Clinical Features of Aortic Dissection in the Emergency Department: A Single-center Experience from South China

Objectives: Our goal in this study was to determine 1) whether there are any differences in clinical characteristics between Chinese and Western patients with aortic dissection (AD), and 2) the mortality rate of AD patients in the emergency department (ED) and identify the risk predictors for death. Methods: We retrospectively analyzed patients who were diagnosed with AD and admitted to our ED between September 1, 2017–August 31, 2020. Data on age, gender, clinical manifestation, medical history, routine blood tests, liver and kidney function, coagulation, myocardial enzymology, and mortality were collected. Results: We enrolled 535 AD patients (422 men and 113 women) with a mean age of 54.7±14.1 years. Type A AD constituted 40% of the total number of AD cases, while type B AD constituted 60%. The proportion of those who were females, 10–92 years, with type A AD, and hypertension in the Chinese population was lower than that in the Western population (P <0.05 for all). Type A AD patients had a higher proportion of acute AD clinical manifestations than did patients with type B AD (P = 0.0084, P <0.05). The mortality rate of type A AD patients (10.75%) was higher than that of type B AD patients (1.87%) (P <0.0001) in the ED. Higher values of white blood cells, neutrophils, high-density lipoprotein, activated partial thromboplastin time, and D-dimer level with worsened hepatic and renal function were found in the deceased group, and multivariate logistic regression revealed that blood urea nitrogen (BUN) levels (P = 0.0031, P <0.05) were significantly associated with death. Conclusion: In South China, patients with AD had a mean age of 54.7 years, with 78.88% prevalence in males and 66.92% hypertension rate. Type A AD accounted for 40% of all AD cases, and 10.70% of patients with type A AD died in the ED. Elevated BUN levels may be a risk predictor for death in patients with type A AD.

Abstract licence: CC BY

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.