title: A Simple Emergency Prediction Tool for Acute Aortic Dissection.
abstract: BACKGROUND
  A simple emergency risk prediction tool should be developed for clinicians to quickly identify the prognosis of patients with acute aortic dissection.
  
  
  METHODS
  We enrolled 280 patients with acute aortic dissection admitted to emergency department between May 2010 and February 2013. Multivariate logistic regression analysis was performed to identify independent predictors of in-hospital death.
  
  
  RESULTS
  The in-hospital mortality of our patients with acute aortic dissection was 32.5%, in-hospital deaths with surgery less than the survived (34.1% VS 54.5%). Multivariate analysis identified that age (≥65 years old), Type A, blood pressure (mean systolic blood pressure ≤ 90 mmHg), neutrophil percentage (≥ 80%) and serum D-dimer (≥ 5.0 mg/L) were significant predictors of death. With the simple emergency risk prediction tool, scores of all in-hospital deaths were ≥ 3, whereas almost all of the survivors (97.9%) had scores < 15. A score of 10 offered the best threshold value, with the highest sensitivity (81.3%) and specificity (86.8%).
  
  
  CONCLUSIONS
  The in-hospital mortality rate of patients with acute aortic dissection is high and can be predicted. Early surgery would be beneficial for in-hospital survive. This tool should be available for clinicians in the emergency department to quickly identify the prognosis of patients with acute aortic dissection.
authors.affiliation: 1. Dept. of Emergency, the Second Xiangya Hospital of Central South University , China.
authors.forename: Wen
authors.initials: W
authors.lastname: Peng
authors.affiliation: 2. Dept. of Cardiovascular, the Second Xiangya Hospital of Central South University , China.
authors.forename: Qing-Yi
authors.initials: QY
authors.lastname: Zhu
authors.affiliation: 1. Dept. of Emergency, the Second Xiangya Hospital of Central South University , China.
authors.forename: Xiang-Hong
authors.initials: XH
authors.lastname: Zhou
authors.affiliation: 1. Dept. of Emergency, the Second Xiangya Hospital of Central South University , China.
authors.forename: Xiang-Ping
authors.initials: XP
authors.lastname: Chai
keywords: Acute aortic dissection; Prediction; Risk factors