NOA-18-009 Dr. Robert Ohle received a NOAMA grant to adapt and improve current guidelines for Acute Aortic Syndrome (AAS), a rare life-threatening and oft-misdiagnosed condition that results from a tear in the inner wall of the aorta. As there are currently no Canadian guidelines to aid in diagnosis, the goal was to adapt the American Heart Association and European Society of Cardiology diagnostic algorithms for AAS. A National Advisory Committee consisting of 21 members, including academic, community and remote/rural emergency medical practitioners and patient representatives, was created. Using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess evidence and make recommendations, the Committee created the first Canadian best practice diagnostic algorithm for AAS that standardizes and improves diagnosis of AAS in all emergency departments across Canada.

NOA-18-009 Background: Acute aortic syndrome (AAS) is a time sensitive aortic catastrophe that is often misdiagnosed. There are currently no Canadian guidelines to aid in diagnosis. Our goal was to adapt the existing American Heart Association (AHA) and European Society of Cardiology (ESC) diagnostic algorithms for AAS into a Canadian evidence based best practices algorithm targeted for emergency medicine physicians. Methods: We chose to adapt existing high-quality clinical practice guidelines (CPG) previously developed by the AHA/ESC using the GRADE ADOLOPMENT approach. We created a National Advisory Committee consisting of 21 members from across Canada including academic, community and remote/rural emergency physicians/nurses, cardiothoracic and vascular surgeons, cardiac anaesthesiologists, critical care physicians, cardiologist, radiologists and patients representatives. The Advisory Committee communicated through multiple teleconference meetings, emails and a one-day in person meeting. The panel prioritized questions and outcomes, using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess evidence and make recommendations. The algorithm was prepared and revised through feedback and discussions and through an iterative process until consensus was achieved. Test accuracy estimates and AAS population prevalence were used to model expected outcomes in diagnostic pathways. Results: The diagnostic algorithm is comprised of an updated pre-test probability assessment tool with further testing recommendations based on risk level. The updated tool incorporates likelihood of an alternative diagnosis and point of care ultrasound. The final best practice diagnostic algorithm defined risk levels as Low (0.5% no further testing), Moderate (0.5-5% further testing required) and High (>5% computed