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轻度创伤性脑损伤患者队列中血液和计算机断层扫描成像生物标志物之间的关联。

Association between Blood and Computed Tomographic Imaging Biomarkers in a Cohort of Mild Traumatic Brain Injury Patients.

机构信息

Department of Radiology, Neuroradiology Division, Quantitative Sciences Unit, Stanford University, Stanford, California, USA.

Department of Medicine, Quantitative Sciences Unit, Stanford University, Stanford, California, USA.

出版信息

J Neurotrauma. 2022 Oct;39(19-20):1329-1338. doi: 10.1089/neu.2021.0390. Epub 2022 Jun 13.

Abstract

The objective of this work was to analyze the relationships between traumatic brain injury (TBI) on computed tomographic (CT) imaging and blood concentration of glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), and S100B. This prospective cohort study involved 644 TBI patients referred to Stanford Hospital's Emergency Department between November 2015 and April 2017. Plasma and serum samples of 462 patients were analyzed for levels of GFAP, UCH-L1, and S100B. Glial neuronal ratio (GNR) was calculated as the ratio between GFAP and UCH-L1 concentrations. Admission head CT scans were reviewed for TBI imaging common data elements, and performance of biomarkers for identifying TBI was assessed via area under the receiver operating characteristic curve (ROC). We also dichotomized biomarkers at established thresholds and estimated standard measures of classification accuracy. We assessed the ability of GFAP, UCH-L1, and GNR to discriminate small and large/diffuse lesions based on CT imaging using an ROC analysis. In our cohort of mostly mild TBI patients, GFAP was significantly more accurate in detecting all types of acute brain injuries than UCH-L1 in terms of area under the curve (AUC) values ( < 0.001), and also compared with S100B ( < 0.001). UCH-L1 and S100B had similar performance (comparable AUC values,  = 0.342). Sensitivity exceeded 0.8 for each biomarker across all different types of TBI injuries, and no significant differences were observed by type of injury. There was a significant difference between GFAP and GNR in distinguishing between small lesions and large/diffuse lesions in all injuries ( = 0.004,  = 0.007). In conclusion, GFAP, UCH-L1, and S100B show high sensitivity and negative predictive values for all types of TBI lesions on head CT. A combination of negative blood biomarkers (GFAP and UCH-L1) in a patient suspected of TBI may be used to safely obviate the need for a head CT scan. GFAP is a promising indicator to discriminate between small and large/diffuse TBI lesions.

摘要

本研究旨在分析创伤性脑损伤(TBI)患者的计算机断层扫描(CT)影像学表现与胶质纤维酸性蛋白(GFAP)、泛素 C 端水解酶-L1(UCH-L1)和 S100B 血浓度之间的关系。这是一项前瞻性队列研究,纳入了 2015 年 11 月至 2017 年 4 月期间斯坦福医院急诊科收治的 644 例 TBI 患者。对其中 462 例患者的 GFAP、UCH-L1 和 S100B 血浆和血清样本进行了分析。通过 GFAP 与 UCH-L1 浓度之比计算出神经胶质细胞比值(GNR)。回顾性评估了入院时头部 CT 扫描的 TBI 影像学常见数据元素,并通过接受者操作特征曲线(ROC)下面积评估了生物标志物对 TBI 的识别效能。我们还在既定阈值下对生物标志物进行了二分法处理,并估计了分类准确性的标准指标。我们使用 ROC 分析评估了 GFAP、UCH-L1 和 GNR 区分 CT 影像学上小病变和大/弥漫性病变的能力。在我们主要为轻度 TBI 患者的队列中,GFAP 在检测各种类型的急性脑损伤方面的曲线下面积(AUC)值明显优于 UCH-L1(<0.001),也优于 S100B(<0.001)。UCH-L1 和 S100B 的性能相似(AUC 值相当,=0.342)。每种生物标志物对所有不同类型的 TBI 损伤的敏感性均超过 0.8,且不同损伤类型之间无显著差异。在所有损伤中,GFAP 和 GNR 均能显著区分小病变和大/弥漫性病变(=0.004,=0.007)。总之,GFAP、UCH-L1 和 S100B 在头部 CT 上对所有类型的 TBI 病变均具有较高的敏感性和阴性预测值。疑似 TBI 的患者若血液生物标志物阴性(GFAP 和 UCH-L1),则可安全避免进行头部 CT 检查。GFAP 是一种有前途的鉴别小病变和大/弥漫性 TBI 病变的指标。

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