The publications listed in the Additional information are the main outputs and form the basis for impact and learning arising from the study. We plan to present our findings at professional meetings, including the RCEM Annual Scientific Meeting, the European Society for Emergency Medicine Annual Conference, and the Society for Medical Decision Making.
We will share summaries of our findings, supported by peer-reviewed publications, with professional organisations involved in delivering clinical care for suspected AAS (RCEM, RCR, Vascular Society of Great Britain and Ireland, British Society of Interventional Radiology). We will share plain language summaries of our findings with patient organisations involved in improving care for suspected AAS (Aortic Dissection Awareness, the Aortic Dissection Charitable Trust).
The main UK guidelines for the diagnosis of AAS are the RCEM/RCR Best Practice Guidelines. We will draw upon our contacts with the guideline authors to ensure that they are aware of our findings. We will provide tailored information showing how the guidelines might develop in the light of our findings and offer to work with the guideline authors to help them to draw upon our findings.
We will also share our findings with the developers of the ESC guidelines,5 the European Society for Vascular Surgery guidelines (https://esvs.org/guidelines/) and the AHA/American College of Cardiology guidelines.21
We will use our contacts with the Aortic Dissection Charitable Trust and Aortic Dissection Awareness to ensure awareness of our findings. We will provide tailored information to show how information provided by each organisation and relevant campaigns, such as the Think Aorta campaign, could be developed in the light of our findings.
We produce plain language information summarising our findings and work with the Aortic Dissection Charitable Trust, using mainstream media and social media, to promote public awareness of our findings.
The impact of this evidence synthesis project will largely be achieved through future primary research, as identified in the research recommendations. The James Lind Alliance Emergency Medicine Priority Setting Partnership Refresh 2022 identified diagnosis of AAS in the ED as the seventh top priority (https://rcem.ac.uk/research-priorities/), and diagnosis of AAS is also currently the third top priority in the James Lind Alliance Aortic Priority Setting Partnership (www.jla.nihr.ac.uk/priority-setting-partnerships/vascular-conditions/aortic-top-10-priorities.htm). Our findings will feed into research proposals developing from these prioritisations.
We will share the research recommendations outlined in Research recommendations with research funders, including National Institute for Health and Care Research (NIHR), UK Research and Innovation Medical Research Council (MRC), British Heart Foundation and Heart Research UK, and feed our findings into research priority setting exercises.
The RCEM funded Aortic Syndrome Evidence Synthesis (ASES) coinvestigators Matthew Reed and Sarah Wilson to undertake the DAShED study33 alongside our study. This multicentre observational cohort study of 5548 patients, with potential symptoms of AAS attending 27 hospitals across the UK, showed that 0.3% (14 patients) had AAS, while 7% received CTA. The findings were included in our systematic reviews, used to populate our decision-analytic model and will inform future research proposals around AAS diagnosis.
The DAShED study33 provided essential data to develop our model, put our findings into context and understand the problem of suspected AAS. The involvement of 27 hospitals and the Trainee Emergency Research Network, along with support from the RCEM and Aortic Dissection Charitable Trust, provide a valuable network for developing future research proposals.
The Aortic Dissection Charitable Trust has funded the Rapid Acute Aortic Syndrome Diagnosis using Artificial Intelligence study,131 led by Jim Zhong and involving ASES coinvestigators Matthew Reed, Graham Cooper, Sarah Wilson and Steve Goodacre. This study aims to use the DAShED data to develop a machine learning decision support system to assist AAS diagnosis in the ED.
In response to the James Lind Alliance prioritisation of AAS diagnosis, the RCEM Research Engagement and NIHR Emergency Care Incubator meetings have included sessions on developing research into AAS diagnosis. Matthew Reed facilitated these sessions and is developing a research network based on the DAShED study to undertake future multicentre research into AAS diagnosis. We plan to build upon the links we made with international researchers while undertaking the meta-analysis of ADD-RS and D-dimer to develop international collaborative research into AAS diagnosis.