Clinical criteria for aortic dissection are poorly defined. Thus, 35% of aortic dissections remain unsuspected in vivo, and 99% of suspected cases can be refuted.
To identify independent predictors of acute aortic dissection and create a prediction model for facilitated estimation of the individual risk of dissection.
Two hundred fifty patients with acute chest pain, back pain, or both; absence of an established differential diagnosis of the pain syndrome; and clinical suspicion of acute aortic dissection were evaluated for the presence of 26 clinical variables in a prospective, observational study. Multivariate analysis was performed to create a prediction model of aortic dissection.
Aortic pain with immediate onset, a tearing or ripping character, or both; mediastinal widening, aortic widening, or both on chest radiography; and pulse differentials, blood pressure differentials, or both (P<.001 for all) were identified as independent predictors of acute aortic dissection. Probability of dissection was low with absence of all 3 variables (7%), intermediate with isolated findings of aortic pain or mediastinal widening (31% and 39%, respectively), and high with isolated pulse or blood pressure differentials or any combination of the 3 variables (≥83%). Accordingly, 4% of all dissections were assigned to the low-probability group, 19% to the intermediate-probability group, and 77% to the high-probability group of aortic dissection.
Assessment of 3 clinical variables permitted identification of 96% of the acute aortic dissections and stratification into high-, intermediate-, and low-probability groupings of disease. With better selection for prompt diagnostic imaging, this prediction model can be used as an aid to improve patient care in aortic dissection.