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dc.contributor.authorShanahan, TAG
dc.contributor.authorFuller, GW
dc.contributor.authorSheldon, T
dc.contributor.authorTurton, E
dc.contributor.authorQuilty, FMA
dc.contributor.authorMarincowitz, C
dc.date.accessioned2021-03-26T16:14:51Z
dc.date.available2021-01-22
dc.date.available2021-03-26T16:14:51Z
dc.date.issued2021-01-28
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/70907
dc.description.abstractIMPORTANCE: This 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. OBJECTIVE: To externally validate the Dutch prediction model for identifying major trauma in a large unselected prehospital population of injured patients in England. DESIGN: External validation using a retrospective cohort of injured patients who ambulance crews transported to hospitals. SETTING: South West region of England. PARTICIPANTS: All patients ≥16 years with a suspected injury and transported by ambulance in the year from February 1, 2017. EXCLUSION CRITERIA: 1) 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 EXPOSURES: Tested 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 MEASURE: Major trauma defined as an Injury Severity Score>15. RESULTS: A 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 RELEVANCE: The 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.en_US
dc.languageeng
dc.relation.ispartofInjury
dc.titleExternal validation of the Dutch prediction model for prehospital triage of trauma patients in South West region of England, United Kingdom.en_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.injury.2021.01.039
pubs.author-urlhttps://www.ncbi.nlm.nih.gov/pubmed/33581872en_US
pubs.notesNot knownen_US
pubs.publication-statusPublished onlineen_US
pubs.publisher-urlhttps://doi.org/10.1016/j.injury.2021.01.039
dcterms.dateAccepted2021-01-22
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US


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