Flitr Logo FINAL

Download the App From

The Google Play Store for Android or The App Store for iOS.
You will need to use the registration code: LAS

What is a ruptured aneurysm, why are they hard to identify and why is this a problem?

An Aortic Aneurysm (AAA) is a diseased weakening of the body’s largest artery. Ruptured aneurysms (rAAA) affect at least 3000 NHS patients/year, and are fatal without urgent lifesaving surgery. The problem is that aneurysm surgery can only be performed in a few regional specialist centres.

Why are they hard to identify? Why is this a problem?

Identifying ruptured aneurysms at the scene of the emergency is tricky, and about half are initially misdiagnosed. Patients are often collapsed and seriously ill, and taken quickly to the nearest hospital. If an aneurysm is discovered, this often requires a second journey to the specialist centre for aneurysm surgery. The delay can be fatal.

Why is our current care not good enough?

Death from a ruptured aorta – the main blood vessel from the heart – is more likely in English hospitals than in the USA, where patients have a better chance of getting an operation that could save their lives. It is possible that if we could improve our ability to detect these ruptured aneurysms at the scene of the emergency, more patients might get lifesaving surgery.

What is Aneurysm FILTR?

Aneurysm FILTR is a trial of a smartphone app to help ambulance crews diagnose ruptured aortic aneurysms (rAAA) at the scene of the emergency.

We need about 100 volunteer paramedics/ EMTs or trainee paramedics to download our simple smartphone scoring system. The app should take about 15 seconds to use, and only asks for routine information you already collect in the PRF.

For a 12-month period, LAS crew will use the app to record the "aneurysm score" of patients observationally - meaning patient triage/care will be unaltered. The app won’t tell you whether or not the patient might have an aneurysm – as we need to prove it works before it is used to alter patient care! Any patient aged >18 with abdominal/back/chest pain or collapse will be included in the study. Patients currently triaged as myocardial infarction, stroke or trauma are excluded.

Each smartphone will upload data to a secure, anonymised database. The FILTR trial manager will talk to receiving hospitals to discover each patient’s final diagnosis.

This will tell us whether or not our app really can identify patients with rAAA. We will assess feasibility by reporting the time taken to use the software, and asking your feedback on ease-of-use.

Ethics, Funding & Approvals

The study has been approved by ethics committee and adopted on the NIHR portfolio. Initial funding has been provided by the Academy of Medical Sciences, and the team are working on further grant applications.

Meet the study team

Principal Investigator:

Alan Karthikesalingam, NIHR Clinical Academic Lecturer in Vascular Surgery, St George’s Vascular Insitute.


  • Fionna Moore, Medical Director, London Ambulance Service
  • Mark Whitbread, Director of Paramedic Education & Development, London Ambulance Service
  • Michael Damiani, Deputy Information Manager, London Ambulance Service
  • Rachael Fothergill, Head of clinical audit and research, London Ambulance Service
  • Peter Holt, NIHR Senior Lecturer in Vascular Surgery, St George’s Vascular Institute
  • Rob Hinchliffe, Reader in Vascular Surgery, St George’s Vascular Institute
  • Matt Thompson, Professor of Vascular Surgery, St George’s Vascular Institute
  • Shaneel Patel & Bilal Azhar, Core Surgery Trainees
  • Cían Hughes, NIHR Academic Clinical Fellow in Surgery
  • Alberto Vidal-Diez & Jan Poloniecki, Statisticians, St George’s Vascular Institute
  • Sandeep Bahia, Research Fellow in Vascular Surgery, St George’s Vascular Institute
  • Anne Cheetham, Lay Representative to NICE/NIHR and Circulation Foundation Patient Representative
  • Heather Jarman, Clinical Director for Major Trauma, Consultant Nurse in Emergency Care
  • Local Co-Ordinators:

  • SW London: Mr Sandeep Bahia
  • NW London: Ms Mahim Qureshi
  • NE London: Mr Bilal Azhar
  • SE London: Mr Gnananandan Janakan
  • How can you get involved?

    The trial is open to all LAS crew members dealing with acutely ill patients: paramedics, trainees, and techs.

    You only need a working smartphone (Android or iPhone are supported).

    Come to our training days:
    12 November 2014 18:00 in Lecture Theatre F at St George’s Hospital, Tooting
    11 December 2014 18:00 in The Paterson Centre at St Mary's Hospital, Paddington
    19 January 2015 18:00 in Seminar Room LNB_00_293 (Ground Floor, Central Tower) at The Royal London Hospital, Whitechapel
    20 January 2015 18:30 at Croydon Ambulance Station (To book a place email jaqualine.lindridge@lond-amb.nhs.uk).
    16 February 2015 18:00 in The Brian Drewe Lecture Theatre (of the Reynolds Building) at Charing Cross Hospital, accessed from St Dunstan's or Margravine Road
    18 February 2015 14:00 EFP (evidence for practice) event at London Ambulance HQ, Waterloo Road
    5 March 2015 18:00 Conference room, London Ambulance HQ, Waterloo Road
    8 April 2015 18:00 4th Floor East Seminar Room at Charing Cross Hospital, Fulham Palace Road
    19 June 2015 14:00 Conference room, London Ambulance HQ, Waterloo Road

    Please email akarthik@sgul.ac.uk to register your interest.

    What do you get in return for joining the project?

    We want LAS crew to be active members of the FILTR team and shape the way this research is used to benefit patients. Any LAS crew recruiting patients will have the opportunity to be listed in the acknowledgements of all resulting scientific publications. Any LAS crew recruiting over 100 patients will be invited to join publication authorship teams. We will host regular “trial recruitment” and “trial update” days and hope to keep you up to date with progress regularly throughout the study. Participation is entirely voluntary.

    Download the App From

    The Google Play Store for Android or The App Store for iOS.

    You will need to use the registration code: LAS