Seizure Characteristics and EEG Features in Intoxication Type and Energy Deficiency Neurometabolic Disorders in the Pediatric Intensive Care Unit– Single Center Experience over 10 Years

Abstract

Introduction: Acute metabolic crises in inborn errors of metabolism (such as Urea Cycle Disorders, Organic Acidemia, Maple Syrup Urine Disease and Mitochondrial disorders) are neurological emergencies requiring management in the pediatric intensive care unit (PICU). There is paucity of data pertaining to EEG characteristics in this cohort. We hypothesized that the incidence of background abnormalities and seizures in this cohort would be high. Neuromonitoring data from our center’s PICU over 10 years is presented in this paper.Methods Data was collected by retrospective chart review for patients with the afore-mentioned disorders who were admitted to the PICU at our institution due to metabolic/ neurologic symptoms from 2008–2018. Descriptive statistics (Chi-square test or Fisher’s exact test) were used to study the association between EEG parameters and outcomes.Results Our cohort included 40 unique patients (8 UCD, 7 OA, 3 MSUD and 22 MD) with 153 admissions. Presenting symptoms included altered mentation (36%), seizures (41%), focal weakness (5%), and emesis (28%). Continuous EEG was ordered in 34% (n = 52) of admissions. Twenty-three admissions were complicated by seizures, including 8 manifesting status epilepticus (7 nonconvulsive, 1 convulsive). Asymmetry and focal slowing on EEG were associated with seizures. Moderate background slowing or worse was noted in 75% of EEGs. Among those patients monitored on EEG with a known outcome at discharge, 4 (8%) died, 3 (6%) experienced a worsening of their Pediatric Cerebral Performance Category (PCPC) score as compared to admission, and 44 (86%) had no change (or improvement) in their PCPC score during admission.Conclusion This study shows a high incidence of clinical and subclinical seizures during metabolic crisis in patients with IEMs. EEG background features were associated with risk of seizures as well as discharge outcomes. This is the largest study to date which investigates EEG features and risk of seizures in patients with neurometabolic disorders admitted to PICUs. This data can be used to form neuromonitoring protocols to improve mortality and morbidity in IEMs.