Evidence map›Paper›PMID 37029436›Full record

ArticleScandinavian journal of trauma, resuscitation and emergency medicine2023

Diagnostic accuracy of clinical examination to identify life- and limb-threatening injuries in trauma patients.

Jared M Wohlgemut, Max E R Marsden, Rebecca S Stoner, Erhan Pisirir, Evangelia Kyrimi, Gareth Grier, Michael Christian, Thomas Hurst, William Marsh, Nigel R M Tai and 1 more

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Scandinavian journal of trauma, resuscitation and emergency medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07634185 (Clinical Evaluation of an AI Risk Prediction and Decision Support System for Early Management of Injured Patients), which is not on this map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
10.1field-weighted citation impact, top 1% of its field
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.

NCT07634185 early_phase1not yet recruitingnot on this mapstarted 2026, after this paper: background citation

Clinical Evaluation of an AI Risk Prediction and Decision Support System for Early Management of Injured Patients: a Stepped-wedge Cluster Randomised Trial

TypeinterventionalSponsorQueen Mary University of LondonRan2026 to 2027Enrolled1,200ConditionsTrauma, Injury, Decision Support Systems, ClinicalArmsAI-TRiPS Device
3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.

  1. Guideline
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  7. Review
  8. Epidemiology of prehospital traumatic cardiac arrest in Geneva: a retrospective cohort study.Scandinavian journal of trauma, resuscitation and emergency medicine · 2025
    Article
  9. Article
  10. Article
  11. Vehicle extrication in road traffic crashes: a descriptive analysis of an advanced medical rescue service in South Africa.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2025
    Article
  12. Article
  13. Review
  14. Accuracy between prehospital and hospital diagnosis in helicopter emergency medical services and its consequences for trauma care.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2024
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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

11 authors at 2 institutions in 1 country.

Jared M WohlgemutCentre for Trauma Sciences, Blizard Institute, Queen Mary University of London, London, UK. jwohlgemut@nhs.net.ORCID http://orcid.org/0000-0001-8276-0465
Max E R MarsdenCentre for Trauma Sciences, Blizard Institute, Queen Mary University of London, London, UK.
Rebecca S StonerCentre for Trauma Sciences, Blizard Institute, Queen Mary University of London, London, UK.
Erhan PisirirDepartment of Electrical Engineering and Computer Science, Queen Mary University of London, London, UK.
Evangelia KyrimiDepartment of Electrical Engineering and Computer Science, Queen Mary University of London, London, UK.
Gareth GrierLondon's Air Ambulance, Royal London Hospital, Barts Health NHS Trust, London, UK.
Michael ChristianLondon's Air Ambulance, Royal London Hospital, Barts Health NHS Trust, London, UK.
Thomas HurstLondon's Air Ambulance, Royal London Hospital, Barts Health NHS Trust, London, UK.
William MarshDepartment of Electrical Engineering and Computer Science, Queen Mary University of London, London, UK.
Nigel R M TaiCentre for Trauma Sciences, Blizard Institute, Queen Mary University of London, London, UK.
Zane B PerkinsCentre for Trauma Sciences, Blizard Institute, Queen Mary University of London, London, UK.
Queen Mary University of London · GBBarts Health NHS Trust · GB

Funding

Combat Casualty Care Research Program DM180044
6 · The paper itself

Abstract

backgroundTimely and accurate identification of life- and limb-threatening injuries (LLTIs) is a fundamental objective of trauma care that directly informs triage and treatment decisions. However, the diagnostic accuracy of clinical examination to detect LLTIs is largely unknown, due to the risk of contamination from in-hospital diagnostics in existing studies. Our aim was to assess the diagnostic accuracy of initial clinical examination for detecting life- and limb-threatening injuries (LLTIs). Secondary aims were to identify factors associated with missed injury and overdiagnosis, and determine the impact of clinician uncertainty on diagnostic accuracy.

methodsRetrospective diagnostic accuracy study of consecutive adult (≥ 16 years) patients examined at the scene of injury by experienced trauma clinicians, and admitted to a Major Trauma Center between 01/01/2019 and 31/12/2020. Diagnoses of LLTIs made on contemporaneous clinical records were compared to hospital coded diagnoses. Diagnostic performance measures were calculated overall, and based on clinician uncertainty. Multivariate logistic regression analyses identified factors affecting missed injury and overdiagnosis.

resultsAmong 947 trauma patients, 821 were male (86.7%), median age was 31 years (range 16-89), 569 suffered blunt mechanisms (60.1%), and 522 (55.1%) sustained LLTIs. Overall, clinical examination had a moderate ability to detect LLTIs, which varied by body region: head (sensitivity 69.7%, positive predictive value (PPV) 59.1%), chest (sensitivity 58.7%, PPV 53.3%), abdomen (sensitivity 51.9%, PPV 30.7%), pelvis (sensitivity 23.5%, PPV 50.0%), and long bone fracture (sensitivity 69.9%, PPV 74.3%). Clinical examination poorly detected life-threatening thoracic (sensitivity 48.1%, PPV 13.0%) and abdominal (sensitivity 43.6%, PPV 20.0%) bleeding. Missed injury was more common in patients with polytrauma (OR 1.83, 95% CI 1.62-2.07) or shock (systolic blood pressure OR 0.993, 95% CI 0.988-0.998). Overdiagnosis was more common in shock (OR 0.991, 95% CI 0.986-0.995) or when clinicians were uncertain (OR 6.42, 95% CI 4.63-8.99). Uncertainty improved sensitivity but reduced PPV, impeding diagnostic precision.

conclusionsClinical examination performed by experienced trauma clinicians has only a moderate ability to detect LLTIs. Clinicians must appreciate the limitations of clinical examination, and the impact of uncertainty, when making clinical decisions in trauma. This study provides impetus for diagnostic adjuncts and decision support systems in trauma.

Indexed as

Abdominal InjuriesMultiple TraumaThoracic InjuriesWounds, NonpenetratingAdolescentAdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesSensitivity and SpecificityYoung AdultClinical examinationDiagnostic accuracyPre-hospital diagnosisTraumatic injuriesUncertainty

Identifiers

PMID37029436
PMCPMC10082501
OpenAlexW4362703847

What OpenQuestion holds

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Registered trials

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.