Evidence map›Paper›PMID 40790207›Full record

ArticleScandinavian journal of trauma, resuscitation and emergency medicine2025

Optimising the care of the trapped patient following a motor vehicle collision: A UK-Based Delphi consensus study.

Tim Nutbeam, Rob Fenwick, Ian Marritt, Brian Lee, Luke Staveley-Wadham, Nigel Lang, Louise Johnson, Nicolas Mattock, Jane Ogilvie, Emily Foote and 3 more

Abstract readConsensus Statement
In one paragraph

Article in Scandinavian journal of trauma, resuscitation and emergency medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Tim NutbeamIMPACT, Centre for Post-Collision Research Innovation and Translation, Exeter, UK. timnutbeam@nhs.net.ORCID http://orcid.org/0000-0003-0814-9240
Rob FenwickIMPACT, Centre for Post-Collision Research Innovation and Translation, Exeter, UK.ORCID http://orcid.org/0000-0002-8340-3109
Ian MarrittUnited Kingdom Rescue Organisation, World Rescue Organisation, Humberside Fire and Rescue, Humberside, UK.ORCID http://orcid.org/0009-0005-7638-8528
Brian LeePatient and Public Representative, IMPACT; Centre for Post-Collision Research Innovation and Translation, Exeter, UK.
Luke Staveley-WadhamUniversity Hospitals Plymouth NHS Trust, Plymouth, UK.ORCID http://orcid.org/0009-0009-8016-039X
Nigel LangDevon Air Ambulance, Exeter, UK.ORCID http://orcid.org/0000-0001-7044-3489
Louise JohnsonLeeds Teaching Hospitals NHS Trust, Leeds, UK.ORCID http://orcid.org/0000-0003-4655-8141
Nicolas MattockNational Police Chiefs' Council , London, UK.ORCID http://orcid.org/0000-0001-8659-3756
Jane OgilvieScottish Fire and Rescue Service, Perth, UK.
Emily FooteUniversity Hospitals Plymouth NHS Trust, Plymouth, UK.ORCID http://orcid.org/0009-0006-3699-3122
Francis ScreechUniversity Hospitals Plymouth NHS Trust, Plymouth, UK.ORCID http://orcid.org/0009-0004-3628-9851
Lara Lebeau-HumarauUniversity of Plymouth, Plymouth, UK.ORCID http://orcid.org/0009-0003-6883-0473
Caroline LeechUniversity Hospitals Coventry & Warwickshire NHS Trust, Coventry, UK.ORCID http://orcid.org/0000-0002-5301-9798

Funding

Road Safety Trust EXIT
6 · The paper itself

Abstract

backgroundMotor vehicle collisions (MVCs) are a leading cause of injury and death worldwide. Up to 40% of casualties may become trapped and entrapment is associated with delayed care and worse outcomes. There is little national or international consensus guiding the care of physically trapped patients who cannot self-extricate. This study aimed to develop multidisciplinary consensus-based principles to optimise clinical and operational care for trapped patients following MVC.

methodsA three-round Delphi study was conducted from January to March 2025, following the CREDES framework. A multi-professional steering group developed preliminary statements informed by literature review and expert consultation. Subject matter experts (SMEs) with operational experience in extrication, prehospital, and trauma care were recruited through stakeholder organisations. Statements were refined iteratively through SME feedback. Consensus was defined as ≥ 70% agreement or disagreement. Statements reaching consensus were removed from subsequent rounds; others were revised based on free-text feedback.

resultsSixty-six SMEs participated, with high engagement across all three rounds. Consensus was achieved for 104 statements covering standardised extrication terminology, prioritisation of time-sensitive extrication for critically injured patients, minimisation of unnecessary on-scene interventions, emphasis on early psychological support for trapped casualties, and the importance of interdisciplinary communication and coordination. The consensus supports a paradigm shift towards rapid, patient-centred extrication, balancing clinical needs, operational realities, and psychological welfare.

conclusionsThis Delphi study establishes expert-endorsed principles for the care of physically trapped patients following MVCs. Adoption of these principles could reduce delays, strengthen multi-agency response and improve patient outcomes. Further work is required to validate the impact of these recommendations on clinical outcomes and to support their integration into practice through policy development, training, and evaluation.

Indexed as

Accidents, TrafficEmergency Medical ServicesWounds and InjuriesDelphi TechniqueHumansMaleUnited KingdomEmergency medical servicesExtricationPrehospital careRescueRoad injuryTrapped

Identifiers

PMID40790207
PMCPMC12337359

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.