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一种预测高血压性脑出血早期血肿扩大的列线图。

A nomogram to predict early hematoma expansion of hypertensive cerebral hemorrhage.

作者信息

Hu Si, Sheng WenGuo, Hu Yi, Ma Qiang, Li Bin, Han RuiZhang

机构信息

Department of Neurosurgery.

Department of Neurology, Affiliated Huzhou FuYin Hospital of Huzhou University, Huzhou, ZheJiang, China.

出版信息

Medicine (Baltimore). 2021 Feb 19;100(7):e24737. doi: 10.1097/MD.0000000000024737.

Abstract

Early hematoma expansion of hypertensive cerebral hemorrhage is affected by various factors. This study aimed to clarify the risk factors and develop a nomogram to predict early hematoma expansion.A retrospective analysis was carried out in patients with hypertensive cerebral hemorrhage admitted to our institution between January 1, 2012 and December 31, 2018; the patients were divided into 2 groups according to the presence of early hematoma expansion. Univariate and multivariate analyses were performed to analyze the risk factors of hematoma expansion. The nomogram was developed based on a multivariate logistic regression model, and the discriminative ability of the model was analyzed.A total of 477 patients with hypertensive cerebral hemorrhage and with a baseline hematoma volume <30 ml were included in our retrospective analysis. The hematoma expansion rate was 34.2% (163/477). After multivariate logistic regression, 9 variables (alcohol history, Glasgow coma scale score, total serum calcium, blood glucose, international normalized ratio, hematoma shape, hematoma density, volume of hematoma on initial computed tomography scan, and presence of intraventricular hemorrhage) identified as independent predictors of hematoma expansion were used to generate the nomogram. The area under the receiver operating characteristic curve of the nomogram was 0.883 (95% confidence interval 0.851-0.914), and the cutoff score was -0.19 with sensitivity of 75.5% and specificity of 87.3%.The nomogram can accurately predict the risk of early hematoma expansion.

摘要

高血压性脑出血的早期血肿扩大受多种因素影响。本研究旨在阐明危险因素并建立列线图以预测早期血肿扩大。对2012年1月1日至2018年12月31日期间我院收治的高血压性脑出血患者进行回顾性分析;根据是否存在早期血肿扩大将患者分为2组。进行单因素和多因素分析以分析血肿扩大的危险因素。基于多因素逻辑回归模型建立列线图,并分析模型的判别能力。共有477例基线血肿体积<30ml的高血压性脑出血患者纳入我们的回顾性分析。血肿扩大率为34.2%(163/477)。多因素逻辑回归后,9个被确定为血肿扩大独立预测因素的变量(饮酒史、格拉斯哥昏迷量表评分、血清总钙、血糖、国际标准化比值、血肿形状、血肿密度、初次计算机断层扫描时的血肿体积以及脑室内出血的存在)用于生成列线图。列线图的受试者工作特征曲线下面积为0.883(95%置信区间0.851 - 0.914),截断分数为 - 0.19,敏感性为75.5%,特异性为87.3%。该列线图可准确预测早期血肿扩大的风险。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9b3a/7899817/bc6476b8fc52/medi-100-e24737-g001.jpg

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