Stanford A型主动脉夹层院内死亡风险的简易床旁评估模型
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  • 英文篇名:A simple bedside model to predict the risk of in-hospital mortality in Stanford type A acute aortic dissection
  • 作者:王德 ; 丘俊涛 ; 于存涛 ; 张良 ; 杨阳 ; 常谦 ; 舒畅 ; 孙晓刚 ; 钱向阳
  • 英文作者:WANG De;QIU Juntao;YU Cuntao;ZHANG Liang;YANG Yang;CHANG Qian;SHU Chang;SUN Xiaogang;QIAN Xiangyang;State Key Laboratory of Cardiovascular Diseases,Fuwai Hospital,National Center for Cardiovascular Diseases,Chinese Academy of Medical Sciences and Peking Union Medical College;
  • 关键词:A型主动脉夹层 ; 院内死亡 ; 评分模型
  • 英文关键词:Type A aortic dissection;;in-hospital mortality;;scoring model
  • 中文刊名:ZXYX
  • 英文刊名:Chinese Journal of Clinical Thoracic and Cardiovascular Surgery
  • 机构:中国医学科学院北京协和医学院国家心血管病中心阜外医院心血管疾病国家重点实验室;
  • 出版日期:2018-05-27 22:45
  • 出版单位:中国胸心血管外科临床杂志
  • 年:2018
  • 期:v.25
  • 基金:国家自然科学基金项目(81270385)
  • 语种:中文;
  • 页:ZXYX201806013
  • 页数:7
  • CN:06
  • ISSN:51-1492/R
  • 分类号:56-62
摘要
目的分析Stanford A型主动脉夹层风险因素为院内死亡风险,建立一个简单而有效的床旁风险评估模型。方法纳入2010年1月至2015年12月我院血管病中心收治的999例Stanford A型主动脉夹层患者,其中男745例、女254例,平均年龄(49.8±12.0)岁。急性夹层837例。在急诊科药物治疗或等待外科治疗的术前患者182例(18.22%),获外科手术治疗的817例(81.78%)。运用多因素回归模型确立院内死亡风险因素,并量化评分院内死亡的风险值用于预测每例患者的院内死亡率。结果总体院内死亡率25.93%。多因素逻辑回归分析中,以下独立变量增加了院内死亡率:增加的年龄[OR=1.04,95%CI(1.02,1.05),P<0.000 1],急性主动脉夹层[OR=2.49,95%CI(1.30,4.77),P=0.006 1],晕厥[OR=2.76,95%CI(1.15,6.60),P=0.022 8],下肢麻木/疼痛[OR=7.99,95%CI(2.71,23.52),P=0.000 2],De BakeyⅠ型[OR=1.72,95%CI(1.05,2.80),P=0.030 5],头壁血管受累[OR=2.25,95%CI(1.20,4.24),P=0.011 7],急性肝功能不全[OR=2.60,95%CI(1.46,4.64),P=0.001 2],白细胞总数>15×10~9个/L[OR=1.87,95%CI(1.21,2.89),P=0.004 9]以及中大量心包积液[OR=4.34,95%CI(2.45,7.69),P<0.000 1]。根据多因素分析结果建立一个简易有效的床旁风险评估模型。结论主动脉A型夹层患者的不同临床表现和影像学特征预示着院内死亡的风险程度。简易快捷的床旁风险评估能有效协助临床医师识别高风险患者。
        Objective To investigate predictors for mortality among patients with Stanford type A acute aortic dissection(AAD) and to establish a predictive model to estimate risk of in-hospital mortality. Methods A total of 999 patients with Stanford type A AAD enrolled between 2010 and 2015 in our hospital were included for analysis. There were745 males and 254 females with a mean age of 49.8±12.0 years. There were 837 patients with acute dissection and 182 patients(18.22%) were preoperatively treated or waiting for surgery in the emergency department and 817(81.78%) were surgically treated. 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 The overall in-hospital mortality was 25.93%. In the multivariable analysis, the following variables were associated with increased in-hospital mortality: increased age(OR=1.04, 95% CI 1.02 to 1.05, P<0.000 1), acute aortic dissection(OR=2.49, 95% CI 1.30 to 4.77,P=0.006 1), syncope(OR=2.76, 95% CI 1.15 to 6.60, P=0.022 8), lower limbs numbness/pain(OR=7.99, 95% CI 2.71 to23.52, P=0.000 2), type Ⅰ De Bakey dissection(OR=1.72, 95% CI 1.05 to 2.80, P=0.030 5), brachiocephalic vessels involvement(OR=2.25, 95% CI 1.20 to 4.24, P=0.011 7), acute liver insufficiency(OR=2.60, 95% CI 1.46 to 4.64, P=0.001 2),white blood cell count(WBC)>15×10~9 cells/L(OR=1.87, 95% CI 1.21 to 2.89, P=0.004 9) and massive pericardial effusion(OR=4.34, 95% CI 2.45 to 7.69, P<0.000 1). Based on these multivariable results, a reliable and simple bedside risk prediction tool was developed. Conclusion Different clinical manifestations and imaging features of patients with Stanford type A AAD predict the risk of in-hospital mortality. This model can be used to assist physicians to quickly identify high risk patients and to make reasonable treatment decisions.
引文
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