ORIGINAL ARTICLE   

Italian Journal of Vascular and Endovascular Surgery 2018 September;25(3):203-9

DOI: 10.23736/S1824-4777.18.01326-8

Copyright © 2018 EDIZIONI MINERVA MEDICA

lingua: Inglese

A simple scoring model for in-hospital mortality of type A aortic dissection

Liang ZHANG, Juntao QIU, Xiaogang SUN, Xiangyang QIAN, Wei GAO, Shen LIU, Wenxiang JIANG, Jinlin WU, Cuntao YU ✉

Department of Cardiovascular Surgery, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing, China

BACKGROUND: The aim of this study was to investigate predictors for mortality among patients presenting with type A aortic dissection (AAD) and to create a predictive model to estimate risk of in-hospital mortality.
METHODS: All patients with AAD enrolled between 2010 and 2015 were retrospectively 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.
RESULTS: A total of 999 patients with AAD were included for analysis (mean age 49.8±12.0 years, 745 male), with an overall in-hospital mortality of 25.93%. In multivariable analysis, the following variables were associated with increased in-hospital mortality: increased age (odds ratio [OR] 1.04; 95% CI: 1.02-1.05], acute aortic dissection (OR=2.49; 95% CI: 1.30-4.77), syncope (OR=2.76; 95% CI: 1.15-6.60), lower limbs numbness/pain (OR=7.99; 95% CI: 2.71-23.52), type I DeBakey dissection (OR=1.72; 95% CI: 1.05-2.80), brachiocephalic vessels involvement (OR=2.25; 95% CI: 1.20-4.24), acute liver insufficiency (OR=2.60; 95% CI: 1.46-4.64), white blood cell count (WBC) >15 ×109 cells/L (OR=1.87; 95% CI: 1.21-2.89), and massive pericardial effusion (OR=4.34; 95% CI: 2.45-7.69). Based on these multivariable results, a reliable and simple bedside risk prediction tool was developed.
CONCLUSIONS: We present a simple prediction model that were independently associated with in-hospital mortality in patients with AAD. This model could be used to assist physicians to quickly identify high risk patients and to make reasonable treatment decisions.

KEY WORDS: Dissecting aneurysm - Aorta - Mortality - Risk assessment - Logistic models