Prediction of acute encephalopathy with biphasic seizures and late reduced diffusion in patients with febrile status epilepticus

• Published in: Brain & development (Tokyo. 1979) Vol. 38; no. 2; pp. 217 - 224
• Main Authors: Yokochi, Takaoki, Takeuchi, Takahito, Mukai, Jumpei, Akita, Yukihiro, Nagai, Kojiro, Obu, Keizo, Kakuma, Tatsuyuki, Matsuishi, Toyojiro
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.02.2016
• Subjects: Acute encephalopathy; Adolescent; Biphasic; Brain Diseases - diagnosis; Brain Diseases - physiopathology; Brain hypothermia; Child; Child, Preschool; Complex febrile seizures; Diffusion Magnetic Resonance Imaging; Diffusion MRI; Female; Humans; Infant; Japan; Male; Neurology; Predictive Value of Tests; Seizures - diagnosis; Seizures - physiopathology; Seizures, Febrile - diagnosis; Seizures, Febrile - physiopathology; Status epilepticus; Status Epilepticus - diagnosis; Status Epilepticus - physiopathology; Biphasic; Diffusion MRI; Complex febrile seizures; Brain hypothermia; Status epilepticus; Acute encephalopathy
• ISSN: 0387-7604; 1872-7131
• DOI: 10.1016/j.braindev.2015.07.007

Abstract Introduction Acute encephalopathy with biphasic seizures and late reduced diffusion (AESD) is the most common subtype of acute encephalopathy among children in Japan. The pathogenesis of AESD is mostly delayed cerebral edema caused by excitotoxic injury. It is difficult to discriminate AESD and complex febrile seizure in the early phase. Many cases have neurologic sequelae because early intervention is difficult. Methods To establish an early diagnostic method, we assessed 213 hospitalized cases of febrile status epilepticus (FSE) between January 2004 and August 2014. We categorized FSE cases into an AESD group and a non-AESD group and compared their clinical courses, laboratory data and cranial computed tomography (CT) findings. Results Of 213 hospitalized FSE cases, 19 (9%) were AESD. Univariate analysis showed that the AESD group took a significantly longer time to wake after FSE, had a higher degree of respiratory acidemia, and higher levels of serum AST, ALT, LD, hyperglycemia and hyperammonemia than the non-AESD group. We developed a scoring model that predicts AESD based on multivariate analysis. Using cut-off points of 4 and more with this scoring model, we could identify the AESD cases with 93% sensitivity and 91% specificity. These scores also had a positive correlation with prognosis. Discussion Our scoring model enables early diagnosis of AESD. Patients with high scores should be observed carefully and early intervention should be considered.