Xie Wei, Ma Xiaoming, Xu Geman, Wang Yumei, Huang Wendie, Liu Meng, Sheng Shiying, Yuan Jie, Wang Jing
Department of Neurology, The Third Affiliated Hospital of Soochow University, The First People's Hospital of Changzhou, Changzhou, China.
North China University of Science and Technology, Tangshan, China.
Front Neurol. 2023 Sep 14;14:1221879. doi: 10.3389/fneur.2023.1221879. eCollection 2023.
Malignant cerebral edema (MCE) is a life-threatening complication of large hemisphere infarction (LHI). Therefore, a fast, accurate, and convenient tool for predicting MCE can guide triage services and facilitate shared decision-making. In this study, we aimed to develop and validate a nomogram for the early prediction of MCE risk in acute LHI involving the anterior circulation and to understand the potential mechanism of MCE.
This retrospective study included 312 consecutive patients with LHI from 1 January 2019 to 28 February 2023. The patients were divided into MCE and non-MCE groups. MCE was defined as an obvious mass effect with ≥5 mm midline shift or basal cistern effacement. Least absolute shrinkage and selection operator (LASSO) and logistic regression were performed to explore the MCE-associated factors, including medical records, laboratory data, computed tomography (CT) scans, and independent clinic risk factors. The independent factors were further incorporated to construct a nomogram for MCE prediction.
Among the 312 patients with LHI, 120 developed MCE. The following eight factors were independently associated with MCE: Glasgow Coma Scale score ( = 0.007), baseline National Institutes of Health Stroke Scale score ( = 0.006), Alberta Stroke Program Early CT Score ( < 0.001), admission monocyte count ( = 0.004), white blood cell count ( = 0.002), HbA1c level (p < 0.001), history of hypertension ( = 0.027), and history of atrial fibrillation ( = 0.114). These characteristics were further used to establish a nomogram for predicting prognosis. The nomogram achieved an AUC-ROC of 0.89 (95% CI, 0.82-0.96).
Our nomogram based on LASSO-logistic regression is accurate and useful for the early prediction of MCE after LHI. This model can serve as a precise and practical tool for clinical decision-making in patients with LHI who may require aggressive therapeutic approaches.
恶性脑水肿（MCE）是大脑半球大面积梗死（LHI）的一种危及生命的并发症。因此，一种快速、准确且便捷的预测MCE的工具可以指导分诊服务并促进共同决策。在本研究中，我们旨在开发并验证一种列线图，用于早期预测涉及前循环的急性LHI患者发生MCE的风险，并了解MCE的潜在机制。
这项回顾性研究纳入了2019年1月1日至2023年2月28日期间连续收治的312例LHI患者。将患者分为MCE组和非MCE组。MCE定义为具有明显占位效应且中线移位≥5mm或基底池消失。采用最小绝对收缩和选择算子（LASSO）及逻辑回归分析来探索与MCE相关的因素，包括病历、实验室数据、计算机断层扫描（CT）结果以及独立的临床危险因素。将这些独立因素进一步纳入以构建用于预测MCE的列线图。
在312例LHI患者中，120例发生了MCE。以下八个因素与MCE独立相关：格拉斯哥昏迷量表评分（=0.007）、基线美国国立卫生研究院卒中量表评分（=0.006）、阿尔伯塔卒中项目早期CT评分（<0.001）、入院时单核细胞计数（=0.004）、白细胞计数（=0.002）、糖化血红蛋白水平（p<0.001）、高血压病史（=0.027）和心房颤动病史（=0.114）。利用这些特征进一步建立了一个预测预后的列线图。该列线图的曲线下面积（AUC-ROC）为0.89（95%CI，0.82-0.96）。
我们基于LASSO-逻辑回归的列线图对于早期预测LHI后发生的MCE准确且有用。该模型可作为可能需要积极治疗方法的LHI患者临床决策的精确实用工具。
