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Record W4396969589 · doi:10.1136/bmjopen-2023-083450

Research priorities for the management of major trauma: an international priority setting partnership with the James Lind Alliance

2024· article· en· W4396969589 on OpenAlexaff
Chris Bretherton, Robert Hirst, Hamez Gacaferi, Jonathan Gower, Lauren Exell, Scott G. Johnston, Shan Martin, Caroline Leech, Catherine Hilton, Ceri Battle, Daniel Axelrod, Heather A. Vallier, Daphne Van Embden, David J. Stockton, Elaine Cole, Julia Williams, Louise Johnson, Maritz Laubscher, Melissa Webb, Philip Braude, Sarah Norris, Steve Bell, Sithombo Maqungo, Xavier L Griffin

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldMedicine
TopicTrauma and Emergency Care Studies
Canadian institutionsUniversity of British ColumbiaMcMaster University
FundersNational Institute for Health and Care ResearchBarts Charity
KeywordsMedicineAllianceGeneral partnershipLaw

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.238
GPT teacher head0.513
Teacher spread0.276 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations11
Published2024
Admission routes1
Has abstractyes

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