Acute febrile encephalopathy (AFE) is an emergent neurological condition that presents with fever and altered mental status, necessitating rapid diagnosis and intervention due to its complex etiology and potentially severe outcomes. This study investigates the clinical and laboratory predictors of outcomes in AFE patients treated at Jawaharlal Nehru Medical College, Aligarh, India, focusing on factors that influence mortality and functional status using the modified Rankin Scale (mRS). Conducted prospectively, the research evaluated patients over 14 years of age presenting with fever, neurological deficits, and altered sensorium for <14 days. Exclusion criteria included cerebrovascular incidents, metabolic and endocrine causes of altered mental status, and trauma. The study reveals a significant correlation between factors like prolonged sensorium alteration, shock, respiratory distress, and high serum potassium levels with adverse outcomes, including high mortality rates. Additionally, the presence of tubercular meningitis (TBM), a major cause of AFE in this cohort, was linked with poor prognosis, highlighting the endemic nature of tuberculosis in North India as a key determinant in AFE etiology. Gender and age were influential, with older age and male gender showing worse functional outcomes. Radiological findings, especially meningeal enhancement on contrast-enhanced computed tomography scans and diffuse cerebral edema on magnetic resonance imaging, were strongly associated with mortality and higher mRS scores. Key biochemical markers, such as dehydration, anemia, and serum sodium, potassium, and calcium levels, were also predictive of patient outcomes, underscoring the need for comprehensive laboratory assessment in AFE cases. The study suggests that early and targeted intervention in high-risk cases is essential to improve patient outcomes. This research advocates for enhanced diagnostic protocols and targeted public health strategies to mitigate the impact of infectious AFE etiologies in high-burden regions, particularly in resource-limited settings.
Singh et al. (Tue,) studied this question.