; for entry into permanent residential aged care, 8.70; 95% CI, 8.32-9.11). The predictive validity (area under the receiver operating characteristic curve) of Cox proportional hazard models including age, sex, and frailty index score was 0.64 (95% CI, 0.63-0.64) for death and 0.63 (95% CI, 0.62-0.63) for entry into permanent residential aged care within one year of assessment. CONCLUSIONS: We used Australian aged care eligibility assessment program data to construct and validate a frailty index. It can be employed in aged care research in Australia, but its application to aged care planning requires further investigation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it