Weng Ze-An, Huang Xiao-Xiong, Deng Die, Yang Zhen-Guo, Li Shu-Yuan, Zang Jian-Kun, Li Yu-Feng, Liu Yan-Fang, Wu You-Sheng, Zhang Tian-Yuan, Su Xuan-Lin, Lu Dan, Xu An-Ding
Department of Neurology and Stroke Center, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China.
Clinical Neuroscience Institute, The First Affiliated Hospital of Jinan University, Jinan University, Guangzhou, China.
Front Neurol. 2022 Mar 10;13:774654. doi: 10.3389/fneur.2022.774654. eCollection 2022.
We aimed to develop and validate a new nomogram for predicting the risk of intracranial hemorrhage (ICH) in patients with acute ischemic stroke (AIS) after intravenous thrombolysis (IVT).
A retrospective study enrolled 553 patients with AIS treated with IVT. The patients were randomly divided into two cohorts: the training set (70%, = 387) and the testing set (30%, = 166). The factors in the predictive nomogram were filtered using multivariable logistic regression analysis. The performance of the nomogram was assessed based on the area under the receiver operating characteristic curve (AUC-ROC), calibration plots, and decision curve analysis (DCA).
After multivariable logistic regression analysis, certain factors, such as smoking, National Institutes of Health of Stroke Scale (NIHSS) score, blood urea nitrogen-to-creatinine ratio (BUN/Cr), and neutrophil-to-lymphocyte ratio (NLR), were found to be independent predictors of ICH and were used to construct a nomogram. The AUC-ROC values of the nomogram were 0.887 (95% CI: 0.842-0.933) and 0.776 (95% CI: 0.681-0.872) in the training and testing sets, respectively. The AUC-ROC of the nomogram was higher than that of the Multicenter Stroke Survey (MSS), Glucose, Race, Age, Sex, Systolic blood Pressure, and Severity of stroke (GRASPS), and stroke prognostication using age and NIH Stroke Scale-100 positive index (SPAN-100) scores for predicting ICH in both the training and testing sets ( < 0.05). The calibration plot demonstrated good agreement in both the training and testing sets. DCA indicated that the nomogram was clinically useful.
The new nomogram, which included smoking, NIHSS, BUN/Cr, and NLR as variables, had the potential for predicting the risk of ICH in patients with AIS after IVT.
我们旨在开发并验证一种新的列线图,用于预测急性缺血性卒中(AIS)患者静脉溶栓(IVT)后颅内出血(ICH)的风险。
一项回顾性研究纳入了553例接受IVT治疗的AIS患者。患者被随机分为两个队列:训练集(70%,n = 387)和测试集(30%,n = 166)。使用多变量逻辑回归分析筛选预测列线图中的因素。基于受试者操作特征曲线下面积(AUC-ROC)、校准图和决策曲线分析(DCA)评估列线图的性能。
经过多变量逻辑回归分析,发现吸烟、美国国立卫生研究院卒中量表(NIHSS)评分、血尿素氮与肌酐比值(BUN/Cr)以及中性粒细胞与淋巴细胞比值(NLR)等因素是ICH的独立预测因素,并用于构建列线图。列线图在训练集和测试集中的AUC-ROC值分别为0.887(95%CI:0.842 - 0.933)和0.776(95%CI:0.681 - 0.872)。在训练集和测试集中,列线图的AUC-ROC均高于多中心卒中调查(MSS)、血糖、种族、年龄、性别、收缩压和卒中严重程度(GRASPS)以及使用年龄和美国国立卫生研究院卒中量表100阳性指数(SPAN-100)评分预测ICH的模型(P < 0.05)。校准图在训练集和测试集中均显示出良好的一致性。DCA表明该列线图具有临床实用性。
新的列线图将吸烟、NIHSS、BUN/Cr和NLR作为变量,具有预测IVT后AIS患者ICH风险的潜力。