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Objective The aim of the study is to model amplitude-integrated electroencephalography (aEEG) utility to diagnose seizures in common clinical scenarios. Study Design Using reported neonatal seizure prevalence and aEEG sensitivities and specificities, likelihood ratios (LRs) and post-test probabilities were calculated to quantify aEEG utility to diagnose seizures in three typical clinical scenarios. Results Prevalence data supported pretest probabilities for neonatal seizures of 0.4 in neonatal hypoxic ischemic encephalopathy (HIE), 0.27 in bacterial meningitis, and 0.05 in extreme prematurity. Reported sensitivity of 85% and specificity of 90% for seizures with expert aEEG interpretation yielded a positive likelihood ratio (LR+) of 8.7 and a negative likelihood ratio (LR−) of 0.17. Reported sensitivity of 65% and specificity of 70% with intermediate interpretation yielded LR+ 2.17 and LR− 0.5. Reported sensitivity of 40% and sensitivity of 50% with inexperienced interpretation gave LR+ 0.8 and LR− 1.2. These translate the ability to move pretest to post-test probability highly dependent on user expertise. For HIE, a pretest probability of seizure of 0.4 moves to a post-test probability of 0.85 when aEEG is positive for seizures by expert interpretation, and down to 0.1 when aEEG is negative. In contrast, no useful information was gained between pretest and post-test probability by aEEG interpreted as negative or positive for seizure at the inexperienced user level. Similarly, in the models of meningitis or extreme prematurity, incremental information gained from aEEG ranged widely based on interpreter experience. Conclusion aEEG is most useful to screen for neonatal seizures when used in conditions with high seizure prevalence, and when interpretation has a sensitivity and specificity as reported for expert users. In contrast, aEEG can become negligible in providing meaningful clinical information when applied in conditions having lower seizure prevalence or when interpretation has low accuracy. Appropriate patient selection and high quality interpretation are essential for aEEG utility in neonatal seizure detection. Key Points

A full-term female neonate developed focal motor seizures at 1 hour of life, followed by paroxysmal nonepileptic abnormal eye-head movements on day 5 (video 1). CSF revealed mild hypoglycorrhachia, borderline low CSF:serum glucose, and low pyridoxal-59-phosphate (P5P). Genetic testing showed compound heterozygous mutations in the pyridoxamine 59phosphate oxidase (PNPO) gene consistent with P5P-dependent epilepsy. Aberrant gaze saccades with head jerks are classically described in GLUT-1 deficiency, 1 though not described in other conditions with associated hypoglycorrhachia. PNPO-associated epilepsy has been associated with abnormal eye movements 2 and should be considered when neonates present with seizures and aberrant saccades with coordinated head movements. Study FundingNo targeted funding reported.

Continuous EEG (cEEG) is a fundamental neurodiagnostic tool in the care of critically ill neonates and is increasingly recommended. cEEG enhances prognostication via assessment of the background brain activity, plays a role in predicting which neonates are at risk for seizures when combined with clinical factors, and allows for accurate diagnosis and management of neonatal seizures. Continuous EEG is the gold standard method for diagnosis of neonatal seizures and should be used for detection of seizures in high-risk clinical conditions, differential diagnosis of paroxysmal events, and assessment of response to treatment. High costs associated with cEEG are a limiting factor in its widespread implementation. Centralized remote cEEG interpretation, automated seizure detection, and pre-natal EEG are potential future applications of this neurodiagnostic tool.

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Background Guidelines recommend evaluation for electrographic seizures in neonates and children at risk, including after cardiopulmonary bypass (CPB). Although initial research using screening electroencephalograms (EEGs) in infants after CPB found a 21% seizure incidence, more recent work reports seizure incidences ranging 3–12%. Deep hypothermic cardiac arrest was associated with increased seizure risk in prior reports but is uncommon at our institution and less widely used in contemporary practice. This study seeks to establish the incidence of seizures among infants following CPB in the absence of deep hypothermic cardiac arrest and to identify additional risk factors for seizures via a prediction model. Methods A retrospective chart review was completed of all consecutive infants ≤ 3 months who received screening EEG following CPB at a single center within a 2-year period during 2017–2019. Clinical and laboratory data were collected from the perioperative period. A prediction model for seizure risk was fit using a random forest algorithm, and receiver operator characteristics were assessed to classify predictions. Fisher’s exact test and the logrank test were used to evaluate associations between clinical outcomes and EEG seizures. Results A total of 112 infants were included. Seizure incidence was 10.7%. Median time to first seizure was 28.1 h (interquartile range 18.9–32.2 h). The most important factors in predicting seizure risk from the random forest analysis included postoperative neuromuscular blockade, prematurity, delayed sternal closure, bypass time, and critical illness preoperatively. When variables captured during the EEG recording were included, abnormal postoperative neuroimaging and peak lactate were also highly predictive. Overall model accuracy was 90.2%; accounting for class imbalance, the model had excellent sensitivity and specificity (1.00 and 0.89, respectively). Conclusions Seizure incidence was similar to recent estimates even in the absence of deep hypothermic cardiac arrest. By employing random forest analysis, we were able to identify novel risk factors for postoperative seizure in this population and generate a robust model of seizure risk. Further work to validate our model in an external population is needed. Supplementary Information The online version contains supplementary material available at 10.1007/s12028-021-01313-1.

Pediatric neurology patients frequently use integrative medicine; however, providers may feel uncomfortable or unfamiliar with these therapies. Child neurologist attitudes toward integrative medicine and educational needs in integrative medicine have not been assessed. A national, anonymous survey was distributed to Child Neurology residents (n=294) and program directors (n=71) to assess attitudes toward specific integrative medicine modalities, practices in discussing integrative medicine with patients, and perceived need for a curriculum on integrative medicine; 61 (17%) partially and 53 (15%) fully completed the survey. Comparative analyses applied chi-square and independent t tests. Qualitative content analysis was performed on free text responses. Most providers surveyed consider mind and body practices safe (93% of respondents) and effective (84%), but have concerns about the safety of chiropractic manipulation (56% felt this was harmful), and the efficacy of homeopathy (none considered this effective). Few inquire about patient integrative medicine use regularly. Child Neurology residents are interested in further education on this topic.

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