文章摘要
李鑫 ，王军伟 ，杨涌涛 ，陈亮 ，郑方硕 ，李琼莉 ，徐新献 ，李兴贵 ，展群岭 ，金戈.急性缺血性脑卒中静脉溶栓预后的多因素联合预测模型研究[J].神经损伤功能重建,2021,16(6):330-333
急性缺血性脑卒中静脉溶栓预后的多因素联合预测模型研究
Study on Multi-Factor Joint Predictive Model of Intravenous Thrombolytic Prognosis inAcute Ischemic Stroke
  
DOI：
中文关键词: 急性缺血性脑卒中  静脉溶栓  预后  模型研究
英文关键词: acute ischemic stroke  intravenous thrombolysis  prognosis  model study
基金项目:重庆市卫生计生委 2017 医 学 科 研 计 划项目（No. 2017 MSXM157）
作者单位
李鑫a ，王军伟a ，杨涌涛a ，陈亮a ，郑方硕a ，李琼莉a ，徐新献b ，李兴贵a ，展群岭a ，金戈a 重庆市第五人民医 院 a. 神经内科，b. 全科医学科 
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中文摘要:
      目的：探讨通过建立多因素联合预测模型的方法预测急性缺血性脑卒中（AIS）患者使用阿替普酶静 脉溶栓治疗后的远期临床预后。方法：通过使用回顾性研究的方法，分析118 例接受阿替普酶静脉溶栓治 疗的AIS患者的临床资料；通过溶栓后90 d的改良Rankin量表（mRS）分为预后良好组（mRS评分0～2分） 和预后不良组（mRS评分3～6分）；使用多因素Logistic 回归的方法分析影响 AIS患者阿替普酶溶栓后90 d 神经功能预后的因素，并通过多因素Logistic回归方法计算联合预测值Y；采用ROC曲线验证Logistic回归 模型的诊断效度。结果：纳入预后良好组56 例（47.46%），纳入预后不良组62例（52.54%）。与预后良好组 相比，预后不良组大脑中动脉高密度征的比例及基线美国国立卫生院脑卒中量表（NIHSS）评分分值增高、 Alberta 卒中项目早期CT（ASPECTS）评分降低、溶栓后出血率较高（均P＜0.05）；多因素Logistic回归分析 结果显示ASPECTS评分和基线NIHSS评分为影响静脉溶栓远期预后的因素（P＜0.001）；两者通过多因素 Logistic回归方法计算的联合预测值Y的ROC曲线下面积为0.740，敏感度为60.70%、特异度为74.19%；优 于单独使用 ASPECTS 评分（AUC=0.672、敏感度=82.10%、特异度=48.39%）和基线 NIHSS 评分（AUC= 0.693、敏感度=75.00%、特异度=59.68%）作为单因素预测AIS溶栓患者预后的效果。结论：在AIS患者溶栓 前的基线指标中，大脑中动脉高密度征、ASPECTS评分、基线NIHSS评分等可作为预测AIS溶栓治疗患者 90 d预后的预测因素。通过建立多因素Logistics回归模型计算的联合变量Y对患者预后的预测效能更高。
英文摘要:
      To investigate the long-term prognosis of patients with acute ischemic stroke (AIS) after intravenous thrombolysis with alteplase by establishing a multi-factor combined prediction model. Methods: A retrospective study was conducted to analyze 118 AIS patients treated with intravenous thrombolysis with alteplase. According to the modified Rankin scale (mRS) 90 days after thrombolysis, patients were divided into the good prognosis group (mRS score 0-2 points) and poor prognosis group (mRS score 3-6 points). Multivariate Logistic regression was used to analyze the factors affecting the 90-day prognosis of neurological function in AIS patients after thrombolysis with alteplase and to determine the joint predictive value Y. The ROC curve was used to verify the diagnostic validity of the Logistic regression model. Results: Among the 118 AIS patients, the prognosis was good in 56 patients (47.46%) and poor in 62 patients (52.54%). Compared to the good prognosis group, the poor prognosis group showed increased density of the middle cerebral artery sign and a higher baseline NIHSS score, a lower ASPECT score, and a greater bleeding rate following thrombolysis (all P<0.05). Multivariate Logistic regression analysis showed that ASPECTS score and baseline NIHSS score affected the long-term prognosis of intravenous thrombolysis (P<0.001), and the area under the ROC curve of the joint predictive value Y calculated by multi-factor Logistic regression was 0.740, with a sensitivity of 60.70% and a specificity of 74.19%. This was superior to using ASPECTS score (AUC=0.672, sensitivity =82.10%, specificity = 48.39% ) and baseline NIHSS score (AUC=0.693, sensitivity =75.00% , specificity =59.68% ) alone to predict prognosis after AIS thrombolysis. Conclusion: The hyperdense middle cerebral artery sign, ASPECTS score, and baseline NIHSS score of AIS patients before thrombolysis can all be used as 90-day prognostic factors. The joint variable Y calculated by multi-factor Logistic regression can better predict prognosis.
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