Jiang Qian-Mei, Yu Shuai, Dong Xiao-Feng, Wang Huai-Shun, Hou Jie, Huang Zhi-Chao, Guo Zhi-Liang, You Shou-Jiang, Xiao Guo-Dong
Department of Neurology and Suzhou Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Department of Neurology, Suzhou Municipal Hospital, Suzhou, China.
J Clin Neurol. 2022 May;18(3):298-307. doi: 10.3988/jcn.2022.18.3.298. Epub 2022 Feb 14.
This study aimed to construct an optimal dynamic nomogram for predicting malignant brain edema (MBE) in acute ischemic stroke (AIS) patients after endovascular thrombectomy (ET).
We enrolled AIS patients after ET from May 2017 to April 2021. MBE was defined as a midline shift of >5 mm at the septum pellucidum or pineal gland based on follow-up computed tomography within 5 days after ET. Multivariate logistic regression and LASSO (least absolute shrinkage and selection operator) regression were used to construct the nomogram. The area under the receiver operating characteristic curve (AUC) and decisioncurve analysis were used to compare our nomogram with two previous risk models for predicting brain edema after ET.
MBE developed in 72 (21.9%) of the 329 eligible patients. Our dynamic web-based nomogram (https://successful.shinyapps.io/DynNomapp/) consisted of five parameters: basal cistern effacement, postoperative National Institutes of Health Stroke Scale (NIHSS) score, brain atrophy, hypoattenuation area, and stroke etiology. The nomogram showed good discrimination ability, with a C-index (Harrell's concordance index) of 0.925 (95% confidence interval=0.890-0.961), and good calibration (Hosmer-Lemeshow test, =0.386). All variables had variance inflation factors of <1.5 and tolerances of >0.7, suggesting no significant collinearity among them. The AUC of our nomogram (0.925) was superior to those of Xiang-liang Chen and colleagues (0.843) and Ming-yang Du and colleagues (0.728).
Our web-based dynamic nomogram reliably predicted the risk of MBE in AIS patients after ET, and hence is worthy of further evaluation.
本研究旨在构建一个最佳动态列线图,用于预测急性缺血性卒中(AIS)患者血管内血栓切除术(ET)后发生恶性脑水肿(MBE)的风险。
我们纳入了2017年5月至2021年4月接受ET治疗的AIS患者。MBE的定义为ET术后5天内的随访计算机断层扫描显示透明隔或松果体处中线移位>5mm。采用多因素逻辑回归和LASSO(最小绝对收缩和选择算子)回归构建列线图。采用受试者操作特征曲线(AUC)下面积和决策曲线分析,将我们的列线图与之前两个预测ET后脑水肿的风险模型进行比较。
329例符合条件的患者中有72例(21.9%)发生了MBE。我们基于网络的动态列线图(https://successful.shinyapps.io/DynNomapp/)由五个参数组成:脑池消失、术后美国国立卫生研究院卒中量表(NIHSS)评分、脑萎缩、低密度区和卒中病因。该列线图显示出良好的区分能力,C指数(Harrell一致性指数)为0.925(95%置信区间=0.890-0.961),且校准良好(Hosmer-Lemeshow检验,P=0.386)。所有变量的方差膨胀因子<1.5,容忍度>0.7,表明它们之间无显著共线性。我们列线图的AUC(0.925)优于陈向亮及其同事(0.843)和杜明阳及其同事(0.728)的AUC。
我们基于网络的动态列线图能够可靠地预测AIS患者ET后发生MBE的风险,因此值得进一步评估。