From the Department of Intensive Care Medicine, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands (E.v.D., A.W.v.d.K., T.N., A.J.C.S.); Alzheimer Center and Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands (E.v.D.); Department of Clinical Neurophysiology and MEG Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands (E.v.D., C.J.S.); MIRA Institute for Biomedical Technology and Technical Medicine, University of Twente, Enschede, The Netherlands (T.N.); Department of Geriatrics, University Medical Center Utrecht, Utrecht, The Netherlands (H.L.K.); Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands (F.A.M.K.); and Department of Cardio-Thoracic Surgery, University Medical Center Utrecht, Utrecht, The Netherlands (M.P.B.).
Anesthesiology. 2014 Aug;121(2):328-35. doi: 10.1097/ALN.0000000000000329.
In this article, the authors explore functional connectivity and network topology in electroencephalography recordings of patients with delirium after cardiac surgery, aiming to improve the understanding of the pathophysiology and phenomenology of delirium. The authors hypothesize that disturbances in attention and consciousness in delirium may be related to alterations in functional neural interactions.
Electroencephalography recordings were obtained in postcardiac surgery patients with delirium (N = 25) and without delirium (N = 24). The authors analyzed unbiased functional connectivity of electroencephalography time series using the phase lag index, directed phase lag index, and functional brain network topology using graph analysis.
The mean phase lag index was lower in the α band (8 to 13 Hz) in patients with delirium (median, 0.120; interquartile range, 0.113 to 0.138) than in patients without delirium (median, 0.140; interquartile range, 0.129 to 0.168; P < 0.01). Network topology in delirium patients was characterized by lower normalized weighted shortest path lengths in the α band (t = -2.65; P = 0.01). δ Band-directed phase lag index was lower in anterior regions and higher in central regions in delirium patients than in nondelirium patients (F = 4.53; P = 0.04, and F = 7.65; P < 0.01, respectively).
Loss of α band functional connectivity, decreased path length, and increased δ band connectivity directed to frontal regions characterize the electroencephalography during delirium after cardiac surgery. These findings may explain why information processing is disturbed in delirium.
本文作者旨在通过对心脏手术后出现谵妄的患者的脑电图记录进行功能连接和网络拓扑分析,以增进对谵妄病理生理学和现象学的理解。作者假设,谵妄患者注意力和意识障碍可能与功能神经相互作用的改变有关。
作者对心脏手术后出现谵妄(n=25)和无谵妄(n=24)的患者进行了脑电图记录。作者使用相位滞后指数、有向相位滞后指数,以及基于图分析的功能脑网络拓扑分析,对脑电图时间序列的无偏功能连接进行了分析。
谵妄患者的α频段(8 至 13 Hz)平均相位滞后指数较低(中位数 0.120,四分位距 0.113 至 0.138),而非谵妄患者的平均相位滞后指数较高(中位数 0.140,四分位距 0.129 至 0.168;P<0.01)。谵妄患者的网络拓扑特征是α频段的标准化加权最短路径长度较低(t=-2.65,P=0.01)。与非谵妄患者相比,谵妄患者的δ频段有向相位滞后指数在前区较低,中区较高(F=4.53,P=0.04,和 F=7.65,P<0.01)。
心脏手术后谵妄患者脑电图的α频段功能连接丧失、路径长度缩短以及δ频段向前区的连接增加,这些特征可解释谵妄时信息处理为何受到干扰。