Montagnese Sara, Jackson Clive, Morgan Marsha Y
The UCL Institute of Hepatology, Department of Medicine, Hampstead Campus, Royal Free & University College Medical School, University College London, Rowland Hill Street, London NW3 2PF, UK.
J Hepatol. 2007 Mar;46(3):447-58. doi: 10.1016/j.jhep.2006.10.015. Epub 2006 Nov 27.
BACKGROUND/AIMS: Slowing of the electroencephalogram (EEG) is a recognised feature of hepatic encephalopathy but its diagnostic sensitivity is indeterminate. Recent advances in EEG analysis should provide better quantifiable/more informative data. The aim of this study was to isolate and determine the scalp distribution of the posterior basic rhythm, in patients with cirrhosis, using a technique for spatio-temporal decomposition (SEDACA) of the EEG.
One hundred and ten patients with cirrhosis, classified, using clinical and psychometric criteria, as neuropsychiatrically unimpaired or as having minimal/overt hepatic encephalopathy were studied. Eyes-closed, awake EEGs were obtained and subjected to standard spectral analysis and spatio-temporal decomposition. Control data were obtained from 26 reference EEGs.
The error in the estimate of the SEDACA-derived mean dominant frequency was lower than for the standard EEG derivation (P<0.00001). The SEDACA-derived spectral estimates correlated better with neuropsychiatric status and allowed differentiation of the patients with minimal hepatic encephalopathy from the reference population. The SEDACA-derived spatial information showed an anteriorization of the posterior basic rhythm, which became more prominent as the degree of neuropsychiatric impairment increased (P=0.00052).
Analysis of the EEG utilising SEDACA provides significantly more diagnostic information on the neuropsychiatric status of patients with cirrhosis than obtained conventionally.
背景/目的:脑电图(EEG)减慢是肝性脑病的一个公认特征,但其诊断敏感性尚不确定。EEG分析的最新进展应能提供更好的可量化/信息更丰富的数据。本研究的目的是使用EEG的时空分解技术(SEDACA),分离并确定肝硬化患者后基本节律的头皮分布。
对110例肝硬化患者进行研究,根据临床和心理测量标准,将其分类为神经精神未受损或患有轻微/明显肝性脑病。在闭眼、清醒状态下获取EEG,并进行标准频谱分析和时空分解。对照数据来自26份参考EEG。
SEDACA得出的平均主导频率估计误差低于标准EEG推导得出的误差(P<0.00001)。SEDACA得出的频谱估计与神经精神状态的相关性更好,并且能够区分轻微肝性脑病患者与参考人群。SEDACA得出的空间信息显示后基本节律向前移位,随着神经精神损害程度的增加,这种移位变得更加明显(P=0.00052)。
与传统方法相比,利用SEDACA分析EEG能为肝硬化患者的神经精神状态提供显著更多的诊断信息。