Tama, Whisnu Nalendra
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Abnormal electroencephalographyas predictor of mortality in meningoencephalitis Tama, Whisnu Nalendra; Satiti, Sekar; Asmedi, Ahmad
Journal of the Medical Sciences (Berkala Ilmu Kedokteran) Vol 52, No 1 (2020)
Publisher : Journal of the Medical Sciences (Berkala Ilmu Kedokteran)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (796.225 KB) | DOI: 10.19106/JMedSci005201202004

Abstract

Although the incidence of meningoencephalitis has decreased,howeverits mortality remainshigh. Electroencephalography (EEG) has an important role in the management of meningoencephalitis although the imaging modalities have replaced its position. Abnormality in EEG may appear earlier than in imaging so it is expected to predict mortality.The study aimed to investigate the prognostic role of EEG results in predicting mortality of meningoencephalitis.This was an observational prospective cohort study involvingmeningoencephalitis patients in Dr. Sardjito General Hospital,Yogyakartafrom July 2016 to January 2017 who underwent EEG examination.The patients who met the inclusion and exclusion criteria were divided into abnormal and normal EEG groups. The outcomewas the mortality during hospitalization. Furthermore, the type of EEG abnormalities associated with mortality were evaluated.Thirty-eight patients with the mean age was 33.61±20.37 yearwere involved in this study. Twenty-eight patients (73.7%) had abnormal EEG result and 10 patients (26.3%) death.Bivariate analysis showed that abnormal EEG result (p =0.028) and Glasgow Coma Scale (GCS) score (p =0.005) were significantly associated with mortality. Analysis for the type of EEG abnormalities found that only diffuse slowing (p =0.001) was significantly associated with mortality. Multivariate analysis showed either abnormal EEG result or GCS score were independently predictor of mortality. Abnormal EEG and GCS score were interrelated in affecting mortality.In conclusion, abnormal EEG resultin meningoencephalitis, diffuse slowing in particular, is predictor of mortality during hospitalization