Quantitative EEG findings in patients with chronic renal failure

Department of Neurology, University Hospital Charité, Charitéplatz 1, 10117 Berlin, Germany.
European journal of medical research (Impact Factor: 1.5). 04/2007; 12(4):173-8.
Source: PubMed


Chronic renal failure frequently causes uremic encephalopathy with impairment of various cognitive functions, but the pathophysiology of uremic syndrome is complex and poorly understood. In this study, we wished to establish a reliable tool and monitor system to evaluate the central nervous system dysfunction of patients with uremic encephalopathy.
A group of 31 patients with chronic renal failure was assessed with online real time brain mapping using the CATEEM technology to detect deviations and abnormal EEG patterns. Quantitative EEG data were compared with those of an age-matched healthy control group and correlated to laboratory markers and various dosages of erythropoietin.
Electrical power was most prominent in delta, theta and alpha frequencies in the temporal and central brain areas (electrode positions T5, T6, C3 and C4). Explorative statistical comparison of the two data sets with respect to these brain areas revealed that the increases in electrical power in delta, theta and alpha frequency bands were different from healthy people with p-values of p<0.003 (delta), p<0.0003 (theta), p<0.01 (alpha 1) and p<0.01 (alpha 2). In addition, high levels of hemoglobin were significantly correlated with higher theta activity.
We detected distinct EEG deviations from normality in patients with chronic renal failure. Online real time brain mapping using the CATEEM technology provides a unique possibility to monitor mental impairment and serves as a control for therapeutical intervention.

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Available from: Jens Eric Roehl, Feb 04, 2014
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    ABSTRACT: Abstract Aim: To study Electroencephalogram (EEG) in different stages of chronic kidney disease (CKD). Materials and Methods: This observational study was carried out in the Department of Medicine, Jawaharlal Nehru Medical College, Sawangi (Meghe), Wardha conducted over a period of 24 months, spanning from August 2011 to August 2013. Eighty three cases of CKD at different stages were studied. EEG was done in all the subjects and the various EEG dynamics like morphometric waveform patterns, symmetricity, amplitude were recorded and compared with the different stages of CKD. Results: We found that characteristic changes were observed with increasing severity of CKD. Slow delta wave patterns were more prominent in stage 5 (p<0.0001), asymmetric discharges, dysthymia, sharp wave transients and low amplitude wave forms were more prominent beyond Stage 4 (p<0.0001). Conclusion: EEG can be used as an effective tool for detection of subclinical or latent uremic encephalopathy. EEG findings which are characteristics of uremic encephalopathy can be present in CKD patients without overt signs of encephalopathy. So, EEG can be used as a prognostic indicator of response to clinical therapy of CKD. Keywords : Dysthymia, Encephalopathy, Uremia
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