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

DOI: 10.23736/S1824-4777.18.01326-8


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

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