Ambulance smartphone tool for field triage of ruptured aortic aneurysms (FILTR): study protocol for a prospective observational validation of diagnostic accuracy

Abstract

IntroductionRupture of an abdominal aortic aneurysm (rAAA) carries a considerable mortality rate and is often fatal. rAAA can be treated through open or endovascular surgical intervention and it is possible that more rapid access to definitive intervention might be a key aspect of improving mortality for rAAA. Diagnosis is not always straightforward with up to 42% of rAAA initially misdiagnosed, introducing potentially harmful delay. There is a need for an effective clinical decision support tool for accurate prehospital diagnosis and triage to enable transfer to an appropriate centre.Methods and analysisProspective multicentre observational study assessing the diagnostic accuracy of a prehospital smartphone triage tool for detection of rAAA. The study will be conducted across London in conjunction with London Ambulance Service (LAS). A logistic score predicting the risk of rAAA by assessing ten key parameters was developed and retrospectively validated through logistic regression analysis of ambulance records and Hospital Episode Statistics data for 2200 patients from 2005 to 2010. The triage tool is integrated into a secure mobile app for major smartphone platforms. Key parameters collected from the app will be retrospectively matched with final hospital discharge diagnosis for each patient encounter. The primary outcome is to assess the sensitivity, specificity and positive predictive value of the rAAA triage tool logistic score in prospective use as a mob app for prehospital ambulance clinicians. Data collection started in November 2014 and the study will recruit a minimum of 1150 non-consecutive patients over a time period of 2 years.Ethics and disseminationFull ethical approval has been gained for this study. The results of this study will be disseminated in peer-reviewed publications, and international/national presentations.Trial registration numberCPMS 16459; pre-results.

Development and Validation of a Prediction Model for Prehospital Triage of Trauma Patients

“…This problem could be solved by implementing the prediction model in a mobile app; such triage tools are increasingly being developed and used in the prehospital process. 8,9 This mobile app includes every variable, calculates the chance of severe injury, and gives advice on where to transport the patient, which is much more practical for EMS professionals compared with an equation. With a mobile device available on every ambulance, the EMS professionals can calculate the risk of severe injury using the prediction model in the app to decide quickly and more accurately where to transport the patient.…”

“…[5][6][7] All are simplistic and static tools, whereas patients are dynamic, and more advanced methods are available to use on the scene, such as a prediction model in a mobile app. 8,9 Undertriage occurs when severely injured patients are not transported to a higher-level trauma center and results in delayed care and increased mortality and morbidity. 1,2 Overtriage occurs when patients without severe injuries are taken to a higher-level trauma center, often incurring preventable cost and resource consumption.…”

The role of emergency medical service providers in the decision-making process of prehospital trauma triage

“…This prediction model could be integrated in a mobile app, so the EMS provider can calculate the risk of a severe injury quickly and more accurately on-scene. Triage tools integrated in a mobile app are increasingly being developed and used in the prehospital process [42,43]. The prediction model would include predictors of a severe injury such as age, vital signs, mechanism of injury and injured body regions.…”

A look to the future: Pandemic-induced digital technologies in vascular surgery

“…With the uptake of clinical management protocols, point-of-care tools can act as decision support tools, improving the consistency of care [74] , relieving the cognitive load on clinicians in high-stress situations, or permitting task substitution such that less experienced clinical staff can execute such protocols. Examples of mobile tools for clinical staging or decision making include phone-based field tools for ruptured abdominal aortic aneurysm recognition and triage by paramedics [75] and apps released by the Society for Vascular Surgery (SVS), including risk calculators and staging tools for mortality of critical limb threatening ischemia based on the Vascular Quality Initiative dataset, a WIfI (wound, ischemia, and foot infection) staging calculator for classification of the threatened limb, and a Global Limb Anatomic Staging System calculator [76] .…”