Craig A Press1, Lindsey Morgan, Michele Mills, Cynthia V Stack, Joshua L Goldstein, Estella M Alonso, Mark S Wainwright. 1. 1Ruth D. & Ken M. Davee Pediatric Neurocritical Care Program, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern Feinberg School of Medicine, Chicago, IL.2Division of Neurology, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern Feinberg School of Medicine, Chicago, IL.3Division of Critical Care, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern Feinberg School of Medicine, Chicago, IL.4Division of Gastroenterology, Hepatology and Nutrition, Department of Pediatrics, Ann & Robert H. Lurie Children's Hospital of Chicago, Northwestern Feinberg School of Medicine, Chicago, IL.
Abstract
OBJECTIVE: Spectral electroencephalogram analysis is a method for automated analysis of electroencephalogram patterns, which can be performed at the bedside. We sought to determine the utility of spectral electroencephalogram for grading hepatic encephalopathy in children with acute liver failure. DESIGN: Retrospective cohort study. SETTING: Tertiary care pediatric hospital. PATIENTS: Patients between 0 and 18 years old who presented with acute liver failure and were admitted to the PICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Electroencephalograms were analyzed by spectral analysis including total power, relative δ, relative θ, relative α, relative β, θ-to-Δ ratio, and α-to-Δ ratio. Normal values and ranges were first derived using normal electroencephalograms from 70 children of 0-18 years old. Age had a significant effect on each variable measured (p < 0.03). Electroencephalograms from 33 patients with acute liver failure were available for spectral analysis. The median age was 4.3 years, 14 of 33 were male, and the majority had an indeterminate etiology of acute liver failure. Neuroimaging was performed in 26 cases and was normal in 20 cases (77%). The majority (64%) survived, and 82% had a good outcome with a score of 1-3 on the Pediatric Glasgow Outcome Scale-Extended at the time of discharge. Hepatic encephalopathy grade correlated with the qualitative visual electroencephalogram scores assigned by blinded neurophysiologists (rs = 0.493; p < 0.006). Spectral electroencephalogram characteristics varied significantly with the qualitative electroencephalogram classification (p < 0.05). Spectral electroencephalogram variables including relative Δ, relative θ, relative α, θ-to-Δ ratio, and α-to-Δ ratio all significantly varied with the qualitative electroencephalogram (p < 0.025). Moderate to severe hepatic encephalopathy was correlated with a total power of less than or equal to 50% of normal for children 0-3 years old, and with a relative θ of less than or equal to 50% normal for children more than 3 years old (p > 0.05). Spectral electroencephalogram classification correlated with outcome (p < 0.05). CONCLUSIONS: Spectral electroencephalogram analysis can be used to evaluate even young patients for hepatic encephalopathy and correlates with outcome. Spectral electroencephalogram may allow improved quantitative and reproducible assessment of hepatic encephalopathy grade in children with acute liver failure.
OBJECTIVE: Spectral electroencephalogram analysis is a method for automated analysis of electroencephalogram patterns, which can be performed at the bedside. We sought to determine the utility of spectral electroencephalogram for grading hepatic encephalopathy in children with acute liver failure. DESIGN: Retrospective cohort study. SETTING: Tertiary care pediatric hospital. PATIENTS: Patients between 0 and 18 years old who presented with acute liver failure and were admitted to the PICU. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Electroencephalograms were analyzed by spectral analysis including total power, relative δ, relative θ, relative α, relative β, θ-to-Δ ratio, and α-to-Δ ratio. Normal values and ranges were first derived using normal electroencephalograms from 70 children of 0-18 years old. Age had a significant effect on each variable measured (p < 0.03). Electroencephalograms from 33 patients with acute liver failure were available for spectral analysis. The median age was 4.3 years, 14 of 33 were male, and the majority had an indeterminate etiology of acute liver failure. Neuroimaging was performed in 26 cases and was normal in 20 cases (77%). The majority (64%) survived, and 82% had a good outcome with a score of 1-3 on the Pediatric Glasgow Outcome Scale-Extended at the time of discharge. Hepatic encephalopathy grade correlated with the qualitative visual electroencephalogram scores assigned by blinded neurophysiologists (rs = 0.493; p < 0.006). Spectral electroencephalogram characteristics varied significantly with the qualitative electroencephalogram classification (p < 0.05). Spectral electroencephalogram variables including relative Δ, relative θ, relative α, θ-to-Δ ratio, and α-to-Δ ratio all significantly varied with the qualitative electroencephalogram (p < 0.025). Moderate to severe hepatic encephalopathy was correlated with a total power of less than or equal to 50% of normal for children 0-3 years old, and with a relative θ of less than or equal to 50% normal for children more than 3 years old (p > 0.05). Spectral electroencephalogram classification correlated with outcome (p < 0.05). CONCLUSIONS: Spectral electroencephalogram analysis can be used to evaluate even young patients for hepatic encephalopathy and correlates with outcome. Spectral electroencephalogram may allow improved quantitative and reproducible assessment of hepatic encephalopathy grade in children with acute liver failure.
Authors: Alexander Andrews; Tesfaye Zelleke; Rima Izem; Jiaxiang Gai; Dana Harrar; Jessica Mvula; Douglas G Postels Journal: Pediatr Neurol Date: 2021-10-19 Impact factor: 3.372
Authors: Matthew P Kirschen; Kerri LaRovere; Binod Balakrishnan; Jennifer Erklauer; Conall Francoeur; Saptharishi Lalgudi Ganesan; Anuj Jayakar; Marlina Lovett; Matthew Luchette; Craig A Press; Michael Wolf; Peter Ferrazzano; Mark S Wainwright; Brian Appavu Journal: Pediatr Neurol Date: 2021-11-12 Impact factor: 4.210