Ictal-interictal Continuum Patterns Research Articles

Ictal-Interictal Continuum in the Pediatric Intensive Care Unit.

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. 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). 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 3.4years (interquartile range (IQR) 0.6-12years). 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). 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.

Combined depth and scalp electroencephalographic monitoring in acute brain injury: Yield and prognostic value.

Depth electroencephalography (dEEG) is an emerging neuromonitoring technology in acute brain injury (ABI). We aimed to explore the concordances between electrophysiological activities on dEEG and on scalp EEG (scEEG) in ABI patients. Consecutive ABI patients who received dEEG monitoring between 2018 and 2022 were included. Background, sporadic epileptiform discharges, rhythmic and periodic patterns (RPPs), electrographic seizures, brief potentially ictal rhythmic discharges, ictal-interictal continuum (IIC) patterns, and hourly RPP burden on dEEG and scEEG were compared. Sixty-one ABI patients with a median dEEG monitoring duration of 114 h were included. dEEG significantly showed less continuous background (75% vs. 90%, p = 0.03), higher background amplitude (p < 0.001), more frequent rhythmic spike-and-waves (16% vs. 3%, p = 0.03), more IIC patterns (39% vs. 21%, p = 0.03), and greater hourly RPP burden (2430 vs. 1090 s/h, p = 0.01), when compared to scEEG. Among five patients with seizures on scEEG, one patient had concomitant seizures on dEEG, one had periodic discharges (not concomitant) on dEEG, and three had no RPPs on dEEG. Features and temporal occurrence of electrophysiological activities observed on dEEG and scEEG are not strongly associated. Patients with seizures and IIC patterns on dEEG seemed to have a higher rate of poor outcomes at discharge than patients without these patterns on dEEG (42% vs. 25%, p = 0.37). dEEG can detect abnormal electrophysiological activities that may not be seen on scEEG and can be used as a complement in the neuromonitoring of ABI patients.

High incidence of epileptiform activity in adults undergoing extracorporeal membrane oxygenation

ObjectiveThe prevalence of seizures and other types of epileptiform brain activity in patients undergoing extracorporeal membrane oxygenation (ECMO) is unknown. We aimed to estimate the prevalence of seizures and ictal-interictal continuum patterns in patients undergoing electroencephalography (EEG) during ECMO. MethodsRetrospective review of a prospective ECMO registry from 2011-2018 in a university-affiliated academic hospital. Adult subjects who had decreased level of consciousness and underwent EEG monitoring for seizure screening were included. EEG classification followed the American Clinical Neurophysiology Society criteria. Poor neurological outcome was defined as a Cerebral Performance Category of 3–5 at hospital discharge. ResultsThree hundred and ninety-five subjects had ECMO, and one hundred and thirteen (28.6%) had EEG monitoring. Ninety-two (23.3%) subjects had EEG performed during ECMO and were included in the study (average EEG duration 54 h). Veno-arterial ECMO was the most common cannulation strategy (83%) and 26 (28%) subjects had extracorporeal cardiopulmonary resuscitation. Fifty-eight subjects (63%) had epileptiform activity or ictal-interictal continuum patterns on EEG, including three (3%) subjects with nonconvulsive status epilepticus, 33 (36%) generalized periodic discharges, and 4 (5%) lateralized periodic discharges. Comparison between subjects with or without epileptiform activity showed comparable in-hospital mortality (57% vs. 47%, p = 0.38) and poor neurological outcome (and 56% and 36%, p = 0.23). Twenty-seven subjects (33%) had acute neuroimaging abnormalities (stroke N = 21). ConclusionsSeizures and ictal-interictal continuum patterns are commonly observed in patients managed with ECMO. Further studies are needed to evaluate whether epileptiform activity is an actionable target for interventions. SignificanceEpileptiform and ictal-interictal continuum abnormalities are frequently observed in patients supported with ECMO undergoing EEG monitoring.

Sleep Spindles and K-Complexes Are Favorable Prognostic Biomarkers in Critically Ill Patients.

In this narrative review, we summarize recent research on the prognostic significance of biomarkers of sleep in continuous EEG and polysomnographic recordings in intensive care unit patients. Recent studies show the EEG biosignatures of non-rapid eye movement 2 sleep (sleep spindles and K-complexes) on continuous EEG in critically ill patients better predict functional outcomes and mortality than the ictal-interictal continuum patterns. Emergence of more complex and better organized sleep architecture has been shown to parallel neurocognitive recovery and correlate with functional outcomes in traumatic brain injury and strokes. Particularly interesting are studies which suggest intravenous dexmedetomidine may induce a more biomimetic non-rapid eye movement sleep state than intravenous propofol, potentially providing more restorative sleep and lessening delirium. Protocols to improve intensive care unit sleep and neurophysiological studies evaluating the effect of these on sleep and sleep architecture are here reviewed.

Periodic and rhythmic patterns in critically ill children: Incidence, interrater agreement, and seizures.

We aimed to determine the incidence of periodic and rhythmic patterns (PRP), assess the interrater agreement between electroencephalographers scoring PRP using standardized terminology, and analyze associations between PRP and electrographic seizures (ES) in critically ill children. This was a prospective observational study of consecutive critically ill children undergoing continuous electroencephalographic monitoring (CEEG). PRP were identified by one electroencephalographer, and then two pediatric electroencephalographers independently scored the first 1-h epoch that contained PRP using standardized terminology. We determined the incidence of PRPs, evaluated interrater agreement between electroencephalographers scoring PRP, and evaluated associations between PRP and ES. One thousand three hundred ninety-nine patients underwent CEEG. ES occurred in 345 (25%) subjects. PRP, ES+PRP, and ictal-interictal continuum (IIC) patterns occurred in 142 (10%), 81 (6%), and 93 (7%) subjects, respectively. The most common PRP were generalized periodic discharges (GPD; 43, 30%), lateralized periodic discharges (LPD; 34, 24%), generalized rhythmic delta activity (GRDA; 34, 24%), bilateral independent periodic discharges (BIPD; 14, 10%), and lateralized rhythmic delta activity (LRDA; 11, 8%). ES risk varied by PRP type (p<.01). ES occurrence was associated with GPD (odds ratio [OR] = 6.35, p<.01), LPD (OR = 10.45, p<.01), BIPD (OR = 6.77, p<.01), and LRDA (OR = 6.58, p<.01). Some modifying features increased the risk of ES for each of those PRP. GRDA was not significantly associated with ES (OR = 1.34, p=.44). Each of the IIC patterns was associated with ES (OR = 6.83-8.81, p<.01). ES and PRP occurred within 6h (before or after) in 45 (56%) subjects. PRP occurred in 10% of critically ill children who underwent CEEG. The most common patterns were GPD, LPD, GRDA, BIPD, and LRDA. The GPD, LPD, BIPD, LRDA, and IIC patterns were associated with ES. GRDA was not associated with ES.

Continuous heart rate variability and electroencephalography monitoring in severe acute brain injury: a preliminary study.

BackgroundDecreases in heart rate variability have been shown to be associated with poor outcomes in severe acute brain injury. However, it is unknown whether the changes in heart rate variability precede neurological deterioration in such patients. We explored the changes in heart rate variability measured by electrocardiography in patients who had neurological deterioration following severe acute brain injury, and examined the relationship between heart rate variability and electroencephalography parameters.MethodsRetrospective analysis of 25 patients who manifested neurological deterioration after severe acute brain injury and underwent simultaneous electroencephalography plus electrocardiography monitoring.ResultsEighteen electroencephalography channels and one simultaneously recorded electrocardiography channel were segmented into epochs of 120-second duration and processed to compute 10 heart rate variability parameters and three quantitative electroencephalography parameters. Raw electroencephalography of the epochs was also assessed by standardized visual interpretation and categorized based on their background abnormalities and ictalinterictal continuum patterns. The heart rate variability and electroencephalography parameters showed consistent changes in the 2-day period before neurological deterioration commenced. Remarkably, the suppression ratio and background abnormality of the electroencephalography parameters had significant reverse correlations with all heart rate variability parameters.ConclusionsWe observed a significantly progressive decline in heart rate variability from the day before the neurological deterioration events in patients with severe acute brain injury were first observed.

EEG monitoring duration to identify electroencephalographic seizures in critically ill children.

To determine the optimal duration of continuous EEG monitoring (CEEG) for electrographic seizure (ES) identification in critically ill children. We performed a prospective observational cohort study of 719 consecutive critically ill children with encephalopathy. We evaluated baseline clinical risk factors (age and prior clinically evident seizures) and emergent CEEG risk factors (epileptiform discharges and ictal-interictal continuum patterns) using a multistate survival model. For each subgroup, we determined the CEEG duration for which the risk of ES was <5% and <2%. ES occurred in 184 children (26%). Patients achieved <5% risk of ES after (1) 6 hours if ≥1 year without prior seizures or EEG risk factors; (2) 1 day if <1 year without prior seizures or EEG risks; (3) 1 day if ≥1 year with either prior seizures or EEG risks; (4) 2 days if ≥1 year with prior seizures and EEG risks; (5) 2 days if <1 year without prior seizures but with EEG risks; and (6) 2.5 days if <1 year with prior seizures regardless of the presence of EEG risks. Patients achieved <2% risk of ES at the same durations except patients without prior seizures or EEG risk factors would require longer CEEG (1.5 days if <1 year of age, 1 day if ≥1 year of age). A model derived from 2 baseline clinical risk factors and emergent EEG risk factors would allow clinicians to implement personalized strategies that optimally target limited CEEG resources. This would enable more widespread use of CEEG-guided management as a potential neuroprotective strategy. NCT03419260.

A standardized nomenclature for spectrogram EEG patterns: Inter-rater agreement and correspondence with common intensive care unit EEG patterns

ObjectiveTo determine the inter-rater agreement (IRA) of a standardized nomenclature for EEG spectrogram patterns, and to estimate the probability distribution of ictal-interictal continuum (IIC) patterns vs. other EEG patterns within each category in this nomenclature. MethodsWe defined seven spectrogram categories: “Solid Flames”, “Irregular Flames”, “Broadband-monotonous”, “Narrowband-monotonous”, “Stripes”, “Low power”, and “Artifact”. Ten electroencephalographers scored 115 spectrograms and the corresponding raw EEG samples. Gwet's agreement coefficient was used to calculate IRA. ResultsSolid Flames represented seizures or IIC patterns 69.4% of the time. Irregular Flames represented seizures or IIC patterns 38.7% of the time. Broadband-monotonous primarily corresponded with seizures or IIC (54.3%) and Narrowband-monotonous with focal or generalized slowing (43.8%). Stripes were associated with burst-suppression (37.2%) and generalized suppression (34.4%). Low Power category was associated with generalized suppression (94%). There was “near perfect” agreement for Solid Flames (κ = 94.36), Low power (κ = 92.61), and Artifact (κ = 93.72). There was “substantial agreement” for all other categories (κ = 74.65–79.49). ConclusionsThis EEG spectrogram nomenclature has high IRA among electroencephalographers. SignificanceThe nomenclature can be a useful tool for EEG screening. Future studies are needed to determine if using this nomenclature shortens time to IIC identification, and how best to use it in practice to reduce time to intervention.

Successful Wean Despite Emergence of Ictal-Interictal EEG Patterns During the Weaning of Prolonged Burst-Suppression Therapy for Super-Refractory Status Epilepticus.

Management of refractory status epilepticus (SE) commonly involves the induction of burst suppression using intravenous anesthetic agents. However, the endpoints of these therapies are not well defined. Weaning anesthetic agents are complicated by the emergence of electroencephalogram (EEG) patterns along the ictal-interictal continuum (IIC), which have uncertain significance given that IIC patterns may worsen cerebral metabolism and oxygenation, have a dissociation between scalp and depth EEG recordings, or may indicate a late stage of SE itself. Determining the significance of IIC patterns in the unique context of anesthetic weaning is important to prevent the potential for unnecessarily prolonging anesthetic coma. Among 118 individuals with SE, we retrospectively identified a series of patients who underwent at least 24h of burst-suppression therapy, experienced two or more weaning trials, and developed IIC patterns during anesthetic weaning. Anesthetic titration strategies during the emergence of these patterns were examined. Each of the six individuals who met inclusion criteria experienced aggressive weaning despite the emergence of IIC patterns. The IIC patterns that were encountered during anesthetic weaning (including generalized and lateralized periodic discharges) are described in detail. Favorable outcomes were reported in each subject. IIC patterns encountered during anesthetic weaning may be transitional and warrant observation, allowing for the emergence of more definitive clinical or electrographic results. The metabolic impact of these IIC patterns on brain activity is uncertain, but weaning strategies that treat IIC as a surrogate of recurrent SE risk further prolonging anesthetic management and its known toxicity. We speculate that these patterns may have a context-specific association with SE relapse, with less-risk conferred when these patterns are observed during the weaning of anesthetic agents after prolonged burst-suppression therapy. Other electrographic features aside from this clinical context may discriminate the risk of SE relapse, such as EEG background activity.

Ictal-Interictal Continuum: When to Worry About the Continuous Electroencephalography Pattern.

Continuous electroencephalography (cEEG) monitoring is an invaluable tool in the evaluation of encephalopathy and coma in critically ill patients. Marked increases in cEEG monitoring, coinciding with several societal guideline statements in the last decade, have allowed earlier detection and treatment of clearly harmful patterns, including nonconvulsive seizures (NCSz) and nonconvulsive status epilepticus (NCSE). However, it has also unmasked a range of EEG patterns of less clear clinical significance, with some more "malignant" than others given their potential association with increased neuronal stress and secondary brain injury. These patterns lay on a spectrum often referred to as the ictal-interictal continuum (IIC). To date, no definitive guidelines exist for the management of these potentially harmful EEG patterns, thus presenting a clinical dilemma for critical care physicians. Here, we review the various IIC patterns, their associated features, seizure risk, and outcomes and also propose a clinical approach to management based on the available data and expert opinion.

The Ictal-Interictal Continuum: To Treat or Not to Treat (and How)?

Continuous electroencephalography (cEEG) monitoring is becoming increasingly used in neurologic and non-neurologic intensive care units (ICUs). Non-convulsive seizures (NCSz) and periodic discharges (PDs) are commonly seen in critically ill patients. Some of these PD patterns, also known as the ictal-interictal continuum (IIC), are associated with an increased risk of seizures and poor outcome. However, we do not fully understand the significance of these periodic patterns and the decision of how aggressively to treat remains controversial. IIC patterns are associated with pathophysiologic changes that closely resemble those of seizures. Here we make the argument that, rather than feature description on EEG, associated changes in brain physiology should dictate management choices.

Metabolic Correlates of the Ictal-Interictal Continuum: FDG-PET During Continuous EEG.

Ictal-interictal continuum (IIC) continuous EEG (cEEG) patterns including periodic discharges and rhythmic delta activity are associated with poor outcome and in the appropriate clinical context, IIC patterns may represent "electroclinical" status epilepticus (SE). To clarify the significance of IIC patterns and their relationship to "electrographic" SE, we investigated FDG-PET imaging as a complementary metabolic biomarker of SE among patients with IIC patterns. A single-center prospective clinical database was ascertained for patients undergoing FDG-PET during cEEG. Following MRI-PET co-registration, the maximum standardized uptake value in cortical and subcortical regions was compared to contralateral homologous and cerebellar regions. Consensus cEEG review and clinical rating of etiology and treatment response were performed retrospectively with blinding. Electrographic SE was classified as discrete seizures without interictal recovery or >3-Hz rhythmic IIC patterns. Electroclinical SE was classified as IIC patterns with electrographic and clinical response to anticonvulsants; clonic activity; or persistent post-ictal encephalopathy. Eighteen hospitalized subjects underwent FDG-PET during contemporaneous IIC patterns attributed to structural lesions (44%), neuroinflammatory/neuroinfectious disease (39%), or epilepsy (11%). FDG-PET hypermetabolism was common (61%) and predicted electrographic or electroclinical SE (sensitivity 79% [95% CI 53-93%] and specificity 100% [95% CI 51-100%]; p=0.01). Excluding electrographic SE, hypermetabolism also predicted electroclinical SE (sensitivity 80% [95% CI 44-94%] and specificity 100% [95% CI 51-100%]; p=0.01). In hospitalized patients with IIC EEG patterns, FDG-PET hypermetabolism is common and is a candidate metabolic biomarker of electrographic SE or electroclinical SE.