文章摘要
张娜,刘仲仲,逯青丽,王静,刘佩,刘燕,常乔乔,王燕,宋沉生,蔺雪梅,王芳,吴松笛.列线图预测模型评估急性缺血性脑卒中患者 1年预后不良的风险[J].神经损伤功能重建,2022,17(5):254-258
列线图预测模型评估急性缺血性脑卒中患者 1年预后不良的风险
Nomogram Risk Prediction Model to Assess Risk of Poor 1-Year Prognosis after AcuteIschemic Stroke
  
DOI:
中文关键词: 急性缺血性脑卒中  危险因素  预后不良  列线图
英文关键词: acute ischemic stroke  risk factors  poor prognosis  nomogram
基金项目:陕西省科技计划项 目(No. 2017SF-163; 2021SF-333); 西安市科技计划重 大项目[No. 2018051 04YX12SF38(2)]; 西安市科技计划项 目[No. 20YXYJ0008 (1)]; 西安市卫健委科研项 目(No. 2020ms03; 2 020yb05; 2021yb33)
作者单位
张娜,刘仲仲,逯青丽,王静,刘佩,刘燕,常乔乔,王燕,宋沉生,蔺雪梅,王芳,吴松笛 西安市第一医院西 北大学附属第一医 院神经内科 
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中文摘要:
      目的:探讨急性缺血性脑卒中(AIS)患者1年发生预后不良的危险因素,并建立其列线图风险预测模 型。方法:通过西安脑卒中数据库平台,连续收集本市4所三级甲等医院2015年1~12月入院的AIS患者, 并在入院确诊后随访1年。采用单因素和多因素Logistic回归分析,探讨AIS患者1年预后不良的相关危 险因素,采用R软件及rms程序包构建AIS患者1年预后不良的列线图预测模型。结果:多因素Logistic回 归分析显示,年龄(OR=1.069,95%CI 1.052~1.087,P=0.000)、合并肺炎(OR=3.121,95%CI 1.595~ 6.107,P=0.001)、白细胞计数(OR=1.137,95%CI 1.062~1.217,P=0.000)、心房颤动(OR=1.816,95%CI 1.059~3.115,P=0.030)、入院NIHSS评分(OR=1.196,95%CI 1.153~1.241,P=0.000)是西安地区AIS患者 随访1年发生预后不良的独立危险因素。根据上述危险因素,成功建立预测AIS患者1年发生预后不良的 列线图预测模型。该模型ROC曲线下面积(AUC)为0.846,具有良好的区分度;Hosmer-Lemeshow拟合优 度检验结果显示差异无统计学意义(χ2=12.22,df=8,P=0.142)。结论:成功建立用于预测AIS患者随访1年 预后不良的列线图风险预测模型,该模型具有良好区分度与校准度。
英文摘要:
      To investigate the risk factors of poor prognosis 1 year after acute ischemic stroke (AIS) and to establish a nomogram risk prediction model. Methods: Clinical data of AIS patients who were consecutively admitted to 4 tertiary-grade A class hospitals from January to December 2015 were collected through the Xi’an Stroke Data Bank. The patients were followed up for 1 year after diagnosis. Univariate and multivariate Logistic analysis were applied to analyze the risk factors of poor 1-year prognosis. R software and the rms package were used to establish a nomogram risk prediction model for poor 1-year prognosis in AIS patients. Results: Multivariate Logistic regression analysis showed that age (OR=1.069, 95% CI 1.052~ 1.087, P=0.000), complication by pneumonia (OR=3.121, 95% CI 1.595~6.107, P=0.001), leukocyte count (OR=1.137, 95%CI 1.062~1.217, P=0.000), atrial fibrillation (OR=1.816, 95%CI 1.059~3.115, P=0.030), and NIHSS score at admission (OR=1.196, 95%CI 1.153~1.241, P=0.000) were independent risk factors for poor 1-year prognosis of AIS patients in the Xi’an area. Based on the above independent risk factors, a nomogram prediction model was established to predict poor 1-year prognosis in AIS patients. ROC curve analysis showed that the area under the curve (AUC) was 0.846, indicating good discrimination. The Hosmer-Lemeshow test showed no significant difference (χ2=12.22, df=8, P=0.142). Conclusion: A nomogram risk prediction model for poor 1-year prognosis in AIS patients was successfully established. This model has good differentiation and calibration.
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