Evaluation of interventions for trauma care in older adults: a consensus study
Bibliographic record
Abstract
BACKGROUND: Trauma care of older adults is an important and growing public health issue. Countries such as the United States and United Kingdom have published best-practice guidelines on the management of older trauma patients. In Australia, there are no such guidelines. Australian guidelines are needed as there are unique contextual challenges, including low population density and large distances between the site of injury and where treatment is administered. AIMS: To determine which interventions for managing older trauma patients should be prioritised for inclusion in national guidelines. METHODS: A consensus method with two survey rounds was conducted with a range of health professionals involved in delivering trauma care for older adults. In round 1, participants were asked which of 28 interventions should be included in national guidelines. Consensus was defined as ≥80% agreement. In round 2, participants ranked interventions in order of priority for inclusion in guidelines. Interventions were classified into pre-hospital care, in-hospital initial assessment, inpatient care, transition care and education. RESULTS: A total of 32 and 25 participants completed rounds 1 and 2 of the survey respectively. Of 28 interventions proposed for national guidelines, 15 reached consensus. Key priority interventions included geriatric-specific triage, documented goals of care, trauma team activation criteria, multidisciplinary geriatric care and training modules in older trauma care. CONCLUSIONS: This study identified 15 interventions that trauma clinicians agreed should be considered for inclusion in guidelines for the management of older adult trauma. Given the burden of older adult trauma, a national consensus guideline should be prioritised and a working group formed.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".