Objective Electroencephalographic seizures (ESs) are common in encephalopathic critically ill children, but ES identification with continuous electroencephalography (EEG) monitoring (CEEG) is resource‐intense. We aimed to develop an ES prediction model that would enable clinicians to stratify patients by ES risk and optimally target limited CEEG resources. We aimed to determine whether incorporating data from a screening EEG yielded better performance characteristics than models using clinical variables alone. Methods We performed a prospective observational study of 719 consecutive critically ill children with acute encephalopathy undergoing CEEG in the pediatric intensive care unit of a quaternary care institution between April 2017 and February 2019. We identified clinical and EEG risk factors for ES. We evaluated model performance with area under the receiver‐operating characteristic (ROC) curve (AUC), validated the optimal model with the highest AUC using a fivefold cross‐validation, and calculated test characteristics emphasizing high sensitivity. We applied the optimal operating slope strategy to identify the optimal cutoff to define whether a patient should undergo CEEG. Results The incidence of ES was 26%. Variables associated with increased ES risk included age, acute encephalopathy category, clinical seizures prior to CEEG initiation, EEG background, and epileptiform discharges. Combining clinical and EEG variables yielded better model performance (AUC 0.80) than clinical variables alone (AUC 0.69; P < .01). At a 0.10 cutoff selected to emphasize sensitivity, the optimal model had a sensitivity of 92%, specificity of 37%, positive predictive value of 34%, and negative predictive value of 93%. If applied, the model would limit 29% of patients from undergoing CEEG while failing to identify 8% of patients with ES. Significance A model employing readily available clinical and EEG variables could target limited CEEG resources to critically ill children at highest risk for ES, making CEEG‐guided management a more viable neuroprotective strategy.

ObjectiveTo determine the association between electroencephalographic seizure (ES) and electroencephalographic status epilepticus (ESE) exposure and unfavorable neurobehavioral outcomes in critically ill children with acute encephalopathy.MethodsThis was a prospective cohort study of acutely encephalopathic critically ill children undergoing continuous EEG monitoring (CEEG). ES exposure was assessed as (1) no ES/ESE, (2) ES, or (3) ESE. Outcomes assessed at discharge included the Glasgow Outcome Scale–Extended Pediatric Version (GOS-E-Peds), Pediatric Cerebral Performance Category (PCPC), and mortality. Unfavorable outcome was defined as a reduction in GOS-E-Peds or PCPC score from preadmission to discharge. Stepwise selection was used to generate multivariate logistic regression models that assessed associations between ES exposure and outcomes while adjusting for multiple other variables.ResultsAmong 719 consecutive critically ill patients, there was no evidence of ES in 535 patients (74.4%), ES occurred in 140 patients (19.5%), and ESE in 44 patients (6.1%). The final multivariable logistic regression analyses included ES exposure, age dichotomized at 1 year, acute encephalopathy category, initial EEG background category, comatose at CEEG initiation, and Pediatric Index of Mortality 2 score. There was an association between ESE and unfavorable GOS-E-Peds (odds ratio 2.21, 95% confidence interval 1.07–4.54) and PCPC (odds ratio 2.17, 95% confidence interval 1.05–4.51) but not mortality. There was no association between ES and unfavorable outcome or mortality.ConclusionsAmong acutely encephalopathic critically ill children, there was an association between ESE and unfavorable neurobehavioral outcomes, but no association between ESE and mortality. ES exposure was not associated with unfavorable neurobehavioral outcomes or mortality.

Objective Guidelines recommend that encephalopathic critically ill children undergo continuous electroencephalographic (CEEG) monitoring for electrographic seizure (ES) identification and management. However, limited data exist on antiseizure medication (ASM) safety for ES treatment in critically ill children. Methods We performed a single‐center prospective observational study of encephalopathic critically ill children undergoing CEEG. Clinical and EEG features and ASM utilization patterns were evaluated. We determined the incidence, types, and risk factors for adverse events associated with ASM administration. Results A total of 472 consecutive critically ill children undergoing CEEG were enrolled. ES occurred in 131 children (28%). Clinicians administered ASM to 108 children with ES (82%). ES terminated after the initial ASM in 38% of patients who received one ASM, after the second ASM in 35% of patients who received two ASMs, after the third ASM in 50% of patients who received three ASMs, and after the fourth ASM in 53% of patients who received four ASMs. Thirty patients (28%) received anesthetic infusions for ES management. Adverse events occurred in 18 patients (17%). Adverse effects were expected and resolved in all patients, and they were generally serious (in 15 patients) and definitely related (in 12 patients). Adverse events were rare in patients with acute symptomatic seizures requiring only one to two ASMs for treatment, but were more common in children with epilepsy, ictal‐interictal continuum EEG patterns, or patients requiring more extensive ASM management. Significance ES ceased after one ASM in only 38% of critically ill children but ceased after two ASMs in 73% of critically ill children. Thus, ES management was often accomplished with readily available medications, but optimization of multistep ES management strategies might be beneficial. Adverse events were rare and manageable in children with acute symptomatic seizures requiring only one to two ASMs for treatment. Future studies are needed to determine whether management of acute symptomatic ES improves neurobehavioral outcomes.

ObjectivesDetermine the optimal duration of continuous EEG monitoring (CEEG) for electrographic seizure (ES) identification in critically ill children.MethodsWe performed a prospective observational cohort study of 719 consecutive critically ill children with encephalopathy. We evaluated baseline clinical risk factors (age and prior clinically evident seizures) and emergent CEEG risk factors (epileptiform discharges and ictal-interictal continuum patterns) using a multi-state survival model. For each subgroup, we determined the CEEG duration for which the risk of ES was <5% and <2%.ResultsES occurred in 184 children (26%). Patients achieved <5% risk of ES after: (1) ∼6 hours if ≥1 year without prior seizures or EEG risk factors; (2) ∼1 day if <1 year without prior seizures or EEG risks; (3) ∼1 day if ≥1 year with either prior seizures or EEG risks; (4) ∼2 days if ≥1 year with prior seizures and EEG risks; (5) ∼2 days if <1 year without prior seizures but with EEG risks; and (6) ∼2.5 days if <1 year with prior seizures irrespective of the presence of EEG risks. Patients achieved <2% risk of ES at the same durations except patients without prior seizures or EEG risk factors would require longer CEEG (∼1.5 days if <1 year; ∼1 day if ≥1 year).ConclusionsA model derived from 2 baseline clinical risk factors and emergent EEG risk factors would allow clinicians to implement personalized strategies that optimally target limited CEEG resources. This would enable more widespread use of CEEG-guided management as a potential neuroprotective strategy.

Objective: Electroencephalographic seizures (ESs) are common in encephalopathic critically ill children, but identification requires extensive resources for continuous electroencephalographic monitoring (CEEG). In a previous study, we developed a clinical prediction rule using three clinical variables (age, acute encephalopathy category, clinically evident seizure[s] prior to CEEG initiation) and two electroencephalographic (EEG) variables (EEG background category and interictal discharges within the first 30 minutes of EEG) to identify patients at high risk for ESs for whom CEEG might be essential. In the current study, we aimed to validate the ES prediction model using an independent cohort. Methods: The prospectively acquired validation cohort consisted of 314 consecutive critically ill children treated in the Pediatric Intensive Care Unit of a quaternary care referral hospital with acute encephalopathy undergoing clinically indicated CEEG. We calculated test characteristics using the previously developed prediction model in the validation cohort. As in the generation cohort study, we selected a 0.10 cutpoint to emphasize sensitivity. Results: The incidence of ESs in the validation cohort was 22%. The generation and validation cohorts were alike in most clinical and EEG characteristics. The ES prediction model was well calibrated and well discriminating in the validation cohort. The model had a sensitivity of 90%, specificity of 37%, positive predictive value of 28%, and negative predictive value of 93%. If applied, the model would limit 31% of patients from undergoing CEEG while failing to identify 10% of patients with ESs. The model had similar performance characteristics in the generation and validation cohorts. Significance: A model employing five readily available clinical and EEG variables performed well when validated in a new consecutive cohort. Implementation would substantially reduce CEEG utilization, although some patients with ESs would not be identified. This model may serve a critical role in targeting limited CEEG resources to critically ill children at highest risk for ESs. How to cite this article: Fung FW, Parikh DS, Jacobwitz M, et al. Validation of a model to predict electroencephalographic seizures in critically ill children.

Background Extra-Corporeal Membrane Oxygenation (ECMO) is a life-saving intervention for severe respiratory and cardiac diseases. However, 50% of survivors have abnormal neurologic exams. Current ECMO management is guided by systemic metrics, which may poorly predict cerebral perfusion. Continuous optical monitoring of cerebral hemodynamics during ECMO holds potential to detect risk factors of brain injury such as impaired cerebrovascular autoregulation ( CA ). Methods We conducted daily measurements of microvascular cerebral blood flow ( CBF ), oxygen saturation, and total hemoglobin concentration using diffuse correlation spectroscopy (DCS) and frequency-domain diffuse optical spectroscopy in 9 neonates. We characterize CA utilizing the correlation coefficient ( DCSx ) between CBF and mean arterial blood pressure ( MAP ) during ECMO pump flow changes. Results Average MAP and pump flow levels were weakly correlated with CBF and were not correlated with cerebral oxygen saturation. CA integrity varied between individuals and with time. Systemic measurements of MAP , pulse pressure, and left cardiac dysfunction were not predictive of impaired CA . Conclusions Our pilot results suggest that systemic measures alone cannot distinguish impaired CA from intact CA during ECMO. Furthermore, optical neuromonitoring could help determine patient-specific ECMO pump flows for optimal CA integrity, thereby reducing risk of secondary brain injury.

Objectives:We aimed to determine the incidence of periodic and rhythmic patterns (PRP), assess the interrater agreement between electroencephalographers scoring PRP using standardized terminology, and analyze associations between PRP and electrographic seizures (ES) in critically ill children. Methods:This was a prospective observational study of consecutive critically ill children undergoing continuous electroencephalographic monitoring (CEEG).PRP were identified by one electroencephalographer, and then two pediatric electroencephalographers independently scored the first 1-h epoch that contained PRP using standardized terminology. We determined the incidence of PRPs, evaluated interrater agreement between electroencephalographers scoring PRP, and evaluated associations between PRP and ES.Results:One thousand three hundred ninety-nine patients underwent CEEG. ES occurred in 345 (25%) subjects. PRP, ES + PRP, and ictal-interictal continuum (IIC) patterns occurred in 142 (10%), 81 (6%), and 93 (7%) subjects, respectively.The most common PRP were generalized periodic discharges (GPD; 43, 30%), lateralized periodic discharges (LPD; 34, 24%), generalized rhythmic delta activity (GRDA; 34, 24%), bilateral independent periodic discharges (BIPD; 14, 10%), and lateralized rhythmic delta activity (LRDA; 11, 8%

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