UNLABELLED: 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 < κ < 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. (
UNLABELLED: 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 < κ < 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. (