Improvement in the management of suspected acute aortic syndrome in the emergency room through a clinical algorithm and study of predictive factors

Background and objective: Acute aortic syndrome (AAS) is uncommon and difficult to diagnose, with great variability in clinical presentation. To develop a computerized algorithm, or clinical decision support system (CDSS), for managing and requesting imaging in the emergency department, specifically computerized tomography of the aorta (CTA), when there is suspicion of AAS, and to determine the effect of implementing this system. To determine the factors associated with a positive radiological diagnosis that improve the predictive capacity of CTA findings.

Materials and methods: After developing and implementing an evidence-based algorithm, we studied suspected cases of AAS. Chi-squared test was used to analyze the association between the variables included in the algorithm and radiological diagnosis, with 3 categories: no relevant findings, positive for AAS, and alternative diagnoses.

Results: 130 requests were identified; 19 (14.6%) had AAS and 34 (26.2%) had a different acute pathology. Of the 19 with AAS, 15 had been stratified as high risk and 4 as intermediate risk. The probability of AAS was 3.4 times higher in patients with known aortic aneurysm (P = .021, 95% CI 1.2–9.6) and 5.1 times higher in patients with a new aortic regurgitation murmur (P = .019, 95% CI 1.3–20.1). The probability of having an alternative severe acute pathology was 3.2 times higher in patients with hypotension or shock (P = .02, 95% CI 1.2–8.5).

Conclusion: The use of a CDSS in the emergency department can help optimize AAS diagnosis. The presence of a known aortic aneurysm and new-onset aortic regurgitation were shown to significantly increase the probability of AAS. Further studies are needed to establish a clinical prediction rule.