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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".