摘要
目的探讨急性缺血性脑卒中患者静脉溶栓后出血性转化(hemorrhagic transformation,HT)的危险因素。方法回顾性分析接受静脉溶栓治疗的171例急性缺血性脑卒中患者按治疗后7 d内行头颅CT检查,根据头颅有无出血性转化分为HT组及无HT组,比较两组患者的临床资料,采用单因素和Logistic回归分析静脉溶栓治疗后出血性转化的危险因素。结果HT组(33例)与无HT组(138例)相比,既往有糖尿病者较多(P=0.008),溶栓前头颅CT有早期缺血改变者较多(P=0.040),溶栓前美国卫生研究院卒中量表(National Institutes of Health Stroke Scale,NIHSS)评分较高(P=0.033),起病-溶栓时间(onset to treatment time,OTT)较长(P=0.043),溶栓后2 h收缩压、24 h收缩压、24 h舒张压较高(P=0.008、P=0.049、P=0.002)。Logistic回归分析表明溶栓前头颅CT有早期缺血改变者、溶栓前NIHSS评分高、溶栓后2 h及24 h收缩压高者与溶栓后HT发生显著相关。结论溶栓前头颅CT有早期缺血改变、溶栓前NIHSS评分的分值偏高、溶栓后2 h及24 h收缩压偏高是溶栓后HT的危险因素。
Objective To investigate the risk factors for hemorrhagic transformation after intraovenous thrombolysis in patients with acute ischemic stroke. Methods Patients with acute ischemic stroke after intravenous thrombolysis within 6 hours were consecutively recruited. Patients were then divided into the hemorrhagic transformation or non hemorrhagic transformation group according brain CT. Logistic regression was used to analyze the risk factors of hemorrhagic transformation after thrombolytic treatment. Results One hundred seventy-one patients were studied. History of diabetes （P=0.008）,early ischemic changes （EICs） on brain CT（P=0.040）, increased blood pressure at 2 and 24 h（P=0.008, P= 0.049）,diastolic pressure at 24 h （P=0.002）, onset to treatment time （P=0.043）,baseline NIHSS score （P=0.033）were higher in patients with HT group （33 cases）than in non HT group （138 cases）. Logistic regression analysis showed that high baseline NIHSS score, early ischemic changes （EICs） on brain CT,increased blood pressure at 2 and 24 h were related to HT independently. Conclusions The baseline NIHSS score,early ischemic changes （EICs） on brain CT, increased blood pressure at 2 and 24 h are the risk factors of hemorrhagic transformation following thrombolytic treatment in acute ischemic stroke patients.
出处
《中国神经精神疾病杂志》
CAS
CSCD
北大核心
2013年第10期581-586,共6页
Chinese Journal of Nervous and Mental Diseases
关键词
静脉溶栓
急性缺血性脑卒中
出血性转化
因素
Intraovenous thrombolysis Acute ischemic stroke Hemorrhagic transformation Prognosis
