Predicting in-hospital mortality in acute type B aortic dissection: evidence from International Registry of Acute Aortic Dissection

Abstract

Background: The outcome of patients with acute type B aortic dissection (ABAD) is strongly related to their clinical presentation. The purpose of this study was to investigate predictors for mortality among patients presenting with ABAD and to create a predictive model to estimate individual risk of in-hospital mortality using the International Registry of Acute Aortic Dissection (IRAD).

Methods and results: All patients with ABAD enrolled in IRAD between 1996 and 2013 were included for analysis. Multivariable logistic regression analysis was used to investigate predictors of in-hospital mortality. Significant risk factors for in-hospital death were used to develop a prediction model. A total of 1034 patients with ABAD were included for analysis (673 men; mean age, 63.5±14.0 years), with an overall in-hospital mortality of 10.6%. In multivariable analysis, the following variables at admission were independently associated with increased in-hospital mortality: increasing age (odds ratio [OR], 1.03; 95% confidence interval [CI], 1.00-1.06; P=0.044), hypotension/shock (OR, 6.43; 95% CI, 2.88-18.98; P=0.001), periaortic hematoma (OR, 3.06; 95% CI, 1.38-6.78; P=0.006), descending diameter ≥5.5 cm (OR, 6.04; 95% CI, 2.87-12.73; P<0.001), mesenteric ischemia (OR, 9.03; 95% CI, 3.49-23.38; P<0.001), acute renal failure (OR, 3.61; 95% CI, 1.68-7.75; P=0.001), and limb ischemia (OR, 3.02; 95% CI, 1.05-8.68; P=0.040). Based on these multivariable results, a reliable and simple bedside risk prediction tool was developed.

Conclusions: We present a simple prediction model using variables that are independently associated with in-hospital mortality in patients with ABAD. Although it needs to be validated in an independent population, this model could be used to assist physicians in their choice of management and for informing patients and their families.

Keywords: aorta; aortic dissection; risk model; type B dissection.