Electrographic seizures in pediatric ICU patients: cohort study of risk factors and mortality

Survey of Pediatric ICU EEG Monitoring-Reassessment After a Decade

PURPOSE

In 2011, the authors conducted a survey regarding continuous EEG (CEEG) utilization in critically ill children. In the interim decade, the literature has expanded, and guidelines and consensus statements have addressed CEEG utilization. Thus, the authors aimed to characterize current practice related to CEEG utilization in critically ill children.

METHODS

The authors conducted an online survey of pediatric neurologists from 50 US and 12 Canadian institutions in 2022.

RESULTS

The authors assessed responses from 48 of 62 (77%) surveyed institutions. Reported CEEG indications were consistent with consensus statement recommendations and included altered mental status after a seizure or status epilepticus, altered mental status of unknown etiology, or altered mental status with an acute primary neurological condition. Since the prior survey, there was a 3- to 4-fold increase in the number of patients undergoing CEEG per month and greater use of written pathways for ICU CEEG. However, variability in resources and workflow persisted, particularly regarding technologist availability, frequency of CEEG screening, communication approaches, and electrographic seizure management approaches.

CONCLUSIONS

Among the surveyed institutions, which included primarily large academic centers, CEEG use in pediatric intensive care units has increased with some practice standardization, but variability in resources and workflow were persistent.

Association of EEG characteristics with outcomes following pediatric ICU cardiac arrest: A secondary analysis of the ICU-RESUScitation trial

BACKGROUND AND OBJECTIVES

There are limited tools available following cardiac arrest to prognosticate neurologic outcomes. Prior retrospective and single center studies have demonstrated early EEG features are associated with neurologic outcome. This study aimed to evaluate the prognostic value of EEG for pediatric in-hospital cardiac arrest (IHCA) in a prospective, multicenter study.

METHODS

This cohort study is a secondary analysis of the ICU-Resuscitation trial, a multicenter randomized interventional trial conducted at 18 pediatric and pediatric cardiac ICUs in the United States. Patients who achieved return of circulation (ROC) and had post-ROC EEG monitoring were eligible for inclusion. Patients < 90 days old and those with pre-arrest Pediatric Cerebral Performance Category (PCPC) scores > 3 were excluded. EEG features of interest included EEG Background Category, and presence of focal abnormalities, sleep spindles, variability, reactivity, periodic and rhythmic patterns, and seizures. The primary outcome was survival to hospital discharge with favorable neurologic outcome. Associations between EEG features and outcomes were assessed with multivariable logistic regression. Prediction models with and without EEG Background Category were developed and receiver operator characteristic curves compared.

RESULTS

Of the 1129 patients with an index cardiac arrest who achieved ROC in the parent study, 261 had EEG within 24 h of ROC, of which 151 were evaluable. The cohort included 57% males with a median age of 1.1 years (IQR 0.4, 6.8). EEG features including EEG Background Category, sleep spindles, variability, and reactivity were associated with survival with favorable outcome and survival, (all p < 0.001). The addition of EEG Background Category to clinical models including age category, illness category, PRISM score, duration of CPR, first documented rhythm, highest early post-arrest arterial lactate improved the prediction accuracy achieving an AUROC of 0.84 (CI 0.77-0.92), compared to AUROC of 0.76 (CI 0.67-0.85) (p = 0.005) without EEG Background Category.

CONCLUSION

This multicenter study demonstrates the value of EEG, in the first 24 h following ROC, for predicting survival with favorable outcome after a pediatric IHCA.

Continuous Electroencephalogram Use and Hospital Outcomes in Critically Ill Children

PURPOSE

To examine the association between CEEG use and discharge status, length of hospitalization, and health care cost in a critically ill pediatric population.

METHODS

Four thousand three hundred forty-eight critically ill children were identified from a US nationwide administrative health claims database; 212 (4.9%) of whom underwent CEEG during admissions (January 1, 2015-june 30, 2020). Discharge status, length of hospitalization, and health care cost were compared between patients with and without CEEG use. Multiple logistic regression analyzed the association between CEEG use and these outcomes, controlling for age and underlying neurologic diagnosis. Prespecified subgroups analysis was performed for children with seizures/status epilepticus, with altered mental status and with cardiac arrest.

RESULTS

Compared with critically ill children without CEEG, those who underwent CEEG were likely to have shorter hospital stays than the median (OR = 0.66; 95% CI = 0.49-0.88; P = 0.004), and also total hospitalization costs were less likely to exceed the median (OR = 0.59; 95% CI = 0.45-0.79; P < 0.001). There was no difference in odds of favorable discharge status between those with and without CEEG (OR = 0.69; 95% CI = 0.41-1.08; P = 0.125). In the subgroup of children with seizures/status epilepticus, those with CEEG were less likely to have unfavorable discharge status, compared with those without CEEG (OR = 0.51; 95% CI = 0.27-0.89; P = 0.026).

CONCLUSIONS

Among critically ill children, CEEG was associated with shorter stay and lower costs of hospitalization but was not associated with change of favorable discharge status except the subgroup with seizures/status epilepticus.

Periodic Discharges in Critically Ill Children: Predictors and Outcome

OBJECTIVES

We aimed to identify clinical and EEG monitoring characteristics associated with generalized, lateralized, and bilateral-independent periodic discharges (GPDs, LPDs, and BIPDs) and to determine which patterns were associated with outcomes in critically ill children.

METHODS

We performed a prospective observational study of consecutive critically ill children undergoing continuous EEG monitoring, including standardized scoring of GPDs, LPDs, and BIPDs. We identified variables associated with GPDs, LPDs, and BIPDs and assessed whether each pattern was associated with hospital discharge outcomes including the Glasgow Outcome Scale-Extended Pediatric version (GOS-E-Peds), Pediatric Cerebral Performance Category (PCPC), and mortality.

RESULTS

PDs occurred in 7% (91/1,399) of subjects. Multivariable logistic regression indicated that patients with coma (odds ratio [OR], 3.45; 95% confidence interval [CI]: 1.55, 7.68) and abnormal EEG background category (OR, 6.85; 95% CI: 3.37, 13.94) were at increased risk for GPDs. GPDs were associated with mortality (OR, 3.34; 95% CI: 1.24, 9.02) but not unfavorable GOS-E-Peds (OR, 1.93; 95% CI: 0.88, 4.23) or PCPC (OR, 1.64; 95% CI: 0.75, 3.58). Patients with acute nonstructural encephalopathy did not experience LPDs, and LPDs were not associated with mortality or unfavorable outcomes. BIPDs were associated with mortality (OR, 3.68; 95% CI: 1.14, 11.92), unfavorable GOS-E-Peds (OR, 5.00; 95% CI: 1.39, 18.00), and unfavorable PCPC (OR, 5.96; 95% CI: 1.65, 21.46).

SIGNIFICANCE

Patients with coma or more abnormal EEG background category had an increased risk for GPDs and BIPDs, and no patients with an acute nonstructural encephalopathy experienced LPDs. GPDs were associated with mortality and BIPDs were associated with mortality and unfavorable outcomes, but LPDs were not associated with unfavorable outcomes.

EEG Monitoring in Critically Ill Children: Establishing High-Yield Subgroups

PURPOSE

Continuous EEG monitoring (CEEG) is increasingly used to identify electrographic seizures (ES) in critically ill children, but it is resource intense. We aimed to assess how patient stratification by known ES risk factors would impact CEEG utilization.

METHODS

This was a prospective observational study of critically ill children with encephalopathy who underwent CEEG. We calculated the average CEEG duration required to identify a patient with ES for the full cohort and subgroups stratified by known ES risk factors.

RESULTS

ES occurred in 345 of 1,399 patients (25%). For the full cohort, an average of 90 hours of CEEG would be required to identify 90% of patients with ES. If subgroups of patients were stratified by age, clinically evident seizures before CEEG initiation, and early EEG risk factors, then 20 to 1,046 hours of CEEG would be required to identify a patient with ES. Patients with clinically evident seizures before CEEG initiation and EEG risk factors present in the initial hour of CEEG required only 20 (<1 year) or 22 (≥1 year) hours of CEEG to identify a patient with ES. Conversely, patients with no clinically evident seizures before CEEG initiation and no EEG risk factors in the initial hour of CEEG required 405 (<1 year) or 1,046 (≥1 year) hours of CEEG to identify a patient with ES. Patients with clinically evident seizures before CEEG initiation or EEG risk factors in the initial hour of CEEG required 29 to 120 hours of CEEG to identify a patient with ES.

CONCLUSIONS

Stratifying patients by clinical and EEG risk factors could identify high- and low-yield subgroups for CEEG by considering ES incidence, the duration of CEEG required to identify ES, and subgroup size. This approach may be critical for optimizing CEEG resource allocation.

Late-Onset Findings During Extended EEG Monitoring Are Rare in Critically Ill Children

PURPOSE

Electrographic seizures (ES) are common in critically ill children undergoing continuous EEG (CEEG) monitoring, and previous studies have aimed to target limited CEEG resources to children at highest risk of ES. However, previous studies have relied on observational data in which the duration of CEEG was clinically determined. Thus, the incidence of late occurring ES is unknown. The authors aimed to assess the incidence of ES for 24 hours after discontinuation of clinically indicated CEEG.

METHODS

This was a single-center prospective study of nonconsecutive children with acute encephalopathy in the pediatric intensive care unit who underwent 24 hours of extended research EEG after the end of clinical CEEG. The authors assessed whether there were new findings that affected clinical management during the extended research EEG, including new-onset ES.

RESULTS

Sixty-three subjects underwent extended research EEG. The median duration of the extended research EEG was 24.3 hours (interquartile range 24.0-25.3). Three subjects (5%) had an EEG change during the extended research EEG that resulted in a change in clinical management, including an increase in ES frequency, differential diagnosis of an event, and new interictal epileptiform discharges. No subjects had new-onset ES during the extended research EEG.

CONCLUSIONS

No subjects experienced new-onset ES during the 24-hour extended research EEG period. This finding supports observational data that patients with late-onset ES are rare and suggests that ES prediction models derived from observational data are likely not substantially underrepresenting the incidence of late-onset ES after discontinuation of clinically indicated CEEG.

Ictal-Interictal Continuum in the Pediatric Intensive Care Unit

BACKGROUND

The ictal-interictal continuum (IIC) consists of several electroencephalogram (EEG) patterns that are common in critically ill adults. Studies focused on the IIC are limited in critically ill children and have focused primarily on associations with electrographic seizures (ESs). We report the incidence of the IIC in the pediatric intensive care unit (PICU). We then compare IIC patterns to rhythmic and periodic patterns (RPP) not meeting IIC criteria looking for associations with acute cerebral abnormalities, ES, and in-hospital mortality.

METHODS

This was a retrospective review of prospectively collected data for patients admitted to the PICU at Children's National Hospital from July 2021 to January 2023 with continuous EEG. We excluded patients with known epilepsy and cerebral injury prior to presentation. All patients were screened for RPP. The American Clinical Neurophysiology Society standardized Critical Care EEG terminology for the IIC was applied to each RPP. Associations between IIC and RPP not meeting IIC criteria, with clinical and EEG variables, were calculated using odds ratios (ORs).

RESULTS

Of 201 patients, 21% (42/201) had RPP and 12% (24/201) met IIC criteria. Among patients with an IIC pattern, the median age was 3.4 years (interquartile range (IQR) 0.6-12 years). Sixty-seven percent (16/24) of patients met a single IIC criterion, whereas the remainder met two criteria. ESs were identified in 83% (20/24) of patients and cerebral injury was identified in 96% (23/24) of patients with IIC patterns. When comparing patients with IIC patterns with those with RPP not qualifying as an IIC pattern, both patterns were associated with acute cerebral abnormalities (IIC OR 26 [95% confidence interval {CI} 3.4-197], p = 0.0016 vs. RPP OR 3.5 [95% CI 1.1-11], p = 0.03), however, only the IIC was associated with ES (OR 121 [95% CI 33-451], p < 0.0001) versus RPP (OR 1.3 [0.4-5], p = 0.7).

CONCLUSIONS

Rhythmic and periodic patterns and subsequently the IIC are commonly seen in the PICU and carry a high association with cerebral injury. Additionally, the IIC, seen in more than 10% of critically ill children, is associated with ES. The independent impact of RPP and IIC patterns on secondary brain injury and need for treatment of these patterns independent of ES requires further study.

Optimizing EEG monitoring in critically ill children at risk for electroencephalographic seizures

OBJECTIVE

Strategies are needed to optimally deploy continuous EEG monitoring (CEEG) for electroencephalographic seizure (ES) identification and management due to resource limitations. We aimed to construct an efficient multi-stage prediction model guiding CEEG utilization to identify ES in critically ill children using clinical and EEG covariates.

METHODS

The largest prospective single-center cohort of 1399 consecutive children undergoing CEEG was analyzed. A four-stage model was developed and trained to predict whether a subject required additional CEEG at the conclusion of each stage given their risk of ES. Logistic regression, elastic net, random forest, and CatBoost served as candidate methods for each stage and were evaluated using cross validation. An optimal multi-stage model consisting of the top-performing stage-specific models was constructed.

RESULTS

When evaluated on a test set, the optimal multi-stage model achieved a cumulative specificity of 0.197 and cumulative F1 score of 0.326 while maintaining a high minimum cumulative sensitivity of 0.938. Overall, 11 % of test subjects with ES were removed from the model due to a predicted low risk of ES (falsely negative subjects). CEEG utilization would be reduced by 32 % and 47 % compared to performing 24 and 48 h of CEEG in all test subjects, respectively. We developed a web application called EEGLE (EEG Length Estimator) that enables straightforward implementation of the model.

CONCLUSIONS

Application of the optimal multi-stage ES prediction model could either reduce CEEG utilization for patients at lower risk of ES or promote CEEG resource reallocation to patients at higher risk for ES.

Neonatal seizures during extra corporeal membrane oxygenation support

To evaluate EEG monitoring during neonatal ECMO and to identify any correlations between seizure detection to abnormal neuroimaging. Eight-year, service evaluation of neonates who received at least one continuous EEG (cEEG) whilst on ECMO at Great Ormond Street Hospital. Pearson's chi-square test and multivariate logistic regression analysis were used to assess clinical and EEG variables association with seizures and neuroimaging findings. Fifty-seven neonates were studied; 57 cEEG recordings were reviewed. The incidence of seizures was 33% (19/57); of these 74% (14/19) were electrographic-only. The incidence of status epilepticus was 42%, (8/19 with 6 neonates having electrographic-only status and 2 electro-clinical status. Seizures were detected within an hour of recording in 84%, (16/19). The overall mortality rate was 39% (22/57). Seizure detection was strongly associated with female gender (OR 4.8, 95% CI: 1.1-20.4, p = 0.03), abnormal EEG background activity (OR 2.8, 95% CI: 1.1-7.4, p = 0.03) and abnormal EEG focal features (OR 23.6, 95% CI: 5.4-103.9, p = 0.001). There was a strong association between the presence of seizures and abnormal neuroimaging findings (OR 10.9, 95% CI: 2.8-41.9, p = 0.001). Neonates were highly likely to have abnormal neuroimaging findings in the presence of severely abnormal background EEG (OR 9.5, 95% CI 1.7-52.02, p = 0.01) and focal EEG abnormalities (OR 6.35, 95% CI 1.97-20.5, p = 0.002)Conclusion: The study highlights the importance of cEEG in neonates undergoing ECMO. An association between seizure detection and abnormal neuroimaging findings was described. What is Known: • Patients on ECMO are at a higher risk of seiures. • Continuous EEG monitoring is recommended by the ACNS for high risk and ECMO patients. What is New: • In this cohort, neonates with sezirues were 11 times more likely of having abnromal neuroimaging findings. • Neonates with burst suppressed or suppressed EEG background were 9.5 times more likely to have abnormal neuroimaging findings. What does this study add? • This study reports a 33% incidence of neonatal seizures during ECMO. • Neonates with seizures were 11 times more likely to have an abnormal brain scan. • The study captures the real-time approach of EEG monitoring. • Recommended cEEG monitoring should last at least 24 h for ECMO patients. • This is the first study to assess this in neonates only.

Association of EEG Background With Diffusion-Weighted Magnetic Resonance Neuroimaging and Short-Term Outcomes After Pediatric Cardiac Arrest

BACKGROUND AND OBJECTIVES

EEG and MRI features are independently associated with pediatric cardiac arrest (CA) outcomes, but it is unclear whether their combination improves outcome prediction. We aimed to assess the association of early EEG background category with MRI ischemia after pediatric CA and determine whether addition of MRI ischemia to EEG background features and clinical variables improves short-term outcome prediction.

METHODS

This was a single-center retrospective cohort study of pediatric CA with EEG initiated ≤24 hours and MRI obtained ≤7 days of return of spontaneous circulation. Initial EEG background was categorized as normal, slow/disorganized, discontinuous/burst-suppression, or attenuated-featureless. MRI ischemia was defined as percentage of brain tissue with apparent diffusion coefficient (ADC) <650 × 10-6 mm2/s and categorized as high (≥10%) or low (<10%). Outcomes were mortality and unfavorable neurologic outcome (Pediatric Cerebral Performance Category increase ≥1 from baseline resulting in ICU discharge score ≥3). The Kruskal-Wallis test evaluated the association of EEG with MRI. Area under the receiver operating characteristic (AUROC) curve evaluated predictive accuracy. Logistic regression and likelihood ratio tests assessed multivariable outcome prediction.

RESULTS

We evaluated 90 individuals. EEG background was normal in 16 (18%), slow/disorganized in 42 (47%), discontinuous/burst-suppressed in 12 (13%), and attenuated-featureless in 20 (22%) individuals. The median percentage of MRI ischemia was 5% (interquartile range 1-18); 32 (36%) individuals had high MRI ischemia burden. Twenty-eight (31%) individuals died, and 58 (64%) had unfavorable neurologic outcome. Worse EEG background category was associated with more MRI ischemia (p < 0.001). The combination of EEG background and MRI ischemia burden had higher predictive accuracy than EEG alone (AUROC: mortality: 0.92 vs 0.87, p = 0.03) or MRI alone (AUROC: mortality: 0.92 vs 0.84, p = 0.02; unfavorable: 0.83 vs 0.73, p < 0.01). Addition of percentage of MRI ischemia to clinical variables and EEG background category improved prediction for mortality (χ2 = 19.1, p < 0.001) and unfavorable neurologic outcome (χ2 = 4.8, p = 0.03) and achieved high predictive accuracy (AUROC: mortality: 0.97; unfavorable: 0.92).

DISCUSSION

Early EEG background category was associated with MRI ischemia after pediatric CA. Combining EEG and MRI data yielded higher outcome predictive accuracy than either modality alone. The addition of MRI ischemia to clinical variables and EEG background improved short-term outcome prediction.

Reducing Time to Electroencephalography in Pediatric Convulsive Status Epilepticus: A Quality Improvement Initiative

BACKGROUND

Pediatric convulsive status epilepticus (CSE) is a neurological emergency utilizing electroencephalography (EEG) to guide therapeutic interventions. Guidelines recommend EEG initiation within one hour of seizure onset, but logistic and structural barriers often lead to significant delays. We aimed to reduce the time to EEG in pediatric CSE.

METHODS

From 2017 to 2022, we implemented process improvements, including EEG order sets with priority-based timing guidance, technologist workflow changes, a satisfaction survey, and feedback from key stakeholder groups, over five plan-do-study-act (PDSA) cycles. Seizure start time, time of EEG order, and time to EEG initiation were extracted. Time to interpretable EEG was determined from manual review of the EEG tracing.

RESULTS

Time from EEG order to interpretable EEG decreased by nearly 50%, from a median of 90 minutes to 48 minutes. There were clinically and statistically significant improvements in time from EEG order to EEG initiation, time from EEG order to interpretable EEG, and EEG start to interpretable EEG. Ongoing provider education and guidance enabled improvements, whereas a new electronic health care record negatively impacted electronic ordering. EEG technologists reported that they understood the importance of emergent EEG for clinical care and did not find that the new workflow caused excessive disruption.

CONCLUSIONS

Timely access to EEG for pediatric patients with CSE can be improved through clinical processes that use existing devices and that maintain the benefits of full-montage EEG recordings. Similar process improvement efforts may be generalizable to other institutions to increase adherence to guidelines and provide improved care.

Lateralized Rhythmic Delta Activity and Lateralized Periodic Discharges in Critically Ill Pediatric Patients

PURPOSE

To evaluate the clinical and electrographic characteristics of critically ill pediatric patients with lateralized rhythmic delta activity (LRDA) and compare them with patients with lateralized periodic discharges (LPDs).

METHODS

This was a retrospective study examining consecutive critically ill pediatric patients (1 month-18 years) with LRDA or LPDs monitored on continuous electroencephalography. Clinical, radiologic, and electrographic characteristics; disease severity; and acute sequelae were compared between the two groups.

RESULTS

Of 668 pediatric patients monitored on continuous electroencephalography during the study period, 12 (1.79%) patients had LRDA and 15 (2.24%) had LPDs. The underlying etiologies were heterogeneous with no difference in the acuity of brain MRI changes between both groups. Lateralized rhythmic delta activity and LPDs were concordant with the side of MRI abnormality in most patients [85.7% (LRDA) and 83.3% (LPD)]. There was no difference in the measures of disease severity between both groups. Seizures were frequent in both groups (42% in the LRDA group and 73% in the LPD group). Patients in the LPD group had a trend toward requiring a greater number of antiseizure medications for seizure control (median of 4 vs. 2 in the LRDA group, p = 0.09), particularly those patients with LPDs qualifying as ictal-interictal continuum compared with those without ictal-interictal continuum (p = 0.02).

CONCLUSIONS

Lateralized rhythmic delta activity and LPDs are uncommon EEG findings in the pediatric population. Seizures occur commonly in patients with these patterns. Seizures in patients with LPDs, especially those qualifying as ictal-interictal continuum, showed a trend toward being more refractory. Larger studies are needed in the future to further evaluate these findings.

Electrographic Seizure Characteristics and Electrographic Status Epilepticus Prediction

PURPOSE

We aimed to characterize electrographic seizures (ES) and electrographic status epilepticus (ESE) and determine whether a model predicting ESE exclusively could effectively guide continuous EEG monitoring (CEEG) utilization in critically ill children.

METHODS

This was a prospective observational study of consecutive critically ill children with encephalopathy who underwent CEEG. We used descriptive statistics to characterize ES and ESE, and we developed a model for ESE prediction.

RESULTS

ES occurred in 25% of 1,399 subjects. Among subjects with ES, 23% had ESE, including 37% with continuous seizures lasting >30 minutes and 63% with recurrent seizures totaling 30 minutes within a 1-hour epoch. The median onset of ES and ESE occurred 1.8 and 0.18 hours after CEEG initiation, respectively. The optimal model for ESE prediction yielded an area under the receiver operating characteristic curves of 0.81. A cutoff selected to emphasize sensitivity (91%) yielded specificity of 56%. Given the 6% ESE incidence, positive predictive value was 11% and negative predictive value was 99%. If the model were applied to our cohort, then 53% of patients would not undergo CEEG and 8% of patients experiencing ESE would not be identified.

CONCLUSIONS

ESE was common, but most patients with ESE had recurrent brief seizures rather than long individual seizures. A model predicting ESE might only slightly improve CEEG utilization over models aiming to identify patients at risk for ES but would fail to identify some patients with ESE. Models identifying ES might be more advantageous for preventing ES from evolving into ESE.

Interpretable machine learning models for predicting 90-day death in patients in the intensive care unit with epilepsy

PURPOSE

This study aims to develop a machine learning-based model for predicting mortality risk in patients with epilepsy admitted to the intensive care unit (ICU), providing clinicians with an accurate prognostic tool to guide individualized treatment.

METHODS

We collected clinical data from clinical databases (MIMIC IV and eICU-CRD) of epilepsy patients 24 h after ICU admission. The clinical characteristics of ICU patients with epilepsy were carefully feature selected and processed. MIMIC IV as the training set and eICU-CRD database as the test set. Six models were developed and validated, and the best LightGBM model was selected by performance comparison and analysed for interpretability.

RESULTS

The final cohort comprised 429 patients for training and 1217 for testing. The training set exhibited a 90-day mortality rate of 9.32 %, and the test set had an in-hospital 90-day mortality rate of 4.10 %. Utilizing the LightGBM model, we achieved an AUC of 0.956 in the training set. External validation demonstrated promising results with accuracy of 0.898, precision of 0.975, AUC of 0.781, F1 score of 0.945, highlighting the model's potential for guiding clinical decision-making. Significant factors influencing model performance included the severity of illness, as measured by the OASIS score, and clinical parameters like heart rate and body temperature.

CONCLUSION

This study introduces a machine learning-based approach to predict mortality risk in ICU epilepsy patients, offering a valuable tool for clinicians to identify high-risk individuals and devise personalized treatment strategies, thus improving patient prognosis and treatment outcomes.

"T" Times: Revisiting the Timing of Neuronal Injury in Status Epilepticus

Effects of Epileptiform Activity on Discharge Outcome in Critically Ill Patients in the USA: A Retrospective Cross-Sectional Study Parikh H, Hoffman K, Sun H, Zafar SF, Ge W, Jing J, Liu L, Sun J, Struck A, Volfovsky A, Rudin C, Westover MB. Lancet Digit Health. 2023;5:e495-e502. doi:10.1016/S2589-7500(23)00088-2 Background: Epileptiform activity is associated with worse patient outcomes, including increased risk of disability and death. However, the effect of epileptiform activity on neurological outcome is confounded by the feedback between treatment with antiseizure medications and epileptiform activity burden. We aimed to quantify the heterogeneous effects of epileptiform activity with an interpretability-centred approach. Methods: We did a retrospective, cross-sectional study of patients in the intensive care unit who were admitted to Massachusetts General Hospital (Boston, MA, USA). Participants were aged 18 years or older and had electrographic epileptiform activity identified by a clinical neurophysiologist or epileptologist. The outcome was the dichotomised modified Rankin Scale (mRS) at discharge and the exposure was epileptiform activity burden defined as mean or maximum proportion of time spent with epileptiform activity in 6 h windows in the first 24 h of electroencephalography. We estimated the change in discharge mRS if everyone in the dataset had experienced a specific epileptiform activity burden and were untreated. We combined pharmacological modelling with an interpretable matching method to account for confounding and epileptiform activity-antiseizure medication feedback. The quality of the matched groups was validated by the neurologists. Findings: Between Dec 1, 2011, and Oct 14, 2017, 1514 patients were admitted to Massachusetts General Hospital intensive care unit, 995 (66%) of whom were included in the analysis. Compared with patients with a maximum epileptiform activity of 0 to less than 25%, patients with a maximum epileptiform activity burden of 75% or more when untreated had a mean 22.27% (SD 0.92) increased chance of a poor outcome (severe disability or death). Moderate but long-lasting epileptiform activity (mean epileptiform activity burden 2% to <10%) increased the risk of a poor outcome by mean 13.52% (SD 1.93). The effect sizes were heterogeneous depending on preadmission profile—eg, patients with hypoxic-ischaemic encephalopathy or acquired brain injury were more adversely affected compared with patients without these conditions. Interpretation: Our results suggest that interventions should put a higher priority on patients with an average epileptiform activity burden 10% or greater, and treatment should be more conservative when maximum epileptiform activity burden is low. Treatment should also be tailored to individual preadmission profiles because the potential for epileptiform activity to cause harm depends on age, medical history, and reason for admission.

Review of Noninvasive Neuromonitoring Modalities in Children II: EEG, qEEG

Critically ill children with acute neurologic dysfunction are at risk for a variety of complications that can be detected by noninvasive bedside neuromonitoring. Continuous electroencephalography (cEEG) is the most widely available and utilized form of neuromonitoring in the pediatric intensive care unit. In this article, we review the role of cEEG and the emerging role of quantitative EEG (qEEG) in this patient population. cEEG has long been established as the gold standard for detecting seizures in critically ill children and assessing treatment response, and its role in background assessment and neuroprognostication after brain injury is also discussed. We explore the emerging utility of both cEEG and qEEG as biomarkers of degree of cerebral dysfunction after specific injuries and their ability to detect both neurologic deterioration and improvement.

Validation of a Model for Targeted EEG Monitoring Duration in Critically Ill Children

PURPOSE

Continuous EEG monitoring (CEEG) to identify electrographic seizures (ES) in critically ill children is resource intense. Targeted strategies could enhance implementation feasibility. We aimed to validate previously published findings regarding the optimal CEEG duration to identify ES in critically ill children.

METHODS

This was a prospective observational study of 1,399 consecutive critically ill children with encephalopathy. We validated the findings of a multistate survival model generated in a published cohort ( N = 719) in a new validation cohort ( N = 680). The model aimed to determine the CEEG duration at which there was <15%, <10%, <5%, or <2% risk of experiencing ES if CEEG were continued longer. The model included baseline clinical risk factors and emergent EEG risk factors.

RESULTS

A model aiming to determine the CEEG duration at which a patient had <10% risk of ES if CEEG were continued longer showed similar performance in the generation and validation cohorts. Patients without emergent EEG risk factors would undergo 7 hours of CEEG in both cohorts, whereas patients with emergent EEG risk factors would undergo 44 and 36 hours of CEEG in the generation and validation cohorts, respectively. The <10% risk of ES model would yield a 28% or 64% reduction in CEEG hours compared with guidelines recommending CEEG for 24 or 48 hours, respectively.

CONCLUSIONS

This model enables implementation of a data-driven strategy that targets CEEG duration based on readily available clinical and EEG variables. This approach could identify most critically ill children experiencing ES while optimizing CEEG use.

Continuous Electroencephalography (EEG) Protocol Improves Seizure Detection in Children on Extracorporeal Membrane Oxygenation

BACKGROUND / OBJECTIVE

Seizures are a complication for pediatric patients requiring extracorporeal membrane oxygenation (ECMO). There are no standardized guidelines regarding continuous electroencephalography (EEG) monitoring to detect seizures in these patients, and the impact of protocolized monitoring has not been evaluated. Here we examined the effects of continuous EEG protocol implementation in our pediatric ECMO population.

METHODS

Retrospective chart reviews were conducted on 57 patients who underwent extracorporeal membrane oxygenation and concurrent continuous EEG out of 165 patients supported on extracorporeal membrane oxygenation. Timing of continuous EEG initiation and seizures detected by continuous EEG was determined for 5 years prior to and 15 months after protocol implementation.

RESULTS

Protocol implementation was associated with increased ECMO-supported patients who were concurrently monitored by continuous EEG. Time from ECMO cannulation to continuous EEG initiation was shorter (median 7 hours after versus 16.2 hours before; P < .001). Patients who had ongoing seizures at the start of continuous EEG recording decreased from 64% preprotocol to 0% postprotocol (P < .001), and there was an associated earlier time to break in status epilepticus postprotocol. Seizures were detected past 48 hours after cannulation in 50% of patients in the postprotocol group.

CONCLUSIONS

Protocol implementation resulted in earlier continuous EEG initiation and more EEGs initiated before seizure onset with evidence of altered seizure dynamics. Although current recommendations suggest that continuous EEG duration of 24-48 hours results in seizure detection for >90% of critically ill adults, longer monitoring may be needed to reliably detect seizures in children supported with ECMO, particularly if monitoring is initiated earlier in the post-cannulation period.

The association between epilepsy and COVID-19: analysis based on Mendelian randomization and FUMA

Objective

A multitude of observational studies have underscored a substantial comorbidity between COVID-19 and epilepsy. This study was aimed at establishing a conclusive causal link between these two conditions.

Methods

We employed Mendelian randomization (MR) to evaluate the causal link between COVID-19 and epilepsy, as well as its focal and generalized subtypes. The GWAS for epilepsy and its subtypes database were abstracted from both FinnGen consortium and ILAE. Additionally, we leveraged functional mapping and annotation (FUMA) to integrate information from genome-wide association studies (GWAS) results.

Results

The MR analyses revealed that genetic liability to COVID-19 infection conferred a causal effect on epilepsy [FinnGen: OR: 1.5306; 95% confidence interval (CI): 1.1676-2.0062, PFDR (false discovery rate) = 0.0076; ILAE: OR: 1.3440; 95% CI: 1.0235-1.7649, PFDR = 0.0429], and generalized epilepsy (FinnGen: OR: 2.1155; 95% CI: 1.1734-3.8139, PFDR = 0.0327; ILAE: OR: 1.1245; 95% CI: 1.0444-1.2108, PFDR = 0.0114). Genetic liability to COVID-19 hospitalization conferred a causal effect on epilepsy (FinnGen: OR: 1.0934; 95% CI: 1.0097-1.1841, PFDR = 0.0422; ILAE: OR: 1.7381; 95% CI: 1.0467-2.8862, PFDR = 0.0451), focal epilepsy (ILAE: OR: 1.7549; 95% CI: 1.1063-2.7838, PFDR = 0.0338), and generalized epilepsy (ILAE: OR: 1.1827; 95% CI: 1.0215-1.3693, PFDR = 0.0406). Genetic liability to COVID-19 severity conferred a causal effect on epilepsy (FinnGen consortium: OR: 1.2454; 95% CI: 1.0850-1.4295, PFDR = 0.0162; ILAE: OR: 1.2724; 95% CI: 1.0347-1.5647, PFDR = 0.0403), focal epilepsy (FinnGen: OR: 1.6818; 95% CI: 1.1478-2.4642, PFDR = 0.0231; ILAE: OR: 1.6598; 95% CI: 1.2572-2.1914, PFDR = 0.0054), and generalized epilepsy (FinnGen: OR: 1.1486; 95% CI: 1.0274-1.2842, PFDR = 0.0335; ILAE: OR: 1.0439; 95% CI: 1.0159-1.0728, PFDR = 0.0086). In contrast, no causal linkage of epilepsy on COVID-19 was observed. Further, FUMA analysis identified six overlapping genes, including SMEK2, PNPT1, EFEMP1, CCDC85A, VRK2, and BCL11A, shared between COVID-19 and epilepsy. Tissue-specific expression analyses revealed that the disease-gene associations of COVID-19 were significantly enriched in lung, ovary, and spleen tissue compartments, while being significantly enriched in brain tissue for epilepsy.

Conclusion

Our study demonstrates that COVID-19 can be a contributing factor to epilepsy, but we found no evidence that epilepsy contributes to COVID-19.

Evaluation of Nonconvulsive Status Epilepticus and Nonconvulsive Seizures in a Pediatric Intensive Care Unit

We aimed to identify nonconvulsive seizures (NCS) and nonconvulsive status epilepticus (NCSE) in a pediatric intensive care unit (PICU). A prospective cohort study on 35 patients who underwent continuous electroencephalographic monitoring in the PICU was done. The patients were evaluated to collect data of their demographics, clinical diagnoses, clinical seizures by electroencephalography, and neuroimaging findings. One case with NCSE and 4 cases with NCS were diagnosed among the 35 patients. The etiology of the patient with NCSE showed antiepileptic drug (AED) withdrawal. The etiology of the patients with NCS included electrical injury, head trauma, subarachnoid hemorrhage, and pneumonia. The findings suggest that younger age, epilepsy, acute structural brain abnormalities, abrupt cessation of AED, and clinically overt seizures before NCSE/NCS are associated with significant risk for NCS/NCSE. In addition, the electrical injury may also be considered as a risk factor for electrographic seizure though such a case has not yet been reported.

Management of Status Epilepticus by Different Pediatric Departments: Neurology, Intensive Care, and Emergency Medicine

INTRODUCTION

The aim of this study was to explore the differences in status epilepticus (SE) management among pediatric neurology, emergency medicine, and intensive care specialists in Turkey.

METHODS

A 22-item questionnaire regarding first-, second-, and third-line management strategies of SE including demographic characteristics and common etiologies according to the specialty of participants was mailed to 370 specialists working in Turkey.

RESULTS

A total of 334 participants (response rate 90%) comprising 136 pediatric neurologists, 102 pediatric emergency medicine specialists, and 96 pediatric intensive care specialists completed the survey. While intensive care specialists frequently managed SE due to metabolic and autoimmune reasons, the most common etiologies encountered by emergency medicine specialists were epilepsy and infections. More than half of the intensive care specialists (64.6%) reported using non-BZD antiseizure medications in the 5th minute of the seizure. Most of the neurologists (76.4%) preferred to administer intravenous (IV) levetiracetam infusion as a second-line agent. About half of intensive care specialists and neurologists tried immunomodulatory therapies in super-refractory SE. Intensive care and emergency medicine specialists were less likely to favor ketogenic diet and pyridoxine therapy for the treatment of super-refractory SE. The rate of requesting EEG monitoring to recognize nonconvulsive SE (NCSE) was found to be very low except for neurologists.

CONCLUSION

There was no consensus among neurologists, intensive care specialists, and emergency medicine specialists in the management of SE in Turkey. Familiarity with particular antiseizure medications and the etiologies they manage seem to be the most important factors influencing the attitudes.

Subtypes and Mechanistic Advances of Extracorporeal Membrane Oxygenation-Related Acute Brain Injury

Extracorporeal membrane oxygenation (ECMO) is a frequently used mechanical cardiopulmonary support for rescuing critically ill patients for whom conventional medical therapies have failed. However, ECMO is associated with several complications, such as acute kidney injury, hemorrhage, thromboembolism, and acute brain injury (ABI). Among these, ABI, particularly intracranial hemorrhage (ICH) and infarction, is recognized as the primary cause of mortality during ECMO support. Furthermore, survivors often suffer significant long-term morbidities, including neurocognitive impairments, motor disturbances, and behavioral problems. This review provides a comprehensive overview of the different subtypes of ECMO-related ABI and the updated advance mechanisms, which could be helpful for the early diagnosis and potential neuromonitoring of ECMO-related ABI.

Pediatric ECLS Neurologic Management and Outcomes

Neurologic complications associated with extracorporeal life support (ECLS), including seizures, ischemia/infarction, and intracranial hemorrhage significantly increase morbidity and mortality in pediatric and neonatal patients. Prompt recognition of adverse neurologic events may provide a window to intervene with neuroprotective measures. Many neuromonitoring modalities are available with varying benefits and limitations. Several pre-ECLS and ECLS-related factors have been associated with an increased risk for neurologic complications. These may be patient- or circuit-related and include modifiable and non-modifiable factors. ECLS survivors are at risk for long-term neurological sequelae affecting neurodevelopmental outcomes. Possible long-term outcomes range from normal development to severe impairment. Patients should undergo a neurological evaluation prior to discharge, and neurodevelopmental assessments should be included in each patient's structured, multidisciplinary follow-up. Safe pediatric and neonatal ECLS management requires a thorough understanding of neurological complications, neuromonitoring techniques and limitations, considerations to minimize risk, and an awareness of possible long-term ramifications. With a focus on ECLS for respiratory failure, this manuscript provides a review of these topics and summarizes best practice guidelines from international organizations and expert consensus.

Systematic Evaluation of Research Priorities in Critical Care Electroencephalography

PURPOSE

The Critical Care EEG Monitoring Research Consortium (CCEMRC) is an international research group focusing on critical care EEG and epilepsy. As CCEMRC grew to include 50+ institutions over the past decade, members met to establish research priorities.

METHODS

The authors used an analytical hierarchy process-based research prioritization method, adapted from an approach previously applied to a Department of Defense health-related research program. Forty-six CCEMRC members identified and scored a set of eight clinical problems (CPs) and 15 research topic areas (RTAs) at an annual CCEMRC meeting. Members scored CPs on three criteria using a five-point ordinal scale: Incidence, Impact, and Gap Size; and RTAs on four additional criteria: Niche, Feasibility, Scientific Importance, and Medical Importance, each of which was assigned a weight. The first three RTA criteria were scored using a five-point scale, and CPs were mapped to RTAs using a four-point scale. The Medical Importance score was a weighted average of its mapping scores and the CP score. Finally, a Priority score was calculated for each RTA as a product of the four RTA criteria scores.

RESULTS

The CPs with the highest scores were "Altered mental status" and "Long-term neurologic disability after hospital discharge." The RTAs with the highest priority scores were "Development of risk prediction tools," "Multicenter observational studies," and "Outcome prediction."

CONCLUSIONS

Research prioritization helped CCEMRC evaluate its current research trajectory, identify high-priority near-term research pursuits, and create a roadmap for future research plans aligned with its mission. This approach may be helpful to other academic consortia and research programs.

Continuous electroencephalography in the intensive care unit: A critical review and position statement from an Australian and New Zealand perspective

Objectives

This article aims to critically review the literature on continuous electroencephalography (cEEG) monitoring in the intensive care unit (ICU) from an Australian and New Zealand perspective and provide recommendations for clinicians.

Design and review methods

A taskforce of adult and paediatric neurologists, selected by the Epilepsy Society of Australia, reviewed the literature on cEEG for seizure detection in critically ill neonates, children, and adults in the ICU. The literature on routine EEG and cEEG for other indications was not reviewed. Following an evaluation of the evidence and discussion of controversial issues, consensus was reached, and a document that highlighted important clinical, practical, and economic considerations regarding cEEG in Australia and New Zealand was drafted.

Results

This review represents a summary of the literature and consensus opinion regarding the use of cEEG in the ICU for detection of seizures, highlighting gaps in evidence, practical problems with implementation, funding shortfalls, and areas for future research.

Conclusion

While cEEG detects electrographic seizures in a significant proportion of at-risk neonates, children, and adults in the ICU, conferring poorer neurological outcomes and guiding treatment in many settings, the health economic benefits of treating such seizures remain to be proven. Presently, cEEG in Australian and New Zealand ICUs is a largely unfunded clinical resource that is subsequently reserved for the highest-impact patient groups. Wider adoption of cEEG requires further research into impact on functional and health economic outcomes, education and training of the neurology and ICU teams involved, and securement of the necessary resources and funding to support the service.

Changes in the treatment of pediatric acute encephalopathy in Japan between 2015 and 2021: A national questionnaire-based survey

BACKGROUND

Although acute encephalopathy (AE) is the most serious disorder associated with a viral infection in childhood and often causes death or neurological sequelae, standard treatments have not been established. In 2016, the Japanese Society of Child Neurology published the "Guidelines for the Diagnosis and Treatment of Acute Encephalopathy in Childhood 2016" (AE GL 2016). We conducted a questionnaire survey to evaluate the status of the treatment of pediatric AE in 2021 and the changes in treatment before and after the publication of the AE GL 2016.

METHODS

In October 2021, questionnaires were mailed via the web to members of two mailing lists who were involved in the practice of pediatric neurological disorders.

RESULTS

Most Japanese physicians (98 %) engaged in the treatment of pediatric AE used the AE GL 2016 as a clinical reference. From 2015 to 2021, the number of institutions that implemented targeted temperature management (TTM), vitamin administration, and continuous electroencephalographic monitoring increased significantly. Regarding the targeted temperature for TTM, the proportion of patients who were treated with normothermia (36.0-37.0 °C) increased from 2015 (55 %) to 2021 (79 %). The use of corticosteroids in patients with AE caused by a cytokine storm, which is recommended in the AE GL 2016, had already been implemented in most institutions by 2015.

CONCLUSION

The AE GL 2016 could be used to disseminate the knowledge accumulated to date. Evidence of the efficacy and proper indication criteria for the treatment of AE is insufficient and must be further accumulated.

Clinical Features and Management of Status Epilepticus in the Pediatric Intensive Care Unit

OBJECTIVES

Status epilepticus (SE) is associated with significant morbidity and mortality in children. SE in the pediatric intensive care unit (PICU) are not well characterized. The aim of this study is to retrospectively investigate the clinical features and treatment of seizures in children admitted to the PICU of our hospital.

METHODS

We retrospectively examined the clinical characteristics of patients aged between 1 month and 18 years who were admitted to our hospital with SE or who were diagnosed with SE after hospitalization and were followed up with continuous electroencephalographic monitoring between January 2015 and December 2019.

RESULTS

A total of 88 patients with SE, 50 (56.8%) boys and 38 (43.2%) girls, were included. The median age was 24 months (interquartile range, 12-80 months). When we evaluate the continuous electroencephalographic monitoring data, 27 (30.7%) were lateralized, 20 (22.7%) were multifocal, 30 (34.1%) were generalized, and 11 (12.5%) were bilateral independent epileptic activity. Seventy nine patients (89.8%) were evaluated as convulsive status epilepticus (CSE) and 9 (10.2%) as nonconvulsive status epilepticus (NCSE). Pediatric Risk of Mortality (PRISM III) score and mortality of patients with NCSE were higher ( P = 0.004 and P = 0.046, respectively). Thirteen eight patients (43.1%) were diagnosed as SE, 38 patients (43.1%) as refractory SE, and 12 patients (13.6%) as super-refractory SE. The overall mortality rate was 10.2%.

CONCLUSIONS

Status epilepticus is a neurological emergency that causes mortality and morbidity. Electroencephalographic monitoring is important for the recognition of seizures and rapid intervention. No superiority of second-line treatments or combined treatments was demonstrated in patients with SE.

Neuromonitoring in Children with Cerebrovascular Disorders

BACKGROUND

Cerebrovascular disorders are an important cause of morbidity and mortality in children. The acute care of a child with an ischemic or hemorrhagic stroke or cerebral sinus venous thrombosis focuses on stabilizing the patient, determining the cause of the insult, and preventing secondary injury. Here, we review the use of both invasive and noninvasive neuromonitoring modalities in the care of pediatric patients with arterial ischemic stroke, nontraumatic intracranial hemorrhage, and cerebral sinus venous thrombosis.

METHODS

Narrative review of the literature on neuromonitoring in children with cerebrovascular disorders.

RESULTS

Neuroimaging, near-infrared spectroscopy, transcranial Doppler ultrasonography, continuous and quantitative electroencephalography, invasive intracranial pressure monitoring, and multimodal neuromonitoring may augment the acute care of children with cerebrovascular disorders. Neuromonitoring can play an essential role in the early identification of evolving injury in the aftermath of arterial ischemic stroke, intracranial hemorrhage, or sinus venous thrombosis, including recurrent infarction or infarct expansion, new or recurrent hemorrhage, vasospasm and delayed cerebral ischemia, status epilepticus, and intracranial hypertension, among others, and this, is turn, can facilitate real-time adjustments to treatment plans.

CONCLUSIONS

Our understanding of pediatric cerebrovascular disorders has increased dramatically over the past several years, in part due to advances in the neuromonitoring modalities that allow us to better understand these conditions. We are now poised, as a field, to take advantage of advances in neuromonitoring capabilities to determine how best to manage and treat acute cerebrovascular disorders in children.

Brain network properties of clinical versus subclinical seizures among critically ill children

OBJECTIVE

Electrographic seizures are common among critically ill children, and have been associated with worse outcomes. Despite their often-widespread cortical representation, most of these seizures remain subclinical, a phenomenon which remains poorly understood. We compared the brain network properties of clinical versus subclinical seizures to gain insight into their relative potential deleterious effects.

METHODS

Functional connectivity (phase lag index) and graph measures (global efficiency and clustering coefficients) were computed for 2178 electrographic seizures recorded during 48-hours of 19-channel continuous EEG monitoring obtained in 20 comatose children. Frequency-specific group differences in clinical versus subclinical seizures were analyzed using a non-parametric ANCOVA, adjusting for age, sex, medication exposure, treatment intensity and seizures per subject.

RESULTS

Clinical seizures demonstrated greater functional connectivity than subclinical seizures at alpha frequencies, but less connectivity than subclinical seizures at delta frequencies. Clinical seizures also demonstrated significantly higher median global efficiency than subclinical seizures (p < 0.01), and significantly higher median clustering coefficients across all electrodes at alpha frequencies.

CONCLUSIONS

Clinical expression of seizures correlates with greater alpha synchronization of distributed brain networks.

SIGNIFICANCE

The stronger global and local alpha-mediated functional connectivity observed during clinical seizures may indicate greater pathological network recruitment. These observations motivate further studies to investigate whether the clinical expression of seizures may influence their potential to cause secondary brain injury.

Sporadic and Periodic Interictal Discharges in Critically Ill Children: Seizure Associations and Time to Seizure Identification

PURPOSE

We evaluated interictal discharges (IEDs) as a biomarker for the time to development of electrographic seizures (ES).

METHODS

Prospective observational study of 254 critically ill children who underwent continuous electroencephalography (cEEG) monitoring. We excluded neonates and patients with known epilepsy or the sole cEEG indication to characterize events. Interictal discharges included sporadic epileptiform discharges and periodic and rhythmic patterns. Sporadic epileptiform discharges were categorized as low frequency (rare [<1/hour] and occasional [≥1/hour but <1/minute]) and high frequency (frequent, [≥1/minute] and abundant [≥1/10 seconds]). Time variables included time from cEEG start to first IED and time between first IED and ES.

RESULTS

Interictal discharges were present in 33% (83/254) of patients. We identified ES in 20% (50/254), and 86% (43/50) had IEDs. High-frequency sporadic epileptiform discharges (odds ratio [OR], 35; 95% confidence interval [CI], 14.5-88; P < 0.0001) and lateralized periodic discharges (OR, 27; 95% CI, 7.3-100; P < 0.0001) were associated with ES. Mildly abnormal EEG background without IEDs or background asymmetry was associated with the absence of seizures (OR, 0.1; 95% CI, 0.04-0.3; P < 0.0001). Time from cEEG start to first IED was 36 minutes (interquartile range, 3-131 minutes), and time between first IED and ES was 9.6 minutes (interquartile range, 0.6-165 minutes).

CONCLUSIONS

Interictal discharges are associated with ES and are identified in the first 3 hours of cEEG. High-frequency sporadic epileptiform discharges and periodic patterns have the highest risk of ES. Our findings define a window of high seizure risk after the identification of IEDs in which to allocate resources to improve seizure identification and subsequent treatment.

Reducing seizure to needle times in nonconvulsive status epilepticus with multifaceted quality improvement initiatives

OBJECTIVES

Delayed management of nonconvulsive status epilepticus (NCSE) can lead to an increased morbidity and mortality. We previously established that inefficient treatment of NCSE at our institution stemmed from delayed initiation of emergent anti-seizure medications (ASM). In the present study, we assessed the trajectories of these time parameters and determined patient outcomes following the specific quality improvement (QI) interventions.

METHODS

The QI interventions, including the revision of the educational content for trainees and pharmacy workflow optimization were implemented between January 2019 and September 2021 by a dedicated multidisciplinary task force. The times needed to initiate and administer the ASMs for patients with NCSE as well as patient mortality were assessed in comatose and noncomatose patients and compared with the corresponding values prior to the interventions.

RESULTS

There were 79 occurrences of NCSE in 74 patients. The median time from seizure detection on EEG to the order of the first and second ASM for NCSE was reduced by 4 (p = 0.83) and 8 min (p = 0.52), respectively compared to the times prior to the initiation of interventions. The median times from the order to administration of the first and third ASM for all NCSE occurrences were reduced by 8 and 10 min, respectively (p = 0.28 and p = 0.10). In the present cohort of comatose patients, the median time spent to order the first ASM was reduced by 16.5 min and the time to administer it reduced by 35 min compared to that in our previous study. The overall patient mortality was decreased by 11.1%.

SIGNIFICANCE

More efficient delivery of rescue ASMs in patients with NCSE and improvement in their mortality can be achieved with multidisciplinary team efforts aimed at streamlining the functioning of pharmacy and strengthening the education of trainees and nurses.

A Commentary on Electrographic Seizure Management and Clinical Outcomes in Critically Ill Children

Continuous EEG (cEEG) monitoring is the gold standard for detecting electrographic seizures in critically ill children and the current consensus-based guidelines recommend urgent cEEG to detect electrographic seizures that would otherwise be undetected. The detection of seizures usually leads to the use of antiseizure medications, even though current evidence that treatment leads to important improvements in outcomes is limited, raising the question of whether the current strategies need re-evaluation. There is emerging evidence indicating that the presence of electrographic seizures is not associated with unfavorable neurological outcome, and thus treatment is unlikely to alter the outcomes in these children. However, a high seizure burden and electrographic status epilepticus is associated with unfavorable outcome and the treatment of status epilepticus is currently warranted. Ultimately, outcomes are more likely a function of etiology than of a direct effect of the seizures themselves. We suggest re-examining our current consensus toward aggressive treatment to abolish all electrographic seizures and recommend a tailored approach where therapeutic interventions are indicated when seizure burden breaches above a critical threshold that may be associated with adverse outcomes. Future studies should explicitly evaluate whether there is a positive impact of treating electrographic seizures or electrographic status epilepticus in order to justify continuing current approaches.

Implementation of a Pediatric Neurocritical Care Program for Children With Status Epilepticus: Adherence to Continuous Electroencephalogram Monitoring

OBJECTIVES

To describe adherence to continuous electroencephalogram (cEEG) monitoring as part of a pediatric neurocritical care (PNCC) program for status epilepticus (SE).

DESIGN

Retrospective review of pre- and postintervention cohorts.

SETTING

A pediatric referral hospital.

PATIENTS

Children admitted to the PICU for SE.

INTERVENTIONS

We restructured the care delivery model to include a pediatric neurointensive care unit (neuro-ICU) and expanded the cEEG capacity. We created a criteria-based cEEG pathway. We provided education to all providers including the nursing staff.

MEASUREMENTS AND MAIN RESULTS

The main outcomes were: 1) the percentages of children meeting American Clinical Neurophysiology Society (ACNS) criteria who underwent cEEG monitoring and 2) the time interval between PICU arrival and cEEG initiation. PICU admissions with the diagnosis of SE from May 2017 to December 2017 served as the baseline, which was compared with the same periods in 2018 to 2020 (PNCC era).There were 60 admissions in the pre-PNCC period (2017), 111 in 2018, 118 in 2019, and 108 in 2020. The percentages of admissions from each period that met ACNS criteria for cEEG monitoring were between 84% and 97%. In the pre-PNCC era, 22 of 52 (42%) admissions meeting ACNS criteria underwent cEEG monitoring. In the PNCC era, greater than or equal to 80% of the qualified admissions underwent cEEG monitoring (74/93 [80%] in 2018, 94/115 [82%] in 2019, and 87/101 [86%] in 2020). Compared with the pre-PNCC era, the neuro-ICU had a shorter interval between PICU arrival and cEEG initiation (216 min [141-1,444 min] vs 138 min [103-211 min]).

CONCLUSIONS

The implementation of a PNCC program with initiatives in care delivery, allocation of resources, and education was associated with increased adherence to best care practices for the management of SE.

VEEG monitoring and electrographic seizures in 232 pediatric patients in ICU at a tertiary hospital in China

Objectives

To investigate neonatal electroencephalography (EEG) background activity and electrographic seizures in patients in the pediatric intensive care unit (PICU) who underwent bedside video-electroencephalography (vEEG) monitoring.

Methods

A total of 232 pediatric patients admitted or transferred to PICU that underwent vEEG monitoring were retrospectively enrolled in this study, and electrographic status epilepticus was observed after vEEG monitoring.

Results

The median age was 1.56 years [95% confidence interval (CI) = 1.12-2.44]. Electrographic seizures occurred in 88 patients (37.9%), out of which 36 cases (40.9%) had electrographic status epilepticus. Prior epileptic encephalopathy diagnosis [odds ratio (OR) = 6.57, 95% CI = 1.91-22.59, p = 0.003], interictal epileptiform discharges (OR = 46.82, 95%CI = 5.31-412.86, p = 0.0005), slow disorganized EEG background (OR = 11.92, 95%CI = 1.31-108.71, p = 0.028), and burst-suppression EEG background (OR = 23.64, 95%CI = 1.71-327.57, p = 0.018) were the risk factors for electrographic seizures' occurrence. Of the 232 patients, the condition of 179 (77.2%) patients improved and they were discharged, 34 cases (14.7%) were withdrawn, and 18 cases (7.8%) died. The in-hospital death rate was 47.6% (10 in 21 cases) in patients with attenuated/featureless, compared to 0/23 with normal EEG background.

Conclusions

Electrographic status epilepticus occurs in more than one-third of patients with electrographic seizures. vEEG is an efficient method to determine electrographic seizures in children. Abnormal EEG background activity is associated with both electrographic seizures' occurrence and unfavorable in-hospital outcomes.

Macroperiodic Oscillations Are Associated With Seizures Following Acquired Brain Injury in Young Children

PURPOSE

Seizures occur in 10% to 40% of critically ill children. We describe a phenomenon seen on color density spectral array but not raw EEG associated with seizures and acquired brain injury in pediatric patients.

METHODS

We reviewed EEGs of 541 children admitted to an intensive care unit between October 2015 and August 2018. We identified 38 children (7%) with a periodic pattern on color density spectral array that oscillates every 2 to 5 minutes and was not apparent on the raw EEG tracing, termed macroperiodic oscillations (MOs). Internal validity measures and interrater agreement were assessed. We compared demographic and clinical data between those with and without MOs.

RESULTS

Interrater reliability yielded a strong agreement for MOs identification (kappa: 0.778 [0.542-1.000]; P < 0.0001). There was a 76% overlap in the start and stop times of MOs among reviewers. All patients with MOs had seizures as opposed to 22.5% of the general intensive care unit monitoring population ( P < 0.0001). Macroperiodic oscillations occurred before or in the midst of recurrent seizures. Patients with MOs were younger (median of 8 vs. 208 days; P < 0.001), with indications for EEG monitoring more likely to be clinical seizures (42 vs. 16%; P < 0.001) or traumatic brain injury (16 vs. 5%, P < 0.01) and had fewer premorbid neurologic conditions (10.5 vs. 33%; P < 0.01).

CONCLUSIONS

Macroperiodic oscillations are a slow periodic pattern occurring over a longer time scale than periodic discharges in pediatric intensive care unit patients. This pattern is associated with seizures in young patients with acquired brain injuries.

Incidence of Seizure and Associated Risk Factors in Patients in the Medical Intensive Care Unit (ICU) at Memorial Sloan Kettering Cancer Center (MSK) from 2016-2017

Background: Seizures and status epilepticus are common neurologic complications in the intensive care unit (ICU) but the incidence in a cancer ICU is unknown. It is important to understand seizure risk factors in cancer patients to properly diagnose the seizure type to ensure appropriate therapy. Methods: We identified patients admitted to the medical ICU at Memorial Sloan Kettering Cancer Center (MSK) from January 2016 to December 2017 who had continuous or routine electroencephalography (EEG) and identified clinical and electrographic seizures by chart review. Results: Of the 1059 patients admitted to the ICU between 2016 and 2017, 50 patients had clinical and/or electrographic seizures (incidence of 4.7%, 95% CI: 3.4-6.0). The incidences of clinical and electrographic seizure were 4.1% and 1.1%, respectively. In a multivariable stepwise regression model, history of seizure (OR: 2.9, 95% CI: 1.1-7.8, P: .03), brain metastasis (OR: 2.5, 95% CI: 1.1-5.8, P: .03), vasopressor requirement (OR: 2.2, 95% CI: 1.0-4.9, P: .05), and age < 65 (2.4, 95% CI: 1.2-5.0, P: .02) were associated with increased risk of seizure (either clinical or electrographic). Obtaining continuous EEG instead of routine EEG increased the yield of seizure detection significantly (OR: 3.9, 95% CI: 1.3-11.1, P: .01). No chemotherapy in the past 30 days, no antibiotic use, vasopressor requirement, and having a brain tumor increased risk of electrographic seizure. Length of continuous EEG > 24 h significantly increased the chances of both clinical and electrographic seizure detection, (OR: 2.6 [95% CI: 1.2-5.7] and 15.0 [95% CI: 2.7-82.5], respectively). Conclusions: We identified known and cancer-related risk factors which can aid clinicians in diagnosing seizures in cancer ICUs. Long-term video EEG monitoring should be considered, particularly given the treatable and reversible nature of seizures.

The Role of Electroencephalography in the Prognostication of Clinical Outcomes in Critically Ill Children: A Review

Electroencephalography (EEG) is a neurologic monitoring modality that allows for the identification of seizures and the understanding of cerebral function. Not only can EEG data provide real-time information about a patient’s clinical status, but providers are increasingly using these results to understand short and long-term prognosis in critical illnesses. Adult studies have explored these associations for many years, and now the focus has turned to applying these concepts to the pediatric literature. The aim of this review is to characterize how EEG can be utilized clinically in pediatric intensive care settings and to highlight the current data available to understand EEG features in association with functional outcomes in children after critical illness. In the evaluation of seizures and seizure burden in children, there is abundant data to suggest that the presence of status epilepticus during illness is associated with poorer outcomes and a higher risk of mortality. There is also emerging evidence indicating that poorly organized EEG backgrounds, lack of normal sleep features and lack of electrographic reactivity to clinical exams portend worse outcomes in this population. Prognostication in pediatric critical illness must be informed by the comprehensive evaluation of a patient’s clinical status but the utilization of EEG may help contribute to this assessment in a meaningful way.

Benzodiazepine Use for Pediatric Patients With Suspected Nonconvulsive Status Epilepticus With or Without Simplified Electroencephalogram: A Retrospective Cohort Study

OBJECTIVES

In the present study, we aimed to determine the changes in the administration rate of benzodiazepines for pediatric patients with suspected nonconvulsive status epilepticus (NCSE) before and after the introduction of simplified electroencephalography (sEEG) in the emergency department.

METHODS

This retrospective cohort study included patients who were younger than 18 years and were admitted to the emergency department from August 1, 2009, to July 31, 2017, with altered level of consciousness and nonpurposeful movement of eyes or extremities after the cessation of convulsive status epilepticus. Patients with apparent persistent convulsions, those who were fully conscious on arrival, and those who were transferred from another hospital were excluded. The patients were categorized into pre and post groups based on the introduction of sEEG, and benzodiazepine administration was compared between the 2 groups.

RESULTS

During the study period, 464 patients with status epilepticus visited our emergency department and 69 and 93 patients fulfilling the study criteria were categorized into the pre and post groups, respectively. There were no significant differences in patient background characteristics between the 2 groups. Simplified electroencephalography was recorded in 52 patients in the post group. Benzodiazepines were administered in 44 of 69 patients (63.8%) in the pre group and 44 of 93 (47.3%) in the post group, and the benzodiazepine administration rate was significantly decreased after the introduction of sEEG ( P = 0.04). The hospitalization rate was significantly lower in the post group, but there were no significant differences in the rates of intensive care unit admission, reconvulsion after discharge, and final diagnoses between the 2 groups.

CONCLUSIONS

Simplified electroencephalography might aid in determining the need for anticonvulsant treatment for suspected NCSE in pediatric patients. Albeit not a definitive diagnostic tool, sEEG might be a reliable choice in the evaluation of pediatric patients with suspected NCSE.

Electroencephalographic Seizures in Emergency Department Patients After Treatment for Convulsive Status Epilepticus

PURPOSE

It is unknown how often and how early EEG is obtained in patients presenting with status epilepticus. The Established Status Epilepticus Treatment Trial enrolled patients with benzodiazepine-refractory seizures and randomized participants to fosphenytoin, levetiracetam, or valproate. The use of early EEG, including frequency of electrographic seizures, was determined in Established Status Epilepticus Treatment Trial participants.

METHODS

Secondary analysis of 475 enrollments at 58 hospitals to determine the frequency of EEG performed within 24 hours of presentation. The EEG type, the prevalence of electrographic seizures, and characteristics associated with obtaining early EEG were recorded. Chi-square and Wilcoxon rank-sum tests were calculated as appropriate for univariate and bivariate comparisons. Odds ratios are reported with 95% confidence intervals.

RESULTS

A total of 278 of 475 patients (58%) in the Established Status Epilepticus Treatment Trial cohort underwent EEG within 24 hours (median time to EEG: 5 hours [interquartile range: 3-10]). Electrographic seizure prevalence was 14% (95% confidence interval, 10%-19%; 39/278) in the entire cohort and 13% (95% confidence interval, 7%-21%) in the subgroup of patients meeting the primary outcome of the Established Status Epilepticus Treatment Trial (clinical treatment success within 60 minutes of randomization). Among subjects diagnosed with electrographic seizures (39), 15 (38%; 95% confidence interval, 25%-54%) had no clinical correlate on the video EEG recording.

CONCLUSIONS

Electrographic seizures may occur in patients who stop seizing clinically after treatment of convulsive status epilepticus. Clinical correlates might not be present during electrographic seizures. These findings support early initiation of EEG recordings in patients suffering from convulsive status epilepticus, including those with clinical evidence of treatment success.

Machine learning to support triage of children at risk for epileptic seizures in the pediatric intensive care unit

OBJECTIVE

Epileptic seizures are relatively common in critically-ill children admitted to the pediatric intensive care unit (PICU) and thus serve as an important target for identification and treatment. Most of these seizures have no discernible clinical manifestation but still have a significant impact on morbidity and mortality. Children that are deemed at risk for seizures within the PICU are monitored using continuous-electroencephalogram (cEEG). cEEG monitoring cost is considerable and as the number of available machines is always limited, clinicians need to resort to triaging patients according to perceived risk in order to allocate resources. This research aims to develop a computer aided tool to improve seizures risk assessment in critically-ill children, using an ubiquitously recorded signal in the PICU, namely the electrocardiogram (ECG).

APPROACH

A novel data-driven model was developed at a patient-level approach, based on features extracted from the first hour of ECG recording and the clinical data of the patient.

MAIN RESULTS

The most predictive features were the age of the patient, the brain injury as coma etiology and the QRS area. For patients without any prior clinical data, using one hour of ECG recording, the classification performance of the random forest classifier reached an area under the receiver operating characteristic curve (AUROC) score of 0.84. When combining ECG features with the patients clinical history, the AUROC reached 0.87.

SIGNIFICANCE

Taking a real clinical scenario, we estimated that our clinical decision support triage tool can improve the positive predictive value by more than 59% over the clinical standard.

Treatment of status epilepticus in pediatrics: curriculum learning combined with in-situ simulations

BACKGROUND

Appropriate and timely treatment of status epilepticus (SE) reduces morbidity and mortality. Therefore, skill-based identification and management are critical for emergency physicians.

PURPOSE

To assess whether the ability of training physicians, residents, nurses, and others to respond to SE as a team could be improved by using curriculum learning [Strategies and Tools to Enhance Performance and Patient Safety of Team (TeamSTEPPS) course training] combined with in-situ simulations of emergency department (ED) staff.

APPROACH

A pre-training-post-training design was used on SE skills and teamwork skills. Emergency training, residents, and N1 and N2 nurses completed the SE skill and teamwork assessments (pre-training) through in-situ simulation. Next, the participating physicians and nurses attended the SE course [Strategies and Tools to Enhance Performance and Patient Safety of Team (TeamSTEPPS) course training], followed by conscious skill practice, including in-situ simulation drills every 20 days (eight times total) and deliberate practice in the simulator. The participants completed the SE skill and teamwork assessments (post-training) again in an in-situ simulation. Pre-training-post-training simulated SE skills and teamwork performance were assessed. The simulation training evaluation showed that the training process was reasonable, and the training medical staff had different degrees of benefit in increasing subject interest, improving operational skills, theoretical knowledge, and work self-confidence.

FINDINGS

Sixty doctors and nurses participated in the intervention. When comparing the SE skills of 10 regular training physicians pre-training and post-training, their performance improved from 40% (interquartile range (IQR): 0-1) before training to 100% (IQR: 80.00-100) after training (p < 0.001). The teamwork ability of the 10 teams improved from 2.43 ± 0.09 before training to 3.16 ± 0.08 after training (p < 0.001).

CONCLUSION

SE curriculum learning combined with in-situ simulation training provides the learners with SE identification and management knowledge in children and teamwork skills.

Use of Continuous EEG Monitoring and Short-Term Outcomes in Critically Ill Children

This study aimed to compare short-term outcomes at pediatric intensive care unit (PICU) discharge in critically ill children with and without continuous electroencephalography (cEEG) monitoring. We retrospectively compared 234 patients who underwent cEEG with 2294 patients without cEEG. Propensity score matching was used to compare patients with seizures and status epilepticus between cEEG and historical cohorts. The EEG cohort had higher in-hospital mortality, worse Pediatric Cerebral Performance Category (PCPC) scores, and greater PCPC decline at discharge. In patients with status epilepticus, the PCPC decline was higher in the cEEG cohort. PCPC decline at PICU discharge was associated with cEEG monitoring in patients with status epilepticus.

Real-time seizure detection in paediatric intensive care patients: the RESET child brain protocol

INTRODUCTION

Approximately 20%-40% of comatose children with risk factors in intensive care have electrographic-only seizures; these go unrecognised due to the absence of continuous electroencephalography (EEG) monitoring (cEEG). Utility of cEEG with high-quality assessment is currently limited due to high-resource requirements. New software analysis tools are available to facilitate bedside cEEG assessment using quantitative EEG (QEEG) trends. The primary aim of this study is to describe accuracy of interpretation of QEEG trends by paediatric intensive care unit (PICU) nurses compared with cEEG assessment by neurologist (standard clinical care) in children at risk of seizures and status epilepticus utilising diagnostic test statistics. The secondary aims are to determine time to seizure detection for QEEG users compared with standard clinical care and describe impact of confounders on accuracy of seizure detection.

METHODS AND ANALYSIS

This will be a single-centre, prospective observational cohort study evaluating a paediatric QEEG programme utilising the full 19 electrode set. The setting will be a 36-bed quaternary PICU with medical, cardiac and general surgical cases. cEEG studies in PICU patients identified as 'at risk of seizures' will be analysed. Trained bedside clinical nurses will interpret the QEEG. Seizure events will be marked as seizures if >3 QEEG criteria occur. Post-hoc dedicated neurologists, who remain blinded to the QEEG analysis, will interpret the cEEG. Determination of standard test characteristics will assess the primary hypothesis. To calculate 95% (CIs) around the sensitivity and specificity estimates with a CI width of 10%, the sample size needed for sensitivity is 80 patients assuming each EEG will have approximately 9 to 18 1-hour epochs.

ETHICS AND DISSEMINATION

The study has received approval by the Children's Health Queensland Human Research Ethics Committee (HREC/19/QCHQ/58145). Results will be made available to the funders, critical care survivors and their caregivers, the relevant societies, and other researchers.

TRIAL REGISTRATION NUMBER

Australian New Zealand Clinical Trials Registry (ANZCTR) 12621001471875.

Pediatric Neurocritical Care

Brain injury in children is a major public health problem, causing substantial morbidity and mortality. Cause of pediatric brain injury varies widely and can be from a primary neurologic cause or as a sequela of multisystem illness. This review discusses the emerging field of pediatric neurocritical care (PNCC), including current techniques of imaging, treatment, and monitoring. Future directions of PNCC include further expansion of evidence-based practice guidelines and establishment of multidisciplinary PNCC services within institutions.

Continuous Video Electroencephalography (EEG) for Event Characterization in Critically Ill Children

OBJECTIVE

To determine features of paroxysmal events and background electroencephalographic (EEG) abnormalities associated with electroclinical seizures in critically ill children who undergo continuous video EEG to characterize clinical events.

METHODS

This is a prospective study of critically ill children from July 2016 to October 2018. Non-neonates with continuous video EEG indication to characterize a clinical event were included. Patients with continuous video EEG to assess for subclinical seizures due to unexplained encephalopathy and those whose event of concern were not captured on continuous video EEG were excluded. The event to be characterized was taken from documented descriptions of health care providers and classified as motor, ocular, orobuccal, autonomic, and other. In patients with more than 1 component to their paroxysmal event, the events were classified as motor plus and nonmotor plus.

RESULTS

One hundred patients met inclusion and exclusion criteria, with electroclinical seizures captured in 30% (30/100). The most common event to be characterized was an autonomic event in 32% (32/100). Asymmetry and epileptiform discharges were associated with electroclinical seizures (odds ratio [OR] 2.7, 95% confidence interval [CI] 1.1-6.5, P = .03; and OR 12.5, 95% CI 4.4-35.6, P < .0001). Autonomic events alone, particularly unexplained vital sign changes, were not associated with electroclinical seizures (OR 0.3, 95% CI 0.11-0.93, P = .03).

CONCLUSIONS

Isolated autonomic events are unlikely to be electroclinical seizures. Details of the paroxysmal events in question can help decide which patient will benefit most from continuous video EEG based on institutional resources.

Incidence and predictors of epilepsy in children with congenital heart disease

OBJECTIVE

Children with CHD may be at increased risk for epilepsy. While the incidence of perioperative seizures after surgical repair of CHD has been well-described, the incidence of epilepsy is less well-defined. We aim to determine the incidence and predictors of epilepsy in patients with CHD.

METHODS

Retrospective cohort study of patients with CHD who underwent cardiopulmonary bypass at <2 years of age between January, 2012 and December, 2013 and had at least 2 years of follow-up. Clinical variables were extracted from a cardiac surgery database and hospital records. Seizures were defined as acute if they occurred within 7 days after an inciting event. Epilepsy was defined based on the International League Against Epilepsy criteria.

RESULTS

Two-hundred and twenty-one patients were identified, 157 of whom were included in our analysis. Five patients (3.2%) developed epilepsy. Acute seizures occurred in 12 (7.7%) patients, only one of whom developed epilepsy. Predictors of epilepsy included an earlier gestational age, a lower birth weight, a greater number of cardiac surgeries, a need for extracorporeal membrane oxygenation or a left ventricular assist device, arterial ischaemic stroke, and a longer hospital length of stay.

CONCLUSIONS

Epilepsy in children with CHD is rare. The mechanism of epileptogenesis in these patients may be the result of a complex interaction of patient-specific factors, some of which may be present even before surgery. Larger long-term follow-up studies are needed to identify risk factors associated with epilepsy in these patients.

Amplitude-Integrated EEG Monitoring in Pediatric Intensive Care: Prognostic Value in Meningitis before One Year of Age

Pediatric morbidity from meningitis remains considerable. Preventing complications is a major challenge to improve neurological outcome. Seizures may reveal the meningitis itself or some complications of this disease. Amplitude-integrated electroencephalography (aEEG) is gaining interest for the management of patients with acute neurological distress, beyond the neonatal age. This study aimed at evaluating the predictive value of aEEG monitoring during the acute phase in meningitis among a population of infants hospitalized in the pediatric intensive care unit (PICU), and at assessing the practicability of the technique. AEEG records of 25 infants younger than one year of age hospitalized for meningitis were retrospectively analyzed and correlated to clinical data and outcome. Recording was initiated, on average, within the first six hours for n = 18 (72%) patients, and overall quality was considered as good. Occurrence of seizure, of status epilepticus, and the background pattern were significantly associated with unfavorable neurological outcomes. AEEG may help in the management and prognostic assessment of pediatric meningitis. It is an easily achievable, reliable technique, and allows detection of subclinical seizures with minimal training. However, it is important to consider the limitations of aEEG, and combinate it with conventional EEG for the best accuracy.

Prevalence and Risk Factors of Neurologic Manifestations in Hospitalized Children Diagnosed with Acute SARS-CoV-2 or MIS-C

BACKGROUND

Our objective was to characterize the frequency, early impact, and risk factors for neurological manifestations in hospitalized children with acute severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or multisystem inflammatory syndrome in children (MIS-C).

METHODS

Multicenter, cross-sectional study of neurological manifestations in children aged <18 years hospitalized with positive SARS-CoV-2 test or clinical diagnosis of a SARS-CoV-2-related condition between January 2020 and April 2021. Multivariable logistic regression to identify risk factors for neurological manifestations was performed.

RESULTS

Of 1493 children, 1278 (86%) were diagnosed with acute SARS-CoV-2 and 215 (14%) with MIS-C. Overall, 44% of the cohort (40% acute SARS-CoV-2 and 66% MIS-C) had at least one neurological manifestation. The most common neurological findings in children with acute SARS-CoV-2 and MIS-C diagnosis were headache (16% and 47%) and acute encephalopathy (15% and 22%), both P < 0.05. Children with neurological manifestations were more likely to require intensive care unit (ICU) care (51% vs 22%), P < 0.001. In multivariable logistic regression, children with neurological manifestations were older (odds ratio [OR] 1.1 and 95% confidence interval [CI] 1.07 to 1.13) and more likely to have MIS-C versus acute SARS-CoV-2 (OR 2.16, 95% CI 1.45 to 3.24), pre-existing neurological and metabolic conditions (OR 3.48, 95% CI 2.37 to 5.15; and OR 1.65, 95% CI 1.04 to 2.66, respectively), and pharyngeal (OR 1.74, 95% CI 1.16 to 2.64) or abdominal pain (OR 1.43, 95% CI 1.03 to 2.00); all P < 0.05.

CONCLUSIONS

In this multicenter study, 44% of children hospitalized with SARS-CoV-2-related conditions experienced neurological manifestations, which were associated with ICU admission and pre-existing neurological condition. Posthospital assessment for, and support of, functional impairment and neuroprotective strategies are vitally needed.

Evaluation and Treatment of Seizures and Epilepsy During the COVID-19 Pandemic

Purpose of Review

Seizures, including status epilepticus, have been reported in association with acute COVID-19 infection. People with epilepsy (PWE) have suffered from seizure exacerbations during the pandemic. This article reviews the data for clinical and electrographic seizures associated with COVID-19, technical EEG considerations for reducing risk of transmission, and factors contributing to seizure exacerbations in PWE as well as strategies to address this issue.

Recent Findings

An increasing number of studies of larger cohorts, accounting for a variety of variables and often utilizing EEG with standardized terminology, are assessing the prevalence of seizures in hospitalized patients with acute COVID-19 infections, and gaining insight into the prevalence of seizures and their effect on outcomes. Additionally, recent studies are evaluating the effect of the pandemic on PWE, barriers faced, and the usefulness of telehealth.

Summary

Although there is still much to learn regarding COVID-19, current studies help in assessing the risk of seizures, guiding EEG utilization, and optimizing the use of telehealth during the pandemic.