What Is the Specificity of the Aortic Dissection Detection Risk Score in a Low‐prevalence Population?

Background Acute aortic syndrome ( AAS ) is a time‐sensitive and difficult‐to‐diagnose aortic emergency. The American Heart Association ( AHA ) proposed the acute aortic dissection detection risk score ( ADD ‐ RS ) as a means to reduce miss rate and improve time to diagnosis. Previous validation studies were performed in a high prevalence population of patients. We do not know how the rule will perform in a lower‐prevalence population. This is important because application of a rule with low specificity would increase imaging rates and complications. Our goal was to assess if the diagnostic accuracy of the score would be maintained in a low‐prevalence population that we are attempting to risk stratify in the emergency department ( ED ). Methods Retrospective cohort of patients age 18 years old and older who presented to two tertiary care ED s from January 1, 2015, to December 31, 2015, and underwent a computed tomographic angiography to rule out AAS . Two trained reviewers extracted data using a standardized data collection form. AAS was defined according to accepted radiologic standards. The components of the AHA risk score were defined a priori. Agreement was measured using kappa statistic. Sensitivity, specificity, and positive and negative likelihood ratios with 95% confidence intervals ( CI s) were calculated. Analysis was performed using SAS 9.4 University Edition. Results A total 370 patients underwent computed tomography for suspected AAS . Chief presenting symptoms were chest pain (207, 58%), back pain (26, 7%), abdominal pain (32, 8.6%), syncope (7, 2.6%), and symptoms of stroke (6, 1.6%). AAS was finally diagnosed in 12 (3.2%) patients: five (1.4%) type A aortic dissection, four (1%) type B aortic dissection, two (0.5%) an aortic intramural hematoma, no penetrating aortic ulcer, and one a ruptured abdominal aortic aneurysm. The presence of one or more ADD risk markers ( ADD ‐ RS ≥ 1) was associated with a sensitivity of 100% (95% CI  = 73.5%–100%) and a specificity of 12.3% (95% CI  = 9.1%–16.2%) for the diagnosis of AAS . The negative likelihood ratio was 0 and the positive likelihood ratio was 1.14 (95% CI  = 1.1–1.2). Conclusions Our study confirms that in North America the prevalence of AAS in those undergoing advanced imaging is low. The ADD ‐ RS in this population has a low specificity. A lack of defined inclusion criteria and a low specificity limits the application of this rule in practice.