Barth Rike, Zubler Frederic, Weck Anja, Haenggi Matthias, Schindler Kaspar, Wiest Roland, Wagner Franca
Sleep-Wake-Epilepsy Center, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland.
Sleep-Wake-Epilepsy Center, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland.
Resuscitation. 2020 Apr;149:217-224. doi: 10.1016/j.resuscitation.2020.01.014. Epub 2020 Jan 23.
Multimodal prognostication in comatose patients after cardiac arrest (CA) is complicated by the fact that different modalities are usually not independent. Here we set out to systematically correlate early EEG and MRI findings.
89 adult patients from a prospective register who underwent at least one EEG and one MRI in the acute phase after CA were included. The EEGs were characterized using pre-existent standardized categories (highly malignant, malignant, benign). For MRIs, the apparent diffusion coefficient (ADC) was computed in pre-defined regions. We then introduced a novel classification based on the topography of ADC reduction (MR-lesion pattern (MLP) 1: no lesion; MLP 2: purely cortical lesions; MLP 3: involvement of the basal ganglia; MLP 4 involvement of other deep grey matter regions).
EEG background reactivity and EEG background continuity were strongly associated with a lower MLP value (p < 0.001 and p = 0.003 respectively). The EEG categories highly malignant, malignant and benign were strongly correlated with the MLP values (rho = 0.46, p < 0.001).
The MRI lesions are highly correlated with the EEG pattern. Our results suggest that performing MRI in comatose patients after CA with either highly malignant or with a benign EEG pattern is unlikely to yield additional useful information for prognostication, and should therefore be performed in priority in patients with intermediate EEG patterns ("malignant pattern").
心脏骤停(CA)后昏迷患者的多模态预后评估较为复杂,因为不同的模态通常并非相互独立。在此,我们着手系统地关联早期脑电图(EEG)和磁共振成像(MRI)的结果。
纳入了89例来自前瞻性登记册的成年患者,这些患者在CA后的急性期至少接受了一次EEG和一次MRI检查。EEG采用现有的标准化类别进行特征描述(高度恶性、恶性、良性)。对于MRI,在预定义区域计算表观扩散系数(ADC)。然后,我们基于ADC降低的部位引入了一种新的分类方法(磁共振病变模式(MLP)1:无病变;MLP 2:单纯皮质病变;MLP 3:基底节受累;MLP 4:其他深部灰质区域受累)。
EEG背景反应性和EEG背景连续性与较低的MLP值密切相关(分别为p < 0.001和p = 0.003)。EEG类别高度恶性、恶性和良性与MLP值密切相关(rho = 0.46,p < 0.001)。
MRI病变与EEG模式高度相关。我们的结果表明,对于CA后昏迷且EEG模式为高度恶性或良性的患者,进行MRI检查不太可能产生额外有用的预后信息,因此应优先对EEG模式为中间类型(“恶性模式”)的患者进行检查。