Generalized Periodic Discharges Research Articles

Cefepime-induced encephalopathy

Cefepime is a fourth-generation cephalosporin antibiotic widely used in clinical practice for various organ systems pathology treatment. The article describes the clinical observation of a patient who, 3 days after cefepime administration, had a decrease in the level of consciousness, regarded as encephalopathy. Cefepime-induced neurotoxicity is characterized by toxic encephalopathy, which manifests 2–6 days after the start of the treatment with this drug and disappears 1–3 days after its withdrawal. Electroencephalography (EEG) abnormalities include generalized periodic discharges (GPR) of triphasic morphology or a pattern corresponding to the criteria for non-convulsive status epilepticus (BSES). In our observation, the EEG recorded stimulus-induced GPRs of triphasic morphology with a frequency of 1.5 Hz; a test with intravenous administration of an antiepileptic drug (levetiracetam) was negative. A day after the withdrawal of cefepime, the patient’s level of consciousness returned to the initial level, and on the EEG periodic discharges completely regressed. Thus, cefepime may cause encephalopathy in patients with rhythmic or intermittent EEG activity, especially in the presence of a stimulus-induced component. In some cases, the use of cefepime may develop epileptic seizures and BSES.

Temporal dynamics of triphasic waves and generalized periodic discharges (P10-1.012)

<h3>Objective:</h3> To quantitatively compare triphasic waves and generalized periodic discharges on scalp EEG. <h3>Background:</h3> Distinguishing epileptiform generalized periodic discharges (GPDs) and triphasic waves (TWs) can be challenging (Foreman <i>et al.</i>, 2016), and consequential since groups may benefit from anti-seizure medications differently. Discharge regularity is an important feature recapitulated in computational models of TWs (Song <i>et al.</i>, 2019) and GPDs (Ruijter <i>et al.</i>, 2017). Recent analysis of GPDs in patients after cardiac arrest have shown that regularity of GPD duration, morphology, and amplitude, based on visual scoring, portend worse prognoses (Nadjar <i>et al.</i>, 2022). This suggests that variability of discharges could be a quantifiable tool in distinguishing GPDs from TWs. <h3>Design/Methods:</h3> We retrospectively collected inpatient EEG recordings marked to show GPDs and TWs from Harborview Medical Center between 11/2020 and 5/2021. The best derivation of a 30 second artifact free period on average reference montage was low pass filtered (0–15hz) for analysis. After visually identifying discharges, interdischarge intervals (IDIs) were calculated based on maximal deflection of each discharge. For each EEG, variance of IDIs was normalized by median IDI, to calculate a regularity index (RI). RI of GPDs and TWs were compared with a one-tailed Wilcoxon rank sum test. <h3>Results:</h3> 24 EEGs with TWs and 33 EEGs with GPDs were studied. Median RI for TWs was 0.438 with a variance of 3.08. Median RI for GPDs was 0.368 with a variance of 4.31. Groups were not statistically different (<i>p</i>=0.08). Excluding EEGs of following cardiac arrest, 23 EEGs with TWs and 10 EEGs with GPDs were studied. Median RI of TWs was 0.430 with variance of 3.14. Median RI of GPDs was 3.14 with variance of 13.7. Groups were not statistically different (<i>p</i>=0.27). <h3>Conclusions:</h3> Comparison of normalized variability in IDI does not distinguish TWs from GPDs but may have utility in the context of other clinical data. <b>Disclosure:</b> Dr. Plummer has nothing to disclose. Dr. Raut has nothing to disclose. Dr. Brunton has received personal compensation for serving as an employee of University of Washington. The institution of Dr. Brunton has received research support from National Science Foundation . The institution of Dr. Brunton has received research support from Air Force Office of Scientific Research. The institution of Dr. Brunton has received research support from National Science Foundation. Dr. Hakimian has received personal compensation in the range of $500-$4,999 for serving as a Consultant for OptumRx. Dr. Hakimian has stock in Various.

Clinical and Electroencephalographic Predictors of Seizures and Status Epilepticus in 12,450 Critically Ill Adults: A Retrospective Cohort Study.

Status epilepticus (SE) is associated with significantly higher morbidity and mortality than isolated seizures. Our objective was to identify clinical diagnoses and rhythmic and periodic electroencephalogram patterns (RPPs) associated with SE and seizures. Retrospective cohort study. Tertiary-care hospitals. Twelve thousand four hundred fifty adult hospitalized patients undergoing continuous electroencephalogram (cEEG) monitoring in selected participating sites in the Critical Care EEG Monitoring Research Consortium database (February 2013 to June 2021). Not applicable. We defined an ordinal outcome in the first 72 hours of cEEG: no seizures, isolated seizures without SE, or SE (with or without isolated seizures). Composite groups included isolated seizures or SE (AnySz) and no seizure or isolated seizures. In this cohort (mean age: 60 ± 17 yr), 1,226 patients (9.8%) had AnySz and 439 patients (3.5%) had SE. In a multivariate model, factors independently associated with SE were cardiac arrest (9.2% with SE; adjusted odds ratio, 8.8 [6.3-12.1]), clinical seizures before cEEG (5.7%; 3.3 [2.5-4.3]), brain neoplasms (3.2%; 1.6 [1.0-2.6]), lateralized periodic discharges (LPDs) (15.4%; 7.3 [5.7-9.4]), brief potentially ictal rhythmic discharges (BIRDs) (22.5%; 3.8 [2.6-5.5]), and generalized periodic discharges (GPDs) (7.2%; 2.4 [1.7-3.3]). All above variables and lateralized rhythmic delta activity (LRDA) were also associated with AnySz. Factors disproportionately increasing odds of SE over isolated seizures were cardiac arrest (7.3 [4.4-12.1]), clinical seizures (1.7 [1.3-2.4]), GPDs (2.3 [1.4-3.5]), and LPDs (1.4 [1.0-1.9]). LRDA had lower odds of SE compared with isolated seizures (0.5 [0.3-0.9]). RPP modifiers did not improve SE prediction beyond RPPs presence/absence ( p = 0.8). Using the largest existing cEEG database, we identified specific predictors of SE (cardiac arrest, clinical seizures prior to cEEG, brain neoplasms, LPDs, GPDs, and BIRDs) and seizures (all previous and LRDA). These findings could be used to tailor cEEG monitoring for critically ill patients.

Rapid response EEG with needle electrodes in an intensive care unit with limited resources

ObjectiveContinuous EEG (cEEG) is the gold standard for detecting seizures and rhythmic and periodic patterns (RPPs) in critically ill patients but is often not available in health systems with limited resources. The current study aims to determine the feasibility and utility of low-cost, practical, limited montage, sub-dermal needle electrode EEG in a setting where otherwise no EEG would be available. MethodsThe study included all adult patients admitted to the intensive care unit of a single center over a 24-month period. Members of the existing ICU care team, mostly nurses, were trained to place 8 sub-dermal needle EEG electrodes to achieve rapid, limited montage-EEG recording. Clinical outcomes were recorded, including any reported major complications; and the EEG findings documented, including background characterization, RPPs, and seizures. ResultsOne hundred twenty-three patients, mean age 68 years, underwent an average of 15.6 min of EEG recording. There were no complications of electrode placement. Overall, 13.0% had seizures (8.1% qualifying as status epilepticus [SE]), 18.7 % had generalized periodic discharges (GPDs), 4.9% had lateralized periodic discharges (LPDs), and 11.4 % sporadic epileptiform discharges (sEDs). Greater mortality was observed in patients with worse background EEGs, seizures, LPDs, or sEDs. ConclusionsRapid, limited montage EEG could be achieved safely and inexpensively in a broad population of critically ill patients following minimal training of existing care teams. SignificanceFor resource poor centers or centers outside of major metropolitan areas who otherwise have no access to EEG, this may prove a useful method for screening for non-convulsive seizures and status epilepticus.

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

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

Continuous EEG monitoring detects nonconvulsive seizure and Ictal-Interictal Continuum abnormalities in moderate to severe ICANS following systemic CAR-T therapy.

Immune Cell Effector Associated Neurotoxicity Syndrome (ICANS) is common amongst patients receiving CD19 targeted Chimeric Antigen Receptor T-cell (CAR-T) therapy. The purpose of this study is to characterize the incidence of seizures and ictal-interictal continuum (IIC) abnormalities in patients with ICANS. Retrospective review of consecutive patients treated with axicabtagene ciloleucel (axi-cel) for recurrent high-grade systemic lymphoma at Stanford Medical Center between 2/2016-6/2019. Electronic medical records (EMR) were reviewed for clinical features, treatment information, EEG data, CRS (cytokine release syndrome)/ICANS severity, and clinical outcomes. Fifty-six patients met inclusion criteria. 85.7% of patients developed CRS, and 58.9% developed ICANS. Twenty-eight patients had EEG monitoring, of whom 26 had ICANS. Median duration of EEG monitoring was 30 hours (range .5-126 hours). Four patients (7.1%) had seizures (1 patient had a clinical generalized seizure, 2 patients had clinical and nonconvulsive seizures, and 1 patient had an isolated non-convulsive seizure). Ictal-interictal continuum abnormalities were common, of which generalized periodic discharges (GPDs) with triphasic morphology and GPDs with epileptiform morphology were most frequently seen. Generalized periodic discharges with triphasic wave morphology were found across Grade 2-3 peak ICANS severity, however the majority (86%) of patients with epileptiform GPDs had Grade 3 peak ICANS severity. Among patients receiving axi-cel, seizure occurred in 7.1% of the total cohort, representing 12% of patients with ICANS. Ictal-interictal continuum abnormalities are also seen in patients with ICANS, most commonly GPDs. 75% of patients with seizures had nonconvulsive seizures supporting the use of continuous video EEG monitoring in this population.

Transition dynamics and optogenetic control of epileptiform activity in a modified mean filed model of human cortex

Physiological experiments have shown that inhibitory interneurons can induce and maintain epileptiform activities, and different interneuron subtypes may be responsible for different types of seizures. Here we aim to link these electrophysiological experimental phenomena with theoretical dynamic mechanisms based on an improved Liley mean field model. Fascinatingly, the number of synapses between inhibitory neural populations can induce a rich state transition. Typically, the system will experience normal rhythm discharges, multispike discharges, spike wave discharges (SWD), generalized periodic discharges (GPD), the beta band oscillation, and eventually return to the normal state. Interestingly, the transition process can also be reversed. Meanwhile, disinhibition circuits can cause more epileptiform activities after taking into account the delay of synaptic information transmission. Furthermore, we are committed to designing different control strategies for epileptiform activities. As we expected, both deep brain stimulation and optogenetic technology can destroy or even eliminate pathological waves. It is need to emphasis that the cell type specificity of optogenetic regulation allows it to precisely target inhibitory neural populations, which is agree with experiment. Particularly, three different optogenetic regulatory strategies targeting inhibitory neural populations are modeled and proposed, of which the intermittent is designed to save energy. These modeling results reproduce the experimental phenomena and more significantly, help understand the mechanism of epilepsy to guide the clinical practice.

Independent risk factors for seizures in critically ill patients on continuous EEG.

The objective of this study was to characterize the independent risk factors for seizures in critically ill patients monitored with continuous EEG (cEEG). We retrospectively investigated variables associated with cEEG seizures, first in the entire cohort of 156 patients and, subsequently, in the subgroup without seizures in the first 30 minutes of monitoring. Seizures were observed in 19.2% of recordings, and in 50% of these, seizures occurred in the first 30 minutes. In the entire cohort, epilepsy, acute seizures prior to cEEG, interictal epileptiform discharges (IEDs), lateralized periodic discharges (LPDs), and brief potentially ictal rhythmic discharges (BIRDs) were associated with a higher incidence of cEEG seizures, whereas coma, intravenous anaesthetic drugs, and generalized periodic discharges (GPDs) were associated with a lower incidence of seizures. On multivariate analysis, this association was maintained for acute seizures before cEEG (OR: 5.92) and IEDs (OR: 6.81). Excluding patients with seizures at the beginning of monitoring, acute seizures before cEEG, IEDs, LPDs, and BIRDs were associated with an increased risk of seizures. The presence of IEDs or LPDs in the first 30 minutes was associated with a 4.14-fold greater chance of seizures on cEEG. On multivariate analysis, acute seizures prior to recording (OR 7.29) and LPDs (OR: 5.38) remained associated with seizures on cEEG. Due to the sample size, BIRDs were not included in multivariate models. Acute seizures prior to monitoring, IEDs, LPDs and BIRDs are important risk factors for cEEG seizures in critically ill patients.

Risk factors that predict delayed seizure detection on continuous electroencephalogram (cEEG) in a large sample size of critically ill patients.

SummaryObjectiveMajority of seizures are detected within 24 hours on continuous EEG (cEEG). Some patients have delayed seizure detection after 24 hours. The purpose of this research was to identify risk factors that predict delayed seizure detection and to determine optimal cEEG duration for various patient subpopulations.MethodsWe retrospectively identified all patients ≥18 years of age who underwent cEEG at Cleveland clinic during calendar year 2016. Clinical and EEG data for all patients and time to seizure detection for seizure patients were collected.ResultsTwenty‐four hundred and two patients met inclusion criteria. Of these, 316 (13.2%) had subclinical seizures. Sixty‐five (20.6%) patients had delayed seizures detection after 24 hours. Seizure detection increased linearly till 36 hours of monitoring, and odds of seizure detection increased by 46% for every additional day of monitoring. Delayed seizure risk factors included stupor (13.2% after 48 hours, P = .031), lethargy (25.9%, P = .013), lateralized (LPDs) (27.7%, P = .029) or generalized periodic discharges (GPDs) (33.3%, P = .022), acute brain insults (25.5%, P = .036), brain bleeds (32.8%, P = .014), especially multiple concomitant bleeds (61.1%, P < .001), altered mental status (34.7%, P = .001) as primary cEEG indication, and use of antiseizure medications (27.8%, P < .001) at cEEG initiation.SignificanceGiven the linear seizure detection trend, 36 hours of standard monitoring appears more optimal than 24 hours especially for high‐risk patients. For awake patients without epileptiform discharges, <24 hours of monitoring appears sufficient. Previous studies have shown that coma and LPDs predict delayed seizure detection. We found that stupor and lethargy were also associated with delayed seizure detection. LPDs and GPDs were associated with delayed seizures. Other delayed seizure risk factors included acute brain insults, brain bleeds especially multiple concomitant bleeds, altered mental status as primary cEEG indication, and use of ASMs at cEEG initiation. Longer cEEG (≥48 hours) is suggested for these high‐risk patients.

Do Triphasic Waves and Nonconvulsive Status Epilepticus Arise From Similar Mechanisms? A Computational Model.

Triphasic waves arising in patients with toxic metabolic encephalopathy (TME) are often considered different from generalized periodic discharges (GPDs) in patients with generalized nonconvulsive status epilepticus (GNCSE). The primary objective of this study was to investigate whether a common mechanism can explain key aspects of both triphasic waves in TME and GPDs in GNCSE. A neural mass model was used for the simulation of EEG patterns in patients with acute hepatic encephalopathy, a common etiology of TME. Increased neuronal excitability and impaired synaptic transmission because of elevated ammonia levels in acute hepatic encephalopathy patients were used to explain how triphasic waves and GNCSE arise. The effect of gamma-aminobutyric acid-ergic drugs on epileptiform activity, simulated with a prolonged duration of the inhibitory postsynaptic potential, was also studied. The simulations show that a model that includes increased neuronal excitability and impaired synaptic transmission can account for both the emergence of GPDs and GNCSE and their suppression by gamma-aminobutyric acid-ergic drugs. The results of this study add to evidence from other studies calling into question the dichotomy between triphasic waves in TME and GPDs in GNCSE and support the hypothesis that all GPDs, including those arising in TME patients, occur via a common mechanism.

Incidence of Electrographic Seizures in Patients With COVID-19.

Critical illness and sepsis are commonly associated with subclinical seizures. COVID-19 frequently causes severe critical illness, but the incidence of electrographic seizures in patients with COVID-19 has been reported to be low. This retrospective case series assessed the incidence of and risks for electrographic seizures in patients hospitalized with COVID-19 who underwent continuous video electroencephalography monitoring (cvEEG) between March 1st, 2020 and June 30th, 2020. One hundred and twenty-two patients were initially identified who resulted SARS-CoV-2 nasopharyngeal RT-PCR swab positivity with any electroencephalography order placed in the EMR. Seventy-nine patients met study inclusion criteria: age ≥18 years, >1 h of cvEEG monitoring, and positive SARS-CoV-2 nasopharyngeal swab PCR. Six (8%) of the 79 patients suffered electrographic seizures (ES), three of whom suffered non-convulsive status epilepticus. Acute hyperkinetic movements were the most common reason for cvEEG in patients with ES (84%). None of the patients undergoing cvEEG for persistent coma (29% of all patients) had ES. Focal slowing (67 vs. 10%), sporadic interictal epileptiform discharges (EDs; 33 vs. 6%), and periodic/rhythmic EDs (67 vs. 1%) were proportionally more frequent among patients with electrographic seizures than those without these seizures. While 15% of patients without ES had generalized periodic discharges (GPDs) with triphasic morphology on EEG, none of the patients with ES had this pattern. Further study is required to assess the predictive values of these risk factors on electrographic seizure incidence and subsequent outcomes.

Association of Epileptiform Abnormality on Electroencephalography with Development of Epilepsy After Acute Brain Injury.

Epileptiform abnormalities (EA) on continuous electroencephalography (cEEG) are associated with increased risk of acute seizures; however, data on their association with development of long-term epilepsy are limited. We aimed to investigate the association of EA in patients with acute brain injury (ABI): ischemic or hemorrhagic stroke, traumatic brain injury, encephalitis, or posterior reversible encephalopathy syndrome, and subsequent development of epilepsy. This was a retrospective, single-center study of patients with ABI who had at least 6hours of cEEG during the index admission between 1/1/2017 and 12/31/2018 and at least 12months of follow-up. We compared patients with EAs; defined as lateralized periodic discharges (LPDs), lateralized rhythmic delta activity (LRDA), generalized periodic discharges (GPDs), and sporadic interictal epileptiform discharges (sIEDs) to patients without EAs on cEEG. The primary outcome was the new development of epilepsy, defined as the occurrence of spontaneous clinical seizures following hospital discharge. Secondary outcomes included time to development of epilepsy and use of anti-seizure medications (ASMs) at the time of last follow-up visit. One hundred and one patients with ABI met study inclusion criteria. Thirty-one patients (30.7%) had EAson cEEG. The median (IQR) time to cEEG was 2 (1-5) days. During a median (IQR) follow-up period of 19.1 (16.2-24.3) months, 25.7% of patients developed epilepsy; the percentage of patients who developed epilepsy was higher in those with EAs compared to those without EAs (41.9% vs. 18.6%, p = 0.025). Patients with EAs were more likely to be continued on ASMs during follow-up compared to patients without EAs (67.7% vs. 38.6%, p = 0.009). Using multivariable Cox regression analysis, after adjusting for age, mental status, electrographic seizures on cEEG, sex, ABI etiology, and ASM treatment on discharge, patients with EAs had a significantly increased risk of developing epilepsy compared to patients without EA (hazard ratio 3.39; 95% CI 1.39-8.26; p = 0.007). EAs on cEEG in patients with ABI are associated with a greater than three-fold increased risk of new-onset epilepsy. cEEG findings in ABI may therefore be a useful risk stratification tool for assessing long-term risk of seizures and serve as a biomarker for new-onset epilepsy.

Triphasic waves on electroencephalogram in patients with encephalopathy and their diagnosis significance. A review

Triphasic waves are high-amplitude (&gt;70 µV) positive sharp transients preceded and followed by relatively low-amplitude negative waves. The distribution is generalized and tends to have a repetition rate of approximately 1 to 2 Hz. This EEG-pattern is traditionally associated with hepatic encephalopathy, although they have been observed in a wide array of neurological disorders including subcortical white-matter disease, infections, metabolic disturbances and nonconvulsive status epilepticus.American Clinical Neurophysiology Society suggested Standardized Critical Care EEG Terminology (2012). One of the goals was to eliminate terms with clinical connotations, such as ‘triphasic waves’, a term that implies a metabolic encephalopathy with no relationship to seizures for many clinicians. The term ‘triphasic waves’ was replaced by ‘Generalized periodic discharges (GPDs) with triphasic morphology’. The clinical significance ofthese waveforms and their relationship with seizures and prognosis has been debated, and differentiation between interictal patterns, patternsassociated with seizures, and the patterns representing nonconvulsive status epilepticus have been concluded to be a challenge. In cases of uncertainty, the decision to treat should follow on a thorough evaluation with a continuous EEG monitoring and using a short-acting benzodiazepine or non-sedating antiepileptic drugs in order to discern the effects of the pattern on the patient’s clinical exam and EEG.

American Clinical Neurophysiology Society's Standardized Critical Care EEG Terminology: 2021 Version.

In the early 2000s, a subcommittee of the American Clinical Neurophysiology Society (ACNS) set out to “standardize terminology of periodic and rhythmic EEG patterns in the critically ill to aid in future research involving such patterns.” The initial proposed terminology was published in 2005.1 This was presented at many meetings on several continents, subjected to multiple rounds of testing of interrater reliability, underwent many revisions, and was then published as an ACNS guideline in 2013.2 Interrater agreement of the 2012 version (published in early 2013) was very good, with almost perfect agreement for seizures, main terms 1 and 2, the +S modifier, sharpness, absolute amplitude, frequency, and number of phases.3 Agreement was substantial for the +F and +R modifiers (66% and 67%) but was only moderate for triphasic morphology (58%) and fair for evolution (21%, likely at least partly because of the short EEG samples provided).3 The authors concluded that interrater agreement for most terms in the ACNS critical care EEG terminology was high and that these terms were suitable for multicenter research on the clinical significance of these critical care EEG patterns. With the help of infrastructure funding from the American Epilepsy Society and administrative and website support from the ACNS, a database that incorporated the ACNS terminology was developed for clinical and research purposes, tested during routine clinical care in multiple centers,4 and made available at no cost on the ACNS website (https://www.acns.org/research/critical-care-eeg-monitoring-research-consortium-ccemrc/ccemrc-public-database). This greatly enhanced the ability to complete multicenter investigations. After the establishment of the standardized terminology and free access to a database incorporating these terms, there have been many investigations into the clinical significance of rhythmic and periodic patterns (RPPs) in critically ill patients. Patterns such as lateralized rhythmic delta activity (LRDA) were found to be highly associated with acute seizures,5,6 equivalent to the association found with lateralized periodic discharges (LPDs) in one study.5 The association of all the main patterns in the nomenclature with seizures was defined in a multicenter cohort of almost 5,000 patients, with seizure rates highest for LPDs, intermediate for LRDA and generalized periodic discharges (GPDs), and lowest for generalized rhythmic delta activity (GRDA).6 This and other studies have shown that several of the modifiers within the nomenclature do indeed have clinically relevant meaning. For example, studies have shown that higher frequency (especially >1.5 Hz), higher prevalence, longer duration, and having a “plus” modifier are all associated with a higher chance of acute seizures.6,7 On the other hand, whether a pattern was spontaneous or “stimulus-induced” did not seem to have a significant effect on its association with seizures.6 In other investigations, the “triphasic morphology” modifier was investigated blindly with multiple expert reviewers, calling into question its relationship with metabolic encephalopathy and its lack of a relationship with seizures.8,9 For patients with refractory status epilepticus treated with anesthetic-induced coma, the presence of “highly epileptiform” bursts suggested that an attempted wean off of anesthetics at that time was much more likely to lead to seizure recurrence than if the bursts were not highly epileptiform.10 Even long-term outcome seemed to be associated with some modifiers, with a higher risk of later epilepsy found if LPDs were more prevalent, had longer duration, or had a “plus” modifier.7

Anesthesia-Associated Periodic Discharges.

Anesthetic agents have been widely used in the treatment of refractory status epilepticus and the medical management of increased intracranial pressure whenever the goal is therapeutic burst suppression. Periodic patterns typically consisting of generalized periodic discharges (GPDs) following emergence from anesthesia have been described in several case reports. However, their clinical significance and in particular whether these patterns are epileptiform remains unclear. This is a single-center, retrospective, observational study examining EEG patterns following emergence from pharmacologically induced burst suppression. Clinical and EEG data were collected. Patients who developed GPDs following anesthetic wean were compared with those who did not. Over 4.5 years, 14 patients developed GPDs related to anesthetic withdrawal. The GPDs had a frequency between 0.5 and 2.5 Hz. Generalized periodic discharges related to anesthetic withdrawal were transient, with a median duration of 40 hours (interquartile range, 24-48 hours). Notably, in all patients, the pattern was stimulus dependent. When compared with a control group of 19 consecutive patients who did not develop a generalized periodic pattern in the context of the anesthetic wean, there was no significant difference in the status epilepticus relapse between the two groups (29% vs. 44%; P = 0.63). Patients in the GPD group were more likely to be on pentobarbital (93% vs. 58%; P = 0.05) and were more likely to have concomitant systemic infection treated with antibiotics compared with the control group (86% vs. 42%; P = 0.02). Generalized periodic patterns are common following the wean of intravenous anesthetics (particularly pentobarbital) and likely represent a transitional encephalopathic state in a subset of patients. Their morphology is distinct and can be differentiated from the reemergence of status epilepticus (if the latter was the indication for anesthetic treatment). Failure to recognize this pattern may lead to prolonged unnecessary treatments if it is mistaken for the emergence of seizure activity. The presence of concomitant systemic infection and associated antibiotic treatment may be risk factors for the development of this pattern.

COVID-19 EEG Studies: The Other Coronavirus Spikes We Need to Worry About.

Report of Electroencephalographic Finding on Critically Ill Patients With COVID-19 Vespignani H, Colas D, Lavin BS, et al. Ann Neurol. 2020. https://onlinelibrary.wiley.com/doi/full/10.1002/ana.25814 In March 2020, we treated a cohort of 26 critically ill hospitalized SARS-CoV-2 infected patients who received EEGs to assess unexplained altered mental status, loss of consciousness, or poor arousal and responsiveness. Of the 26 patients studied, 5 patients had EEGs that showed periodic discharges (PD) consisting of high amplitude frontal monomorphic delta waves with absence of epileptic activity. These findings may suggest CNS injury potentially related to COVID-19 in these patients. EEG Findings in Acutely Ill Patients Investigated for SARS-CoV-2/COVID-19: A Small Case Series Preliminary Report Galanopoulou AS, Ferastraoaru V, Correa DJ, et al. Epilepsia Open. 2020;5(2):314-324. https://doi.org/10.1002/epi4.12399 Objective:Acute encephalopathy may occur in COVID-19-infected patients. We investigated whether medically indicated EEGs performed in acutely ill patients under investigation (PUIs) for COVID-19 report epileptiform abnormalities and whether these are more prevalent in COVID-19 positive than negative patients.Methods:In this retrospective case series, adult COVID-19 inpatient PUIs underwent EEGs for acute encephalopathy and/or seizure-like events. PUIs had 8-channel headband EEGs (Ceribell; 20 COVID-19 positive, 6 COVID-19 negative); 2 more COVID-19 patients had routine EEGs. Overall, 26 Ceribell EEGs, 4 routine, and 7 continuous EEG studies were reviewed. EEGs were interpreted by board-certified clinical neurophysiologists (n = 16). EEG findings were correlated with demographic data, clinical presentation and history, and medication usage. Fisher exact test was used.Results:We included 28 COVID-19 PUIs (30-83 years old), of whom 22 tested positive (63.6% males) and 6 tested negative (33.3% male). The most common indications for EEG, among COVID-19-positive versus COVID-19-negative patients, respectively, were new onset encephalopathy (68.2% vs 33.3%) and seizure-like events (14/22, 63.6%; 2/6, 33.3%), even among patients without prior history of seizures (11/17, 64.7%; 2/6, 33.3%). Sporadic epileptiform discharges (EDs) were present in 40.9% of COVID-19-positive and 16.7% of COVID-19-negative patients; frontal sharp waves were reported in 8/9 (88.9%) of COVID-19-positive patients with EDs and in 1/1 of COVID-19-negative patient with EDs. No electrographic seizures were captured, but 19/22 COVID-19-positive and 6/6 COVID-19-negative patients were given anti-seizure medications and/or sedatives before the EEG.Significance:This is the first preliminary report of EDs in the EEG of acutely ill COVID-19-positive patients with encephalopathy or suspected clinical seizures. EDs are relatively common in this cohort and typically appear as frontal sharp waves. Further studies are needed to confirm these findings and evaluate the potential direct or indirect effects of COVID-19 on activating epileptic activity. Electroencephalogram (EEG) in COVID-19: A systematic Retrospective Study Petrescu AM, Taussig D, Bouilleret V. Neurophysiol Clin. 2020;50(3):155-165. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7315937/ Objectives:Although rare, neurological manifestations in SARS-CoV-2 infection are increasingly being reported. We conducted a retrospective systematic study to describe the electroencephalography (EEG) characteristics in this disease, looking for specific patterns.Methods:EEGs performed in patients with positive PCR for SARS-CoV-2 between March 25, 2020 and May 06, 2020 in the University Hospital of Bicetre were independently reviewed by 2 experienced neurologists. We used the American Clinical Neurophysiology Society’s terminology for the description of abnormal patterns. EEGs were classified into 5 categories, from normal to critically altered. Interobserver reliability was calculated using Cohen kappa coefficient. Medical records were reviewed to extract demographics, clinical, imaging, and biological data.Results:Forty EEGs were reviewed in 36 COVID-19 patients, 18 in intensive care units (ICU) and 22 in medicine units. The main indications were confusion or fluctuating alertness for 23 (57.5%) and delayed awakening after stopping sedation in ICU in 6 (15%). EEGs were normal to mildly altered in 23 (57.5%) contrary to the 42.5% where EEG alterations were moderate in 4 (10%), severe in 8 (20%), and critical in 5 (12.5%). Generalized periodic discharges (GPDs), multifocal periodic discharges (MPDs), or rhythmic delta activity (RDA) were found in 13 recordings (32.5%). EEG alterations were not stereotyped or specific. They could be related to an underlying morbid status, except for 3 ICU patients with unexplained encephalopathic features.Conclusion:In this first systematic analysis of COVID-19 patients who underwent EEG, over half of them presented a normal recording pattern. EEG alterations were not different from those encountered in other pathological conditions.

Electroencephalogram (EEG) in COVID-19: A systematic retrospective study

SummaryObjectivesAlthough rare, neurological manifestations in SARS-CoV-2 infection are increasingly being reported. We conducted a retrospective systematic study to describe the electroencephalography (EEG) characteristics in this disease, looking for specific patterns.MethodsEEGs performed in patients with positive PCR for SARS-CoV-2 between 25/03/2020 and 06/05/2020 in the University Hospital of Bicêtre were independently reviewed by two experienced neurologists. We used the American Clinical Neurophysiology Society's terminology for the description of abnormal patterns. EEGs were classified into five categories, from normal to critically altered. Interobserver reliability was calculated using Cohen's kappa coefficient. Medical records were reviewed to extract demographics, clinical, imaging and biological data.ResultsForty EEGs were reviewed in 36 COVID-19 patients, 18 in intensive care units (ICU) and 22 in medicine units. The main indications were confusion or fluctuating alertness for 23 (57.5%) and delayed awakening after stopping sedation in ICU in six (15%). EEGs were normal to mildly altered in 23 (57.5%) contrary to the 42.5% where EEG alterations were moderate in four (10%), severe in eight (20%) and critical in five (12.5%). Generalized periodic discharges (GPDs), multifocal periodic discharges (MPDs) or rhythmic delta activity (RDA) were found in 13 recordings (32.5%). EEG alterations were not stereotyped or specific. They could be related to an underlying morbid status, except for three ICU patients with unexplained encephalopathic features.ConclusionIn this first systematic analysis of COVID-19 patients who underwent EEG, over half of them presented a normal recording pattern. EEG alterations were not different from those encountered in other pathological conditions.

Presence of generalized periodic discharges and hospital mortality.

Generalized periodic discharges (GPDs) are rare patterns that can be found in long-term electroencephalographic monitoring in critical patients. These patterns have been correlated with non-seizure crisis and non-convulsive status epilepticus, associated with poor prognosis. To compare the outcome between patients who developed GPDs and patients with other abnormalities in long-term electroencephalographic monitoring. A retrospective study was performed by analyzing the medical records of 112 patients over 18 years who developed GPDs during long-term electroencephalographic monitoring (12‒16 hours of monitoring) in the intensive care unit of a general hospital, compared with a group that had only nonspecific abnormalities in the monitoring. Age and cardiorespiratory arrest (CA) were risk factors for death - OR 1.04 (95% CI 1,02 - 1,07) and p<0.001; OR 3.00 (95% CI 1,01 - 8,92) and p=0.046, respectively. It was not possible to evaluate if GPDs alone were associated with an unfavorable outcome or would be a bias for the development of CA in these patients. However, of the six isolated GPDs cases, 2/3 evolved to death, showing a tendency to worse prognosis. A significant difference (p=0.031) was observed for a worse outcome when comparing the group of 28 patients who presented GPD or CA with the other group which did not present any of these variables; of these 28 patients, 20 (71.4%) died. The presence of post-CA GPDs was associated with worse prognosis, but it was not clear whether these patterns are independent factors of an unfavorable evolution.

Abstract TMP22: Dynamic Worsening of Epileptiform Abnormalities Following Subarachnoid Hemorrhage is Associated With Poor 3-Month Outcomes

Objective: Worsening epileptiform abnormalities (EAs) and deteriorating background activity are common continuous electroencephalography (cEEG) patterns that predict subsequent clinical deterioration following subarachnoid hemorrhage (SAH). While worsening EAs and background deterioration both imply cortical dysfunction, we sought to clarify if these patterns have a different association with clinical outcomes. Methods: We enrolled patients with SAH undergoing &gt; 3 days of cEEG monitoring enrolled in a prospective outcome study with a modified Rankin Scale (mRS) assessment at 3 months. Worsening EAs included new or increasing burden of sporadic epileptiform discharges, lateralized rhythmic delta activity (LRDA), lateralized periodic discharges (LPD), or generalized periodic discharges (GPD). Background deterioration was defined as decreasing Alpha Delta Ratio (ADR), Relative Alpha Variability (RAV) or worsening focal slowing. We evaluated the association between these cEEG patterns and 3-month mRS &gt;3 and examined whether the influence on outcome was independent of delayed cerebral ischemia (DCI). Results: Of 59 patients meeting inclusion criteria (3-month mRS median 3 [IQR 1-5]), worsening EAs developed in 23 (39%) and new background deterioration in 24 (41%), whereas 24 patients (41%) developed neither finding and 12 (20%) developed both. Patients with worsening EAs were more likely to have a poor 3-month mRS compared to those without worsening EAs (OR 6.44; 95%CI 1.99-20.9; p=0.001). Developing new background deterioration was not significantly associated with poor 3-month outcome (OR 1.56, 95%CI 0.53-4.59; p=0.42). There was no additive effect on poor outcome of developing both findings. In a multivariate logistic regression, the effect of worsening EAs on 3-month mRS was independent of DCI. Interpretation: While both worsening EAs and new background deterioration have previously been associated with DCI, only worsening EAs influences poor long-term outcome. Further investigation may clarify if distinct mechanisms underlie these differences.

Transition Dynamics of Generalized Periodic Discharges Observed in EEG Waveforms

Generalized periodic discharges (GPD) are generalized waveforms that recur with a relatively uniform morphology and duration observed in EEG recordings of many types of metabolic encephalopathy, which are often referred to as epileptiform. In this paper, we try to link these spatiotemporal electrocortical activities and significant attributes of cortex based on Liley’s mean field model, and seek possible generation mechanisms of GPD rhythms from several factors. To these ends, the dynamical properties of simulated EEG consistent with neurophysiological features of human cortex are investigated, among which GPD patterns are our focus. Firstly, with different value sets of model parameters, we reproduce some typical simulation waveforms which are analogous to mammalian normal or abnormal brain activities detected by EEG. Or in other words, we put more emphasis on brain waveforms of GPD states, normal states, and low firing rate states in our numerical simulations, and mode transitions among different firing states are our main interests. Secondly, through analysis of maximum Lyapunov exponents and frequency spectrum, we give several mode transitions by varying synaptic connections between excitatory and inhibitory populations, which support the conjecture that selective changes of synaptic connections can trigger GPD states, such as in excitatory (AMPA receptors) and inhibitory neurotransmitters (GABA receptors). Thirdly, we stress the importance of time delay on neural population connections and find that they are free to transfer among different firing modes with appropriate time delays. Furthermore, considering the effects of external inputs to cerebral cortex, we verify that stimulation can lead to good controls on GPD patterns, including facilitation and elimination. Finally, we show that more dynamical rhythms can be produced when taking into account the cortico-cortical connections. These modeling results are expected to shed light into the pathophysiological mechanisms of GPD modes from a theoretical viewpoint.