Authors
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Suma R, Netravathi M, Gururaj G, Thomas PT, Singh B, Solomon T, Desai A, Vasanthapuram R, Banandur PS -More
Category
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Primary study
Journal»Journal of global infectious diseases
Year
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2023
INTRODUCTION: Encephalitis is a major public health problem worldwide that causes huge emotional and economic loss to humanity. Encephalitis, being a serious illness, affects people of all ages. The aim is to describe the sociodemographic, clinical, etiological, and neuroimaging profile among 101 acute encephalitis syndrome (AES) patients visiting a tertiary neuro-specialty care hospital in India.
METHODS: Record review of medical records of all patients attending neurology emergency and outpatient services at NIMHANS Hospital, diagnosed with AES in 2019, was conducted. Data were collected using standardized data collection forms for all cases in the study. Descriptive analyses (mean and standard deviation for continuous variables and proportions for categorical variables) were conducted. The Chi-square test/Fisher's exact test was used for the comparison of independent groups for categorical variables, and t-test for comparing means for continuous variables.
RESULTS: About 42.6% of AES patients had viral etiology, while in 57.4%, etiology was not ascertained. Common presenting symptoms were fever (96%), altered sensorium (64.4%), seizures (70.3%), headache (42.6%), and vomiting (27.7%). Herpes simplex was the most common (21.8%) identified viral encephalitis, followed by chikungunya (5%), arboviruses (chikungunya and dengue) (4%), Japanese encephalitis (4%), rabies (3%), dengue (1%), and varicella virus (1%). About 40% of AES patients showed cerebrospinal fluid pleocytosis (44%), increased protein (39.6%), abnormal computed tomography brain (44.6%), and magnetic resonance imaging abnormalities (41.6%).
CONCLUSION: The study highlights the need to ascertain etiology and importance of evidence-based management of AES patients. A better understanding of opportunities and limitations in the management and implementation of standard laboratory and diagnostic algorithms can favor better diagnosis and management of AES.
Epistemonikos ID: b08215ea73bc3ee65e497d224b0afa79c3ffa7a0
First added on: Aug 30, 2024