TITLE:
Frequency of Neurological Disorders and Related EEG Finding in a Tertiary Care Hospital of Karachi
AUTHORS:
Danish Mohammad, Syeda Saba Zaidi, Bina Fawad, Muhammad Fazal Hussain Qureshi, Zain Jawed Abubaker, Muhammad Zubair Shaikh, Muzna Shah, Mahira Lakhani, Sara Sadiq
KEYWORDS:
Neurological Disorders, EEG, Association
JOURNAL NAME:
Journal of Biosciences and Medicines,
Vol.7 No.11,
November
7,
2019
ABSTRACT: Background: Electroencephalogram (EEG) is defined as a method of detecting brain waves signifying the electrical conductivity of the brain. Globally, EEG is used to further classify neuropsychiatric disorders. Objective: To evaluate the prevalence of abnormal EEGs and related neurological disorders and it’s correlation with age and gender. Methodology: A descriptive cross sectional study was conducted in Neurology department, Ziauddin hospital, Karachi, Pakistan from June 2018 to May 2019. A total of 440 individuals based on inclusion criteria were selected through Non-probability consecutive sampling. Informed consent was obtained from study participants. A self-designed structured questionnaire and EEG record were used for data collection. Data were entered and analyzed using SPSS v 20. Mean and standard deviation was calculated for numerical variable and frequency and percentages were calculated for categorical variable. Independent t-test and chi square was used to check association of abnormal EEG with age and gender. P value of ≤0.05 was considered statistically significant. Results: The mean age of study participants was 52.98 ± 22.68 years. There were 54.5% (n = 240) males. Approximately 45.2% (n = 199) participants had predisposing condition which can lead to abnormal EEG. EEG records of 39.8% (n = 175) of the patients was normal while 60.2% (n = 265) had abnormal records. Diffuse neuronal dysfunction consistent with encephalopathy was found in 45.2%. Mild neuronal dysfunction consistent with encephalopathy accounted for 33.5% of cases. Significant difference was found in Abnormal EEG among different age group (p = 0.01). Chi square shows an association between abnormal EEG and male gender (p = 0.025). Conclusion: EEG plays a vital role in the diagnosis of neuropsychiatric conditions in developing countries. EEGs can further help to determine the relationship of different neuropsychiatric conditions and can help in early diagnosis and better prognosis.