Pradyumna Gadewar1, Sourya Acharya2, Praveen Khairkar3, Samarth Shukla4, S N Mahajan2. 1. Assistant Professor, Department of Medicine, JNMC, DMIMSU , Wardha, Maharashtra, India . 2. Professor, Department of Medicine, JNMC, DMIMSU , Wardha, Maharashtra, India . 3. Professor, Department of Psychiatry, MGIMS, Sewagram , Wardha, Maharashtra, India . 4. Professor, Department of Pathology, JNMC, DMIMSU , Wardha, Maharashtra, India .
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.
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.
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