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Brain functional connectivity during the first day of coma reflects long-term outcome.
NeuroImage: Clinical ( IF 4.2 ) Pub Date : 2020-05-27 , DOI: 10.1016/j.nicl.2020.102295
Thomas Kustermann 1 , Nathalie Ata Nguepnjo Nguissi 1 , Christian Pfeiffer 2 , Matthias Haenggi 3 , Rebekka Kurmann 4 , Frédéric Zubler 4 , Mauro Oddo 5 , Andrea O Rossetti 6 , Marzia De Lucia 1
Affiliation  

Objective

In patients with disorders of consciousness (DOC), properties of functional brain networks at rest are informative of the degree of consciousness impairment and of long-term outcome. Here we investigate whether connectivity differences between patients with favorable and unfavorable outcome are already present within 24 h of coma onset.

Methods

We prospectively recorded 63-channel electroencephalography (EEG) at rest during the first day of coma after cardiac arrest. We analyzed 98 adults, of whom 57 survived beyond unresponsive wakefulness. Functional connectivity was estimated by computing the ‘debiased weighted phase lag index’ over epochs of five seconds duration. We evaluated the network’s topological features, including clustering coefficient, path length, modularity and participation coefficient and computed their variance over time. Finally, we estimated the predictive value of these topological features for patients’ outcomes by splitting the patient sample in training and test datasets.

Results

Group-level analysis revealed lower clustering coefficient, higher modularity and path length variance in patients with favorable compared to those with unfavorable outcomes (p < 0.01). Within all features, the path length variance in the network provided the best positive predictive value (PPV) for favorable outcome and specificity for unfavorable outcome in the test dataset (PPV: 0.83, p < 0.01; specificity: 0.86, p < 0.01) with above-chance negative predictive value and accuracy. Of note, the exclusion of patients with epileptiform activity (20 in total) eliminates all false positive predictions (n = 6) for path length variance.

Interpretation

Topological features of functional connectivity differ as a function of long-term outcome in patients on the first day of coma. These differences are not interpretable in terms of consciousness levels as all patients were in a deep unconscious state. The time variance of path length is informative of comatose patients’ outcome, as patients with favorable outcome exhibit a richer repertoire of path length than those with unfavorable outcomes.



中文翻译:

昏迷第一天的大脑功能连接反映了长期结果。

目的

在患有意识障碍(DOC)的患者中,静止时的功能性大脑网络的性质可为意识障碍程度和长期预后提供信息。在这里,我们调查了在昏迷发作后24小时内,结果是否良好的患者之间的连通性差异是否已经存在。

方法

我们前瞻性地记录了心脏骤停后昏迷的第一天在休息时的63通道脑电图(EEG)。我们分析了98位成年人,其中57位幸免于无反应的清醒。通过计算持续时间为五秒的“偏移加权相位滞后指数”来估算功能连接性。我们评估了网络的拓扑特征,包括聚类系数,路径长度,模块性和参与系数,并计算了它们随时间的变化。最后,我们通过在训练和测试数据集中拆分患者样本,估计了这些拓扑特征对患者结果的预测价值。

结果

小组水平分析显示,与预后差的患者相比,预后良好的患者的聚类系数更低,模块性更高,路径长度方差更大(p <0.01)。在所有特征中,网络中的路径长度方差提供了最佳的阳性预测值(PPV),以提供有利的结果,并提供了测试数据集中不利结果的特异性(PPV:0.83,p  <0.01;特异性:0.86,p <0.01),其中高于预期的负面预测值和准确性。值得注意的是,排除癫痫样活动的患者(总共20例)消除了所有关于路径长度变化的假阳性预测(n = 6)。

解释

在昏迷的第一天,功能连接的拓扑特征随患者长期结局而异。这些差异在意识水平上是无法解释的,因为所有患者都处于深度无意识状态。路径长度的时间变化可提供昏迷患者预后的信息,因为预后良好的患者比预后不良的患者表现出更丰富的路径长度。

更新日期:2020-05-27
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