• Thomas A G Shanahan, FullerGordon WardGWCentre for Urgent and Emergency Care Research, School of Health and Related Research, University of Sheffield, Regent Court, 30 Regent Street, Sheffield, S1 4DA, UK. Electronic address: G.fuller@sheffield.ac.uk., Trevor Sheldon, Emily Turton, Fionn Michael Appleton Quilty, and Carl Marincowitz.
• University of Manchester, Faculty of Biology, Medicine and Health, School of Medical Sciences, Division of Cardiovascular Sciences, Oxford Road, Manchester, M13 9PL. Electronic address: Thomas.shanahan1@nhs.net.
• Injury. 2021 May 1; 52 (5): 1108-1116.

ImportanceThis paper investigates the use of a major trauma prediction model in the UK setting. We demonstrate that application of this model could reduce the number of patients with major trauma being incorrectly sent to non-specialist hospitals. However, more research is needed to reduce over-triage and unnecessary transfer to Major Trauma Centres.ObjectiveTo externally validate the Dutch prediction model for identifying major trauma in a large unselected prehospital population of injured patients in England.DesignExternal validation using a retrospective cohort of injured patients who ambulance crews transported to hospitals.SettingSouth West region of England.ParticipantsAll patients ≥16 years with a suspected injury and transported by ambulance in the year from February 1, 2017.Exclusion Criteria1) Patients aged ≤15 years; 2) Non-ambulance attendance at hospital with injuries; 3) Death at the scene and; 4) Patients conveyed by helicopter. This study had a census sample of cases available to us over a one year period.Interventions Or ExposuresTested the accuracy of the prediction model in terms of discrimination, calibration, clinical usefulness, sensitivity and specificity and under- and over triage rates compared to usual triage practices in the South West region.Main Outcome MeasureMajor trauma defined as an Injury Severity Score>15.ResultsA total of 68799 adult patients were included in the external validation cohort. The median age of patients was 72 (i.q.r. 46-84); 55.5% were female; and 524 (0.8%) had an Injury Severity Score>15. The model achieved good discrimination with a C-Statistic 0.75 (95% CI, 0.73 - 0.78). The maximal specificity of 50% and sensitivity of 83% suggests the model could improve undertriage rates at the expense of increased overtriage rates compared with routine trauma triage methods used in the South West, England.Conclusions And RelevanceThe Dutch prediction model for identifying major trauma could lower the undertriage rate to 17%, however it would increase the overtriage rate to 50% in this United Kingdom cohort. Further prospective research is needed to determine whether the model can be practically implemented by paramedics and is cost-effective.Copyright © 2021. Published by Elsevier Ltd.

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