Frailty prevalence in Australia: Findings from four pooled Australian cohort studies
Bibliographic record
Abstract
OBJECTIVE: To examine frailty prevalence in Australian older adults. METHODS: Frailty was measured using a modified Fried Frailty Phenotype (FFP) in a combined cohort of 8804 Australian adults aged ≥65 years (female 86%, median age 80 (79-82) years) from the Dynamic Analyses to Optimise Ageing Project and the North West Adelaide Health Study. RESULTS: Using the FFP, 21% of participants were frail while a further 48% were prefrail. Chi-squared testing of frailty among four age groups (65-69, 70-74, 75-79 and 80-84 years) for sex, and marital status revealed that frailty was significantly higher for women (approximately double that of men), increased significantly with advancing age for both sexes, and was significantly higher for women who were widowed, divorced or never married. CONCLUSION: If frailty could be prevented or reversed, it would have an impact on a larger number of older people.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".