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大血管闭塞性卒中急性症状严重程度的分解:与多参数CT成像和临床参数的关联

Decomposing Acute Symptom Severity in Large Vessel Occlusion Stroke: Association With Multiparametric CT Imaging and Clinical Parameters.

作者信息

Stueckelschweiger Lena, Tiedt Steffen, Puhr-Westerheide Daniel, Fabritius Matthias P, Mueller Franziska, Kellert Lars, Maurus Stefan, Grosu Sergio, Rueckel Johannes, Herzberg Moriz, Liebig Thomas, Ricke Jens, Dimitriadis Konstantinos, Kunz Wolfgang G, Reidler Paul

机构信息

Department of Radiology, University Hospital, Ludwig-Maximilians-University of Munich, Munich, Germany.

Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-University of Munich, Munich, Germany.

出版信息

Front Neurol. 2021 Mar 11;12:651387. doi: 10.3389/fneur.2021.651387. eCollection 2021.

DOI:10.3389/fneur.2021.651387
PMID:33776900
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7991695/
Abstract

Acute ischemic stroke of the anterior circulation due to large vessel occlusion (LVO) is a multifactorial process, which causes neurologic symptoms of different degree. Our aim was to examine the impact of neuromorphologic and vascular correlates as well as clinical factors on acute symptom severity in LVO stroke. We selected LVO stroke patients with known onset time from a consecutive cohort which underwent multiparametric CT including non-contrast CT, CT angiography and CT perfusion (CTP) before thrombectomy. Software-based quantification was used to calculate CTP total ischemic and ischemic core volume. Symptom severity was assessed using the National Institutes of Health Stroke Scale (NIHSS) upon admission. Multivariable regression analysis was performed to determine independent associations of admission NIHSS with imaging and clinical parameters. Receiver operating characteristics (ROC) analyses were used to examine performance of imaging parameters to classify symptom severity. We included 142 patients. Linear and ordinal regression analyses for NIHSS and NIHSS severity groups identified significant associations for total ischemic volume [β = 0.31, = 0.01; Odds ratio (OR) = 1.11, 95%-confidence-interval (CI): 1.02-1.19], clot burden score (β = -0.28, = 0.01; OR = 0.76, 95%-CI: 0.64-0.90) and age (β = 0.17, = 0.04). No association was found for ischemic core volume, stroke side, collaterals and time from onset. Stroke topography according to the Alberta Stroke Program CT Score template did not display significant influence after correction for multiple comparisons. AUC for classification of the NIHSS threshold ≥6 by total ischemic volume was 0.81 ( < 0.001). We determined total ischemic volume, clot burden and age as relevant drivers for baseline NIHSS in acute LVO stroke. This suggests that not only mere volume but also degree of occlusion influences symptom severity. Use of imaging parameters as surrogate for baseline NIHSS reached limited performance underlining the need for combined clinical and imaging assessment in acute stroke management.

摘要

大动脉闭塞(LVO)所致前循环急性缺血性卒中是一个多因素过程,可导致不同程度的神经症状。我们的目的是研究神经形态学和血管相关性以及临床因素对LVO卒中急性症状严重程度的影响。我们从一个连续队列中选取了已知发病时间的LVO卒中患者,这些患者在取栓术前接受了包括非增强CT、CT血管造影和CT灌注(CTP)在内的多参数CT检查。基于软件的定量分析用于计算CTP总缺血体积和缺血核心体积。入院时使用美国国立卫生研究院卒中量表(NIHSS)评估症状严重程度。进行多变量回归分析以确定入院NIHSS与影像学和临床参数之间的独立关联。使用受试者工作特征(ROC)分析来检验影像学参数对症状严重程度进行分类的性能。我们纳入了142例患者。对NIHSS和NIHSS严重程度组进行的线性和有序回归分析确定了总缺血体积[β = 0.31,P = 0.01;比值比(OR)= 1.11,95%置信区间(CI):1.02 - 1.19]、血栓负荷评分(β = -0.28,P = 0.01;OR = 0.76,95%CI:0.64 - 0.90)和年龄(β = 0.17,P = 0.04)之间存在显著关联。未发现缺血核心体积、卒中侧别、侧支循环和发病时间之间存在关联。根据阿尔伯塔卒中项目CT评分模板的卒中部位在进行多重比较校正后未显示出显著影响。总缺血体积对NIHSS阈值≥6进行分类的AUC为0.81(P < 0.001)。我们确定总缺血体积、血栓负荷和年龄是急性LVO卒中基线NIHSS的相关驱动因素。这表明不仅单纯的体积,而且闭塞程度也会影响症状严重程度。将影像学参数用作基线NIHSS的替代指标的性能有限,这突出了在急性卒中管理中进行临床和影像学联合评估的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5570/7991695/c2f4e791a515/fneur-12-651387-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5570/7991695/940e48160e64/fneur-12-651387-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5570/7991695/c2f4e791a515/fneur-12-651387-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5570/7991695/940e48160e64/fneur-12-651387-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5570/7991695/c2f4e791a515/fneur-12-651387-g0002.jpg

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