A data-driven algorithm to support the clinical decision-making of patient extrication following a road traffic collision

Eyston Vaughan-Huxley, Joanne Griggs, Jasmit Mohindru*, Malcolm Russell, Richard Lyon, Ewoud ter Avest

*Bijbehorende auteur voor dit werk

    OnderzoeksoutputAcademicpeer review

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    Background: Some patients involved in a road traffic collision (RTC) are physically entrapped and extrication is required to provide critical interventions. This can be performed either in an expedited way, or in a more controlled manner. In this study we aimed to derive a data-driven extrication algorithm intended to be used as a decision-support tool by on scene emergency service providers to decide on the optimal method of patient extrication from the vehicle.

    Methods: A retrospective observational study was performed of all trauma patients trapped after an RTC who were attended by a Helicopter Emergency Medical Service (HEMS) in the United Kingdom between March 2013 and December 2021. Variables were identified that were associated with the need for HEMS interventions (as a surrogate for the need for expedited extrication), based on which a practical extrication algorithm was devised.

    Results: During the study period 12,931 patients were attended, of which 920 were physically trapped. Patients who scored an “A” on the AVPU score (n = 531) rarely required HEMS interventions (3%). Those who did were characterised by a shorter than average (29 vs. 37 min) 999/112 emergency call to HEMS on-scene arrival interval. A third of all patients responding to voice required HEMS interventions. Absence of a patent airway (OR 6.98 [1.74–28.03] p <.001) and the absence of palpable radial pulses (OR 9.99 [2.48–40.18] p <.001) were independently associated with the need for (one or more) HEMS interventions in this group. Patients only responding to pain and unresponsive patients almost invariably needed HEMS interventions post extrication (90% and 86% respectively). Based on these findings, a practical and easy to remember algorithm “APEX” was derived.

    Conclusion: A simple, data-driven algorithm, remembered by the acronym “APEX”, may help emergency service providers on scene to determine the preferred method of extrication for patients who are trapped after a road traffic collision. This has the potential to facilitate earlier recognition of a ‘sick’ critical patient trapped in an RTC, decrease entrapment and extrication time, and may contribute to an improved outcome for these patients.

    Originele taal-2English
    Aantal pagina's8
    TijdschriftScandinavian Journal of Trauma, Resuscitation and Emergency Medicine
    StatusPublished - dec.-2023


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