A low-cost, user-friendly electroencephalographic recording system for the assessment of hepatic encephalopathy
A low-cost, user-friendly electroencephalographic recording system for the assessment of hepatic encephalopathy
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DOI：
10.1002/hep.28477
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发表时间：
2016-05-01
期刊：
影响因子：
13.5
通讯作者：
Montagnese, Sara
中科院分区：
文献类型：
--
作者：
Schiff, Sami;Casa, Mariella;Montagnese, Sara
脑电图（EEG）可用于客观诊断/分级肝性脑病（HE）的严重程度。然而，它需要昂贵的设备，肝胃肠病学家通常不熟悉其采集/解释。最近的技术进步导致了低成本、用户友好的EEG系统的发展，允许在神经生理学经验有限的环境中也进行EEG采集。本研究的目的是评估从标准EEG系统和从商业，低成本的无线耳机（光EEG）在肝硬化和不同程度的HE患者获得的EEG参数之间的关系。72例患者（58例男性，61 ± 9岁）接受了临床评价、心理测量肝性脑病评分（PHES）和两种系统的EEG记录。在两个推导上计算自动EEG参数。从两个EEG系统获得的自动化参数之间观察到强相关性。Bland和Altman分析表明，这两个系统提供了相当的自动化参数，并且基于标准EEG和轻度EEG的分类（正常与异常EEG）之间的一致性良好（0.6 < < 0.8）。自动化参数，如从光脑电图获得的平均主频与终末期肝病模型评分（r =-0.39，P < 0.05）、空腹静脉血氨水平（r =-0.41，P < 0.01）和PHES（r =-0.49，P < 0.001）显著相关。最后，在不同程度的HE患者中观察到光EEG参数的显著差异。结论：用于HE诊断/分级的可靠EEG参数可以从廉价的商业无线耳机中获得;这可能导致在常规肝脏实践和研究环境中更广泛地使用这种独立于患者的工具。（肝病学2016;63：1651-1659）
Electroencephalography (EEG) is useful to objectively diagnose/grade hepatic encephalopathy (HE) across its spectrum of severity. However, it requires expensive equipment, and hepatogastroenterologists are generally unfamiliar with its acquisition/interpretation. Recent technological advances have led to the development of low-cost, user-friendly EEG systems, allowing EEG acquisition also in settings with limited neurophysiological experience. The aim of this study was to assess the relationship between EEG parameters obtained from a standard-EEG system and from a commercial, low-cost wireless headset (light-EEG) in patients with cirrhosis and varying degrees of HE. Seventy-two patients (58 males, 61 +/- 9 years) underwent clinical evaluation, the Psychometric Hepatic Encephalopathy Score (PHES), and EEG recording with both systems. Automated EEG parameters were calculated on two derivations. Strong correlations were observed between automated parameters obtained from the two EEG systems. Bland and Altman analysis indicated that the two systems provided comparable automated parameters, and agreement between classifications (normal versus abnormal EEG) based on standard-EEG and light-EEG was good (0.6 < < 0.8). Automated parameters such as the mean dominant frequency obtained from the light-EEG correlated significantly with the Model for End-Stage Liver Disease score (r = -0.39, P < 0.05), fasting venous ammonia levels (r = -0.41, P < 0.01), and PHES (r = -0.49, P < 0.001). Finally, significant differences in light-EEG parameters were observed in patients with varying degrees of HE. Conclusion: Reliable EEG parameters for HE diagnosing/grading can be obtained from a cheap, commercial, wireless headset; this may lead to more widespread use of this patient-independent tool both in routine liver practice and in the research setting. (Hepatology 2016;63:1651-1659)