Electrographic seizures and ictal-interictal continuum (IIC) patterns in critically ill patients

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.

Real-World Continuous EEG Utilization and Outcomes in Hospitalized Patients With Acute Cerebrovascular Diseases

PURPOSE

Continuous electroencephalography (cEEG) is recommended for hospitalized patients with cerebrovascular diseases and suspected seizures or unexplained neurologic decline. We sought to (1) identify areas of practice variation in cEEG utilization, (2) determine predictors of cEEG utilization, (3) evaluate whether cEEG utilization is associated with outcomes in patients with cerebrovascular diseases.

METHODS

This cohort study of the Premier Healthcare Database (2014-2020), included hospitalized patients age >18 years with cerebrovascular diseases (identified by ICD codes). Continuous electroencephalography was identified by International Classification of Diseases (ICD)/Current Procedural Terminology (CPT) codes. Multivariable lasso logistic regression was used to identify predictors of cEEG utilization and in-hospital mortality. Propensity score-matched analysis was performed to determine the relation between cEEG use and mortality.

RESULTS

1,179,471 admissions were included; 16,777 (1.4%) underwent cEEG. Total number of cEEGs increased by 364% over 5 years (average 32%/year). On multivariable analysis, top five predictors of cEEG use included seizure diagnosis, hospitals with >500 beds, regions Northeast and South, and anesthetic use. Top predictors of mortality included use of mechanical ventilation, vasopressors, anesthetics, antiseizure medications, and age. Propensity analysis showed that cEEG was associated with lower in-hospital mortality (Average Treatment Effect -0.015 [95% confidence interval -0.028 to -0.003], Odds ratio 0.746 [95% confidence interval, 0.618-0.900]).

CONCLUSIONS

There has been a national increase in cEEG utilization for hospitalized patients with cerebrovascular diseases, with practice variation. cEEG utilization was associated with lower in-hospital mortality. Larger comparative studies of cEEG-guided treatments are indicated to inform best practices, guide policy changes for increased access, and create guidelines on triaging and transferring patients to centers with cEEG capability.

How Many Patients Do You Need? Investigating Trial Designs for Anti-Seizure Treatment in Acute Brain Injury Patients

Objectives

Epileptiform activity (EA) worsens outcomes in patients with acute brain injuries (e.g., aneurysmal subarachnoid hemorrhage [aSAH]). Randomized trials (RCTs) assessing anti-seizure interventions are needed. Due to scant drug efficacy data and ethical reservations with placebo utilization, RCTs are lacking or hindered by design constraints. We used a pharmacological model-guided simulator to design and determine feasibility of RCTs evaluating EA treatment.

Methods

In a single-center cohort of adults (age >18) with aSAH and EA, we employed a mechanistic pharmacokinetic-pharmacodynamic framework to model treatment response using observational data. We subsequently simulated RCTs for levetiracetam and propofol, each with three treatment arms mirroring clinical practice and an additional placebo arm. Using our framework we simulated EA trajectories across treatment arms. We predicted discharge modified Rankin Scale as a function of baseline covariates, EA burden, and drug doses using a double machine learning model learned from observational data. Differences in outcomes across arms were used to estimate the required sample size.

Results

Sample sizes ranged from 500 for levetiracetam 7 mg/kg vs placebo, to >4000 for levetiracetam 15 vs. 7 mg/kg to achieve 80% power (5% type I error). For propofol 1mg/kg/hr vs. placebo 1200 participants were needed. Simulations comparing propofol at varying doses did not reach 80% power even at samples >1200.

Interpretation

Our simulations using drug efficacy show sample sizes are infeasible, even for potentially unethical placebo-control trials. We highlight the strength of simulations with observational data to inform the null hypotheses and assess feasibility of future trials of EA treatment.

Interrater Reliability of Expert Electroencephalographers Identifying Seizures and Rhythmic and Periodic Patterns in EEGs

BACKGROUND AND OBJECTIVES

The validity of brain monitoring using electroencephalography (EEG), particularly to guide care in patients with acute or critical illness, requires that experts can reliably identify seizures and other potentially harmful rhythmic and periodic brain activity, collectively referred to as "ictal-interictal-injury continuum" (IIIC). Previous interrater reliability (IRR) studies are limited by small samples and selection bias. This study was conducted to assess the reliability of experts in identifying IIIC.

METHODS

This prospective analysis included 30 experts with subspecialty clinical neurophysiology training from 18 institutions. Experts independently scored varying numbers of ten-second EEG segments as "seizure (SZ)," "lateralized periodic discharges (LPDs)," "generalized periodic discharges (GPDs)," "lateralized rhythmic delta activity (LRDA)," "generalized rhythmic delta activity (GRDA)," or "other." EEGs were performed for clinical indications at Massachusetts General Hospital between 2006 and 2020. Primary outcome measures were pairwise IRR (average percent agreement [PA] between pairs of experts) and majority IRR (average PA with group consensus) for each class and beyond chance agreement (κ). Secondary outcomes were calibration of expert scoring to group consensus, and latent trait analysis to investigate contributions of bias and noise to scoring variability.

RESULTS

Among 2,711 EEGs, 49% were from women, and the median (IQR) age was 55 (41) years. In total, experts scored 50,697 EEG segments; the median [range] number scored by each expert was 6,287.5 [1,002, 45,267]. Overall pairwise IRR was moderate (PA 52%, κ 42%), and majority IRR was substantial (PA 65%, κ 61%). Noise-bias analysis demonstrated that a single underlying receiver operating curve can account for most variation in experts' false-positive vs true-positive characteristics (median [range] of variance explained ([Formula: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Formula: see text]: 75 [59, 89]%). Thus, variation between experts is mostly attributable not to differences in expertise but rather to variation in decision thresholds.

DISCUSSION

Our results provide precise estimates of expert reliability from a large and diverse sample and a parsimonious theory to explain the origin of disagreements between experts. The results also establish a standard for how well an automated IIIC classifier must perform to match experts.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that an independent expert review reliably identifies ictal-interictal injury continuum patterns on EEG compared with expert consensus.

Status Epilepticus in Older Adults: Diagnostic and Treatment Considerations

Status epilepticus (SE) is one of the leading life-threatening neurological emergencies in the elderly population, with significant morbidity and mortality. SE presents unique diagnostic and therapeutic challenges in the older population given overlap with other causes of encephalopathy, complicating diagnosis, and the common occurrence of multiple comorbid diseases complicates treatment. First-line therapy involves the use of rescue benzodiazepine in the form of intravenous lorazepam or diazepam, intramuscular or intranasal midazolam and rectal diazepam. Second-line therapies include parenteral levetiracetam, fosphenytoin, valproate and lacosamide, and underlying comorbidities guide the choice of appropriate medication, while third-line therapies may be influenced by the patient's code status as well as the cause and type of SE. The standard of care for convulsive SE is treatment with an intravenous anesthetic, including midazolam, propofol, ketamine and pentobarbital. There is currently limited evidence guiding appropriate therapy in patients failing third-line therapies. Adjunctive strategies may include immunomodulatory treatments, non-pharmacological strategies such as ketogenic diet, neuromodulation therapies and surgery in select cases. Surrogate decision makers should be updated early and often in refractory episodes of SE and informed of the high morbidity and mortality associated with the disease as well as the high probability of subsequent epilepsy among survivors.

Periodic discharges in veterinary electroencephalography-A visual review

First described in human EEG over 60 years ago, there are very few examples of periodic discharges in the veterinary literature. They are associated with a wide variety of etiologies, both intracranial and systemic, making interpretation challenging. Whether these patterns are indicative of ictal, interictal, or postictal activity is a matter of debate and may vary depending on the clinical features in an individual patient. Periodic discharges have a repeated waveform occurring at nearly regular intervals, with varying morphology of individual discharges from simple sharp waves or slow waves to more complex events. Amplitudes, frequencies, and morphologies of the discharges can fluctuate, occasionally evolving, or resolving over time. This study presents a visual review of several veterinary cases with periodic discharges on EEG similar to those described in human EEG, and discusses the current known pathophysiology of these discharges.

Simultaneous Electroencephalographic and Electocorticographic Recordings of Lateralized Periodic Discharges in Temporal Lobe Epilepsy

OBJECTIVE

Lateralized periodic discharges (LPDs), which constitute an abnormal electroencephalographic (EEG) pattern, are most often observed in critically ill patients with acute pathological conditions, and are less frequently observed in chronic conditions such as focal epilepsies, including temporal lobe epilepsy (TLE). Here we aim to explore the pathophysiological mechanism of LPD in TLE.

METHODS

We retrospectively selected 3 patients with drug-resistant TLE who simultaneously underwent EEG and electrocorticography (ECoG) and demonstrated LPDs. We analyzed the correlation between the EEG and ECoG findings.

RESULTS

In patients 1 and 2, LPDs were recorded in the temporal region of the scalp during the interictal periods, when repeated spikes followed by slow waves (spike-and-wave complexes; SWs) and periodic discharges (PDs) with amplitudes of >600 to 800 µV appeared in the lateral temporal lobe over a cortical area of >10 cm². In patient 3, when the ictal discharges persisted and were confined to the medial temporal lobe, repeated SWs were provoked on the lateral temporal lobe. When repeated SWs with amplitudes of >800 µV appeared in an area of the lateral temporal lobe of >10 cm², the corresponding EEG discharges appeared on the temporal scalp.

CONCLUSIONS

LPDs in patients with TLE originate from repeated SWs and PDs of the lateral temporal lobe, which might represent a highly irritable state of the lateral temporal cortex during both interictal and ictal periods.

High Incidence of Epileptiform Potentials During Continuous EEG Monitoring in Critically Ill COVID-19 Patients

Objective: To analyze continuous 1- or 2-channel electroencephalograms (EEGs) of mechanically ventilated patients with coronavirus disease 2019 (COVID-19) with regard to occurrence of epileptiform potentials. Design: Single-center retrospective analysis. Setting: Intensive care unit of Hannover Medical School, Hannover, Germany. Patients: Critically ill COVID-19 patients who underwent continuous routine EEG monitoring (EEG monitor: Narcotrend-Compact M) during sedation. Measurements and Main Results: Data from 15 COVID-19 patients (11 men, four women; age: 19-75 years) were evaluated. Epileptiform potentials occurred in 10 of 15 patients (66.7%). Conclusions: The results of the evaluation regarding the occurrence of epileptiform potentials show that there is an unusually high percentage of cerebral involvement in patients with severe COVID-19. EEG monitoring can be used in COVID-19 patients to detect epileptiform potentials.

Deep active learning for Interictal Ictal Injury Continuum EEG patterns

OBJECTIVES

Seizures and seizure-like electroencephalography (EEG) patterns, collectively referred to as "ictal interictal injury continuum" (IIIC) patterns, are commonly encountered in critically ill patients. Automated detection is important for patient care and to enable research. However, training accurate detectors requires a large labeled dataset. Active Learning (AL) may help select informative examples to label, but the optimal AL approach remains unclear.

METHODS

We assembled >200,000 h of EEG from 1,454 hospitalized patients. From these, we collected 9,808 labeled and 120,000 unlabeled 10-second EEG segments. Labels included 6 IIIC patterns. In each AL iteration, a Dense-Net Convolutional Neural Network (CNN) learned vector representations for EEG segments using available labels, which were used to create a 2D embedding map. Nearest-neighbor label spreading within the embedding map was used to create additional pseudo-labeled data. A second Dense-Net was trained using real- and pseudo-labels. We evaluated several strategies for selecting candidate points for experts to label next. Finally, we compared two methods for class balancing within queries: standard balanced-based querying (SBBQ), and high confidence spread-based balanced querying (HCSBBQ).

RESULTS

Our results show: 1) Label spreading increased convergence speed for AL. 2) All query criteria produced similar results to random sampling. 3) HCSBBQ query balancing performed best. Using label spreading and HCSBBQ query balancing, we were able to train models approaching expert-level performance across all pattern categories after obtaining ∼7000 expert labels.

CONCLUSION

Our results provide guidance regarding the use of AL to efficiently label large EEG datasets in critically ill patients.

Continuous EEG monitoring in the follow-up of convulsive status epilepticus patients: A proposal and preliminary validation of an EEG-based seizure build-up score (EaSiBUSSEs)

Continuous electroencephalography (EEG) is a major tool for monitoring patients admitted to the intensive care unit after refractory convulsive status epilepticus, following control of convulsive movements. We review the values of different EEG patterns observed in critically ill patients for prognosis and seizure risk, together with proposed criteria for non-convulsive status epilepticus diagnosis (Salzburg Criteria), the EEG scores for prognosis (Epidemiology-based Mortality score in Status Epilepticus, EMSE) and for seizure risk (2HELPS2B). These criteria and scores, based partially on continuous EEG, are not tailored to repetitively monitor the progressive build-up leading to seizure or status epilepticus recurrence. Therefore, we propose a new EEG-based seizure build-up score in status epilepticus (EaSiBUSSEs), based on the morphology and the prevalence of the EEG patterns observed in the follow-up of convulsive status epilepticus patients. It displays subscores from the least (no interictal activity) to the most associated with seizures (focal or generalized status epilepticus). We then evaluated the performance of the EaSiBUSSEs in a cohort of eleven patients who were admitted to intensive care unit for convulsive status epilepticus and who underwent continuous EEG recording. The receiver operating curve revealed good accuracy in identifying patients who would have seizures in the next 24 h, with excellent intra- and inter-rater reliability. We believe that this score is simple to perform, and suitable for repeated monitoring of EEG following refractory convulsive status epilepticus, with quantitative description of major EEG changes leading to seizures.

Ictal-interictal continuum: a review of recent advancements

Continuous electroencephalogram (cEEG) has become an indispensable technique in the management of critically ill patients for early detection and treatment of non-convulsive seizures (NCS) and non-convulsive status epilepticus (NCSE). It has also brought about a renaissance in a wide range of rhythmic and periodic patterns with heterogeneous frequency and morphology. These patterns share the rhythmic and sharp appearances of electrographic seizures, but often lack the necessary frequency, spatiotemporal evolution and clinical accompaniments to meet the definitive criteria for ictal patterns. They may be associated with cerebral metabolic crisis and neuronal injury, therefore not clearly interictal either, but lie along an intervening spectrum referred to as ictal-interictal continuum (IIC). Generally speaking, rhythmic and periodic patterns are categorized as interictal patterns when occurring at a rate of <1Hz, and are categorized as NCS and NCSE when occurring at a rate of >2.5 Hz with spatiotemporal evolution. As such, IIC commonly includes the rhythmic and periodic patterns occurring at a rate of 1–2.5 Hz without spatiotemporal evolution and clinical correlates. Currently there are no evidence-based guidelines on when and if to treat patients with IIC patterns, and particularly how aggressively to treat, presenting a challenging electrophysiological and clinical conundrum. In practice, a diagnostic trial with preferably a non-sedative anti-seizure medication (ASM) can be considered with the end point being both clinical and electrographic improvement. When available and necessary, correlation of IIC with biomarkers of neuronal injury, such as neuronal specific enolase (NSE), neuroimaging, depth electrode recording, cerebral microdialysis and oxygen measurement, can be assessed for the consideration of ASM treatment. Here we review the recent advancements in their clinical significance, risk stratification and treatment algorithm.