Research priorities for the management of major trauma: an international priority setting partnership with the James Lind Alliance
Bibliographic record
Abstract
OBJECTIVE: The objective of this study is to determine research priorities for the management of major trauma, representing the shared priorities of patients, their families, carers and healthcare professionals. DESIGN/SETTING: An international research priority-setting partnership. PARTICIPANTS: People who have experienced major trauma, their carers and relatives, and healthcare professionals involved in treating patients after major trauma. The scope included chest, abdominal and pelvic injuries as well as major bleeding, multiple injuries and those that threaten life or limb. METHODS: A multiphase priority-setting exercise was conducted in partnership with the James Lind Alliance over 24 months (November 2021-October 2023). An international survey asked respondents to submit their research uncertainties which were then combined into several indicative questions. The existing evidence was searched to ensure that the questions had not already been sufficiently answered. A second international survey asked respondents to prioritise the research questions. A final shortlist of 19 questions was taken to a stakeholder workshop, where consensus was reached on the top 10 priorities. RESULTS: A total of 1572 uncertainties, submitted by 417 respondents (including 132 patients and carers), were received during the initial survey. These were refined into 53 unique indicative questions, of which all 53 were judged to be true uncertainties after reviewing the existing evidence. 373 people (including 115 patients and carers) responded to the interim prioritisation survey and 19 questions were taken to a final consensus workshop between patients, carers and healthcare professionals. At the final workshop, a consensus was reached for the ranking of the top 10 questions. CONCLUSIONS: The top 10 research priorities for major trauma include patient-centred questions regarding pain relief and prehospital management, multidisciplinary working, novel technologies, rehabilitation and holistic support. These shared priorities will now be used to guide funders and teams wishing to research major trauma around the globe.
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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 | 0.230 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.003 | 0.033 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".