Author/Authors :
P. Amodio، نويسنده , , Alfred P. Marchetti، نويسنده , , F. Del Piccolo، نويسنده , , M. de Tourtchaninoff، نويسنده , , Femina P. Varghese، نويسنده , , C. Zuliani، نويسنده , , G. Campo، نويسنده , , A. GATTA، نويسنده , , J. M. Guérit، نويسنده ,
Abstract :
Objective: Spectral EEG analysis has been claimed to reduce subjective variability in EEG assessment of hepatic encephalopathy and to allow the detection of mild encephalopathy.
Method: To test such assumptions, 43 digital EEG were recorded in 32 cirrhotics without overt encephalopathy or with grade 1 overt encephalopathy; 7 patients were re-tested (2–5 times) in their follow up. All patients underwent psychometric assessment. Nineteen controls were considered. EEG were blindly evaluated by two electroencephalographers and by spectral EEG analysis performed according to 3 different techniques.
Results: The reliability of the classification based on spectral analysis (biparietal technique) was higher than that based on a three-degree qualitative visual reading (concordance/discordance=58/4 versus 46/16 P<0.01) and comparable with that of semiquantitative visual assessment based on posterior basic rhythm (concordance/discordance=55/7 P=0.5). The accuracy of spectral EEG analysis was higher than that of qualitative visual EEG readings alone (90 versus 75%) and comparable to semi-quantitative visual assessment (87%), however, statistical significance was not reached. In the follow-up, the variations of theta and delta relative power were found to be significantly correlated with psychometric variations.
Conclusions: In conclusion, spectral EEG analysis may improve the assessment of mild hepatic encephalopathy by decreasing interoperator variability and providing reliable parameters correlated with mental status.
Keywords :
Hepatic encephalopathy , EEG automatic analysis , EEG spectral analysis , EEG , Psychometic alterations