Reducing hip and non-vertebral fractures in institutionalised older adults by restoring inadequate intakes of protein and calcium is cost-saving
Bibliographic record
Abstract
BACKGROUND: older adults in aged care account for 30% of the population burden of hip fractures. Nutritional interventions to correct under nutrition reduce these debilitating fractures, perhaps partly by reducing falls and slowing deterioration in bone morphology. OBJECTIVE: to determine whether a nutritional approach to fracture risk reduction in aged care homes is cost-effective. DESIGN: cost-effectiveness was estimated based on results from a prospective 2-year cluster-randomised controlled trial and secondary data. Intervention residents consumed a total of 3.5 daily servings of milk, yoghurt and/or cheese, resulting in 1,142 mg of calcium and 69 g of protein compared with the daily intakes of 700 mg of calcium and 58 g of protein consumed by the control group. SETTING: fifty-six aged care homes. PARTICIPANTS: residents for 27 intervention (n = 3,313) and 29 control (n = 3,911) homes. METHODS: ambulance, hospital, rehabilitation and residential care costs incurred by fracture were estimated. The incremental cost-effectiveness ratios per fracture averted within a 2-year time horizon were estimated from the Australian healthcare perspective applying a 5% discount rate on costs after the first year. RESULTS: intervention providing high-protein and high-calcium foods reduced fractures at a daily cost of AU$0.66 per resident. The base-case results showed that the intervention was cost-saving per fracture averted, with robust results in a variety of sensitivity and scenario analyses. Scaling the benefits of intervention equates to a saving of AU$66,780,000 annually in Australia and remained cost-saving up to a daily food expenditure of AU$1.07 per resident. CONCLUSIONS: averting hip and other non-vertebral fractures in aged care residents by restoring nutritional inadequacy of protein and calcium is cost-saving.
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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 | 0.000 |
| 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 | 0.000 | 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".