Predictors and Dynamic Nomogram to Determine the Individual Risk of Malignant Brain Edema After Endovascular Thrombectomy in Acute Ischemic Stroke.

Abstract

BACKGROUND AND PURPOSE:

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).

METHODS:

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.

RESULTS:

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, p=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).

CONCLUSIONS:

Our web-based dynamic nomogram reliably predicted the risk of MBE in AIS patients after ET, and hence is worthy of further evaluation.

• Authors: Qian-Mei Jiang, Shuai Yu, Xiao-Feng Dong, Huai-Shun Wang, Jie Hou, Zhi-Chao Huang, Zhi-Liang Guo, Shou-Jiang You, Guo-Dong Xiao
• Journal: Journal of clinical neurology (Seoul, Korea) (J Clin Neurol) Vol. 18 Issue 3 Pg. 298-307 (May 2022) ISSN: 1738-6586 [Print] Korea (South)
• PMID: 35196752 (Publication Type: Journal Article)
• Copyright: Copyright © 2022 Korean Neurological Association.