The challenges of treating status epilepticus in rural Canada.

Though unified by challenges in the treatment of status epilepticus (SE), rural Canada is simultaneously massive and diverse, spanning the Pacific, Atlantic, and Arctic Oceans. According to the national statistical agency, the most rural jurisdiction in Canada is the Arctic territory of Nunavut. In particular, the Kivalliq region of Nunavut represents a unique epidemiologic SE space because any treatment beyond typical first-line lorazepam and second-line phenytoin by a non-neurologist locum tenens requires airborne evacuation over a thousand kilometers away to a single hospital with a single electroencephalographic (EEG) laboratory. This distinctive mode of healthcare delivery affords unique insights into the challenges of treating SE in rural Canada, such as lack of EEG infrastructure, a markedly high incidence of SE, the struggles of enduring cultural and socioeconomic trauma, and a relative lack of local epilepsy care as recommended by the World Health Organization. For example, despite empiric treatment and waiting over 2 days on average for EEG, 1 in 5 patients still had ongoing or possible electrographic seizures. At the same time, Kivalliq experiences routine dramatic changes in light-dark exposure each year to afford unique insights into circannual SE chronobiology in relation to the chief human zeitgeber of sunlight. This shows that challenges may also represent opportunities, such as for existing and emerging technologies to synergistically address enormous treatment gaps to improve SE care for the people of Kivalliq, while providing novel insights that may also help improve SE clinical care around the world.

Residual Seizure Rate of Intermittent Inpatient EEG Compared to a Continuous EEG Model.

BACKGROUND: Subclinical seizures are common in hospitalized patients and require electroencephalography (EEG) for detection and intervention. At our institution, continuous EEG (cEEG) is not available, but intermittent EEGs are subject to constant live interpretation. As part of quality improvement (QI), we sought to estimate the residual missed seizure rate at a typical quaternary Canadian health care center without cEEG. METHODS: We calculated residual risk percentages using the clinically validated 2HELPS2B score to risk-stratify EEGs before deriving a risk percentage using a MATLAB calculator which modeled the risk decay curve for each recording. We generated a range of estimated residual seizure rates depending on whether a pre-cEEG screening EEG was simulated, EEGs showing seizures were included, or repeat EEGs on the same patient were excluded. RESULTS: Over a 4-month QI period, 499 inpatient EEGs were scored as low (n = 125), medium (n = 123), and high (n = 251) seizure risk according to 2HELPS2B criteria. Median recording duration was 1:00:06 (interquartile range, IQR 30:40-2:21:10). The model with highest residual seizure rate included recordings with confirmed electrographic seizures (median 20.83%, IQR 20.6-26.6%), while the model with lowest residual seizure rate was in seizure-free recordings (median 10.59%, IQR 4%-20.6%). These rates were significantly higher than the benchmark 5% miss-rate threshold set by 2HELPS2B (p<0.0001). CONCLUSIONS: We estimate that intermittent inpatient EEG misses 2-4 times more subclinical seizures than the 2HELPS2B-determined acceptable 5% seizure miss-rate threshold for cEEG. Future research is needed to determine the impact of potentially missed seizures on clinical care.

Antiseizure medication use during pregnancy and neonatal growth outcomes: A systematic review and meta-analysis.

AIMS: We aimed to systematically synthesize the current published literature on neonatal growth outcomes associated with antiseizure medication (ASM) use during pregnancy. METHODS: We searched seven databases, from inception to 23 March 2022. We investigated small for gestational age (SGA) and low birth weight (LBW) as primary outcomes and birth weight, birth height, cephalization index and head circumference as secondary outcomes. The primary analysis included pregnant people exposed to any ASM compared with unexposed pregnant people. Subgroup analysis included ASM class analysis, within epilepsy group analysis and polytherapy compared to monotherapy. RESULTS: We screened 15 720 citations and included 65 studies in the review. Exposed pregnant people had a significantly increased risk of SGA relative risk (RR) 1.33 (95% CI 1.18 to 1.50, I2 74%), LBW RR 1.54 (95% CI 1.33 to 1.77, I2 67%), and decreased birth weight with a mean difference (MD) of -118.87 (95% CI -161.03 to -76.71, I2 42%) g. A non-significant risk change in birth height and head circumference was observed. In subgroup analysis, ASM polytherapy, within epilepsy and ASM class analysis were also associated with an increased risk of SGA and LBW. CONCLUSIONS: This meta-analysis demonstrates that pregnant people exposed to ASMs have a significantly increased risk of adverse fetal growth outcomes including SGA and LBW and decreased birth weight compared to unexposed pregnant people. Polytherapy was associated with higher risks compared to monotherapy. Additional studies are warranted on specific ASM risks.

Circannual incidence of seizure evacuations from the Canadian Arctic.

OBJECTIVES: Emerging evidence suggests that circadian rhythms affect seizure propensity in addition to, and possibly independent of, sleep-wake states. Subject to extreme seasonal changes in light and dark, the northerly Arctic can serve as a "natural experiment" to assess the real-life impact of environmental influences on seizure severity. Therefore, we evaluated the timing of seizure evacuations over 11.25 years in a well-defined region of the Canadian Arctic. METHODS: Retrospective review of EEG database and patient records at the single "bottleneck" hospital to which all patients from the Kivalliq Region in Nunavut, Canada are evacuated for seizure emergencies. We calculated the mean resultant length (MRL) of circular data for circannual analysis, and conducted Rayleigh's test to assess for a statistical departure from circular uniformity. RESULTS: Screening 40,392 EEGs, we found 117 medical evacuations from 99 distinct individuals from September 2009 to November 2020. Most evacuations occurred month-wise in May (19%); week-wise within a 7-day period in February (5%), June (5%), or November (5%); and day-wise within a 24-hour period in June (3%) or November (3%). Maximal MRL clustering occurred in April no matter if analyzed by day (0.16333, p = 0.04), week (0.16296, p = 0.04), or month (0.1736, p = 0.03). CONCLUSIONS: A relative circannual increase in seizure evacuations between the winter and summer solstices may be related to increasing sleep loss when day length grows. Fewer evacuations between the summer and winter solstices may be related to decreased daylight and "catching up" on sleep when night length grows. Additional factors likely also play a role in circannual variation of seizure evacuations in the Arctic, which warrants further research.

Position Statement on the Use of Medical Cannabis for the Treatment of Epilepsy in Canada.

In Canada, recreational use of cannabis was legalized in October 2018. This policy change along with recent publications evaluating the efficacy of cannabis for the medical treatment of epilepsy and media awareness about its use have increased the public interest about this agent. The Canadian League Against Epilepsy Medical Therapeutics Committee, along with a multidisciplinary group of experts and Canadian Epilepsy Alliance representatives, has developed a position statement about the use of medical cannabis for epilepsy. This article addresses the current Canadian legal framework, recent publications about its efficacy and safety profile, and our understanding of the clinical issues that should be considered when contemplating cannabis use for medical purposes.

Énoncé de position quant à l'utilisation du cannabis médical dans le traitement de l'épilepsie. L'utilisation du cannabis à des fins récréatives a été légalisée au Canada en octobre 2018. Parallèlement à ce changement de politique, de récentes publication visant à évaluer l'efficacité du cannabis dans le traitement de l'épilepsie, de même qu'une sensibilisation médiatique accrue en ce qui concerne son utilisation, ont eu pour effet d'augmenter l'intérêt du grand public à son égard. Le Comité médical thérapeutique de la Ligue canadienne contre l'épilepsie (LCCE), de concert avec un groupe multidisciplinaire d'experts et des représentants de l'Alliance canadienne de l'épilepsie, a ainsi élaboré un énoncé de position en ce qui regarde l'utilisation du cannabis médical dans le traitement de l'épilepsie. Cet article entend donc aborder le cadre légal qui prévaut actuellement au Canada et examiner de récentes publications s'étant penchées sur le profil sécuritaire et sur l'efficacité du cannabis. De plus, nous voulons apporter un éclairage au sujet des aspects cliniques dont il faudrait tenir compte au moment d'envisager l'utilisation du cannabis à des fins médicales.

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers.

[Formula: see text]-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM . Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

Sleep misperception in persons with epilepsy.

Being able to confidently ascertain the amount of sleep is critical to the clinical management of epilepsy. Sleep misperception is the phenomenon in which an individual underestimates the amount of time spent asleep. Little is known about sleep misperception in patients with epilepsy. We conducted retrospective chart reviews on individuals who self-identified as having epilepsy in a questionnaire database of patients undergoing polysomnography (PSG) at the Massachusetts General Hospital Sleep Laboratory. Our metric for sleep misperception was the difference between subjective and objective sleep latency (S-O SL) and subjective and objective total sleep time (S-O TST) with subjective values based on questionnaire and objective values based on PSG. We confirmed 64 patients with epilepsy. We then selected age- and sex-matched diagnostic PSG data for comparison from 50 patients with insomnia symptoms but no obstructive sleep apnea (OSA) and another 50 patients with OSA but no insomnia symptoms. In our cohort with epilepsy, the median SL overestimation was 20 min (p<0.05), and the median TST underestimation was 45 min (p<0.05). Sleep misperception was similar regardless of potential confounding factors such as categorical epilepsy refractoriness, cognitive impairment, or psychiatric comorbidity. Our findings suggest that sleep misperception occurs similarly in patients with epilepsy as in patients without epilepsy with insomnia. Our findings further support the potential clinical utility of objective PSG testing in patients with epilepsy, as this may not only identify occult OSA but also disclose sleep misperception.

High-definition transcranial direct current stimulation desynchronizes refractory status epilepticus.

Recently, we showed that high-definition transcranial direct current stimulation (hd-tDCS) can acutely reduce epileptic spike rates during and after stimulation in refractory status epilepticus (RSE), with a greater likelihood of patient discharge from the intensive care unit compared to historical controls. We investigate whether electroencephalographic (EEG) desynchronization during hd-tDCS can help account for observed anti-epileptic effects. Defining desynchronization as greater power in higher frequencies such as above 30 â€‹Hz ("gamma") and lesser power in frequency bands lower than 30 â€‹Hz, we analyzed 27 EEG sessions from 10 RSE patients who had received 20-minute session(s) of 2-milliamperes of transcranial direct current custom-targeted at the epileptic focus as previously determined by a clinical EEGer monitoring the EEG in real-time. During hd-tDCS, median relative power change over the EEG electrode chains in which power changes were maximal was +4.84%, -5.25%, -1.88%, -1.94%, and +4.99% for respective delta, theta, alpha, beta, and gamma frequency bands in the bipolar longitudinal montage (p â€‹= â€‹0.0001); and +4.13%, -5.44%, -1.81%, -3.23%, and +5.41% in the referential Laplacian montage (p â€‹= â€‹0.0012). After hd-tDCS, median relative power changes reversed over the EEG electrode chains in which power changes were maximal: -2.74%, +4.20%, +1.74%, +1.75%, and -4.68% for the respective delta, theta, alpha, beta, and gamma frequency bands in the bipolar longitudinal montage (p â€‹= â€‹0.0001); and +1.59%, +5.07%, +1.74%, +2.40%, and -5.12% in the referential Laplacian montage (p â€‹= â€‹0.0004). These findings are consistent with EEG desynchronization through theta-alpha-beta-gamma bands during hd-tDCS, helping account for the efficacy of hd-tDCS as an emerging novel anti-epileptic therapy against RSE.

Do Epilepsy Patients with Cognitive Impairment Have Alzheimer's Disease-like Brain Metabolism?

Although not classically considered together, there is emerging evidence that Alzheimer's disease (AD) and epilepsy share a number of features and that each disease predisposes patients to developing the other. Using machine learning, we have previously developed an automated fluorodeoxyglucose positron emission tomography (FDG-PET) reading program (i.e., MAD), and demonstrated good sensitivity (84%) and specificity (95%) for differentiating AD patients versus healthy controls. In this retrospective chart review study, we investigated if epilepsy patients with/without mild cognitive symptoms also show AD-like metabolic patterns determined by the MAD algorithm. Scans from a total of 20 patients with epilepsy were included in this study. Because AD diagnoses are made late in life, only patients aged ≥40 years were considered. For the cognitively impaired patients, four of six were identified as MAD+ (i.e., the FDG-PET image is classified as AD-like by the MAD algorithm), while none of the five cognitively normal patients was identified as MAD+ (χ2 = 8.148, p = 0.017). These results potentially suggest the usability of FDG-PET in prognosticating later dementia development in non-demented epilepsy patients, especially when combined with machine learning algorithms. A longitudinal follow-up study is warranted to assess the effectiveness of this approach.

Circannual seizure provocation as the day lengthens in the northern and southern hemispheres.

Circannual status epilepticus (SE) patterns in communities near Earth's poles best test the hypothesis that SE susceptibility varies with light exposure because these communities are routinely subject to large changes in annual light exposure, which may result in changes to daily sleep time. We compared northern hemispheric circannual SE occurrence in Kivalliq, Canada (latitude-62.8° N) to southern hemispheric Auckland, New Zealand (latitude-36.9° S). Instead of peaking at a similar calendar time, SE peaked at a similar solar time during the increasing daylight phase after each region's respective winter solstice. This demonstrates that cumulative effects of increasing light exposure can mediate SE susceptibility.

A Pilot Study of High-Definition Transcranial Direct Current Stimulation in Refractory Status Epilepticus: The SURESTEP Trial.

Refractory status epilepticus (RSE) is a life-threatening emergency with high mortality and poor functional outcomes in survivors. Treatment is typically limited to intravenous anesthetic infusions and multiple anti-seizure medications. While ongoing seizures can cause permanent neurological damage, medical therapies also pose severe and life-threatening side effects. We tested the feasibility of using high-definition transcranial direct current stimulation (hd-tDCS) in the treatment of RSE. We conducted 20-min hd-tDCS sessions at an outward field orientation, intensity of 2-mA, 4 + 1 channels, and customized for deployment over the electrographic maximum of epileptiform activity ("spikes") determined by real-time clinical EEG monitoring. There were no adverse events from 32 hd-tDCS sessions in 10 RSE patients. Over steady dosing states of infusions and medications in 29 included sessions, median spike rates/patient fell by 50% during hd-tDCS on both automated (p = 0.0069) and human (p = 0.0277) spike counting. Median spike rates for any given stimulation session also fell by 50% during hd-tDCS on automated spike counting (p = 0.0032). Immediately after hd-tDCS, median spike rates/patient remained down by 25% on human spike counting (p = 0.018). Compared to historical controls, hd-tDCS subjects were successfully discharged from the intensive care unit (ICU) 45.8% more often (p = 0.004). When controls were selected using propensity score matching, the discharge rate advantage improved to 55% (p = 0.002). Customized EEG electrode targeting of hd-tDCS is a safe and non-invasive method of hyperacutely reducing epileptiform activity in RSE. Compared to historical controls, there was evidence of a cumulative chronic clinical response with more hd-tDCS subjects discharged from ICU.

Development of Expert-Level Classification of Seizures and Rhythmic and Periodic Patterns During EEG Interpretation.

BACKGROUND AND OBJECTIVES: Seizures (SZs) and other SZ-like patterns of brain activity can harm the brain and contribute to in-hospital death, particularly when prolonged. However, experts qualified to interpret EEG data are scarce. Prior attempts to automate this task have been limited by small or inadequately labeled samples and have not convincingly demonstrated generalizable expert-level performance. There exists a critical unmet need for an automated method to classify SZs and other SZ-like events with expert-level reliability. This study was conducted to develop and validate a computer algorithm that matches the reliability and accuracy of experts in identifying SZs and SZ-like events, known as "ictal-interictal-injury continuum" (IIIC) patterns on EEG, including SZs, lateralized and generalized periodic discharges (LPD, GPD), and lateralized and generalized rhythmic delta activity (LRDA, GRDA), and in differentiating these patterns from non-IIIC patterns. METHODS: We used 6,095 scalp EEGs from 2,711 patients with and without IIIC events to train a deep neural network, SPaRCNet, to perform IIIC event classification. Independent training and test data sets were generated from 50,697 EEG segments, independently annotated by 20 fellowship-trained neurophysiologists. We assessed whether SPaRCNet performs at or above the sensitivity, specificity, precision, and calibration of fellowship-trained neurophysiologists for identifying IIIC events. Statistical performance was assessed by the calibration index and by the percentage of experts whose operating points were below the model's receiver operating characteristic curves (ROCs) and precision recall curves (PRCs) for the 6 pattern classes. RESULTS: SPaRCNet matches or exceeds most experts in classifying IIIC events based on both calibration and discrimination metrics. For SZ, LPD, GPD, LRDA, GRDA, and "other" classes, SPaRCNet exceeds the following percentages of 20 experts-ROC: 45%, 20%, 50%, 75%, 55%, and 40%; PRC: 50%, 35%, 50%, 90%, 70%, and 45%; and calibration: 95%, 100%, 95%, 100%, 100%, and 80%, respectively. DISCUSSION: SPaRCNet is the first algorithm to match expert performance in detecting SZs and other SZ-like events in a representative sample of EEGs. With further development, SPaRCNet may thus be a valuable tool for an expedited review of EEGs. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that among patients with epilepsy or critical illness undergoing EEG monitoring, SPaRCNet can differentiate (IIIC) patterns from non-IIIC events and expert neurophysiologists.

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.

A Primer on EEG Spectrograms.

SUMMARY: As continuous brain monitoring becomes a routine part of clinical care, continuous EEG has allowed better detection and characterization of nonconvulsive seizures, and patterns along the ictal-interictal continuum in critically ill patients. However, this increased workload has led many to turn to quantitative EEG whose central tool is the "spectrogram." Although in relatively wide use, many clinicians lack a detailed understanding of how spectrograms relate to the underlying "raw" EEG signal. This article provides an approachable set of first principles to help clinicians understand how spectrograms encode information about the raw EEG and how to interpret spectrograms to efficiently infer underlying EEG patterns.

Sleep-wake states change the interictal localization of candidate epileptic source generators.

STUDY OBJECTIVES: To compare estimated epileptic source localizations from 5 sleep-wake states (SWS): wakefulness (W), rapid eye movement sleep (REM), and non-REM 1-3. METHODS: Electrical source localization (sLORETA) of interictal spikes from different SWS on surface EEG from the epilepsy monitoring unit at spike peak and take-off, with results mapped to individual brain models for 75% of patients. Concordance was defined as source localization voxels shared between 2 and 5 SWS, and discordance as those unique to 1 SWS against 1-4 other SWS. RESULTS: 563 spikes from 16 prospectively recruited focal epilepsy patients across 161 day-nights. SWS exerted significant differences at spike peak but not take-off. Source localization size did not vary between SWS. REM localizations were smaller in multifocal than unifocal patients (28.8% vs. 54.4%, p = .0091). All five SWS contributed about 45% of their localizations to converge onto 17.0 ± 15.5% voxels. Against any one other SWS, REM was least concordant (54.4% vs. 66.9%, p = .0006) and most discordant (39.3% vs. 29.6%, p = .0008). REM also yielded the most unique localizations (20.0% vs. 8.6%, p = .0059). CONCLUSIONS: REM was best suited to identify candidate epileptic sources. sLORETA proposes a model in which an "omni-concordant core" of source localizations shared by all five SWS is surrounded by a "penumbra" of source localizations shared by some but not all SWS. Uniquely, REM spares this core to "move" source voxels from the penumbra to unique cortex not localized by other SWS. This may reflect differential intra-spike propagation in REM, which may account for its reported superior localizing abilities.

Status epilepticus in the Canadian Arctic: A public health imperative hidden in plain sight.

OBJECTIVE: The World Health Organization, International League Against Epilepsy (ILAE), and International Bureau for Epilepsy have called epilepsy a public health imperative, with appropriate emphasis on low-to-middle-income countries (LMIC). Although Canada is a high-income country (HIC), income is not distributed uniformly. Furthermore, epilepsy data from the national statistical agency explicitly overlook the Arctic by excluding these territories. A common neurologic emergency, status epilepticus (SE) is a life-threatening manifestation of epilepsy that demands prompt treatment to avoid death and long-term sequelae. Therefore, we examined the rate of SE in a well-defined Canadian Arctic region. METHODS: This study takes epidemiologic advantage of the Kivalliq Region's geographical isolation, which is accessible only by air. All SE patients requiring emergency care are consistently flown 1200-1900 kilometers to a single designated hospital in a distinct southern part of Canada for further management and electroencephalography (EEG). We conducted a retrospective database and chart review at this "bottleneck" hospital to identify patients with seizure(s) severe enough to justify emergency airborne medical evacuation over a 11.25-year period from 2009 to 2020. RESULTS: We screened 40 392 EEGs to yield 117 distinct medical evacuations for "operational SE" from 99 patients to derive estimated SE incidences of 99.9 evacuations per 100 000/year and 84.5 patients per 100 000/year. The average time from seizure onset to EEG was 3.2 days. Only 16.2% of SE patients had known epilepsy. For "confirmed SE" cases meeting ILAE criteria, or cases with persistently epileptiform EEG despite days of empiric treatment, estimated incidence was 77.7 evacuations per 100 000/year and 64.9 patients per 100 000/year. SIGNIFICANCE: High SE and epilepsy rates in the Canadian Arctic are consistent with LMIC rather than HIC. Our findings demonstrate the paradox of LMIC-equivalent epilepsy populations camouflaged within HIC. Our findings also highlight the long-standing plight of these under-served and overlooked populations hidden in plain sight.

Quantitative burst suppression on serial intermittent EEG in refractory status epilepticus.

OBJECTIVES: In refractory status epilepticus (RSE), the optimal degree of suppression (EEG burst suppression or merely suppressing seizures) remains unknown. Many centers lacking continuous EEG must default to serial intermittent recordings where uncertainty from lack of data may prompt more aggressive suppression. In this study, we sought to determine whether the quantitative burst suppression ratio (QBSR) from serial intermittent EEG recording is associated with RSE patient outcome. METHODS: We screened the EEG database to identify non-anoxic adult RSE patients for EEG and chart review. QBSR was calculated per 10-second EEG epoch as the percentage of time during which EEG amplitude was <3 µV. Patients who survived 1-3 months after discharge from ICU and hospital comprised the favorable group. Further to initial unadjusted univariate analysis of all pooled QBSR, we conducted multivariate analyses to account for individual patient confounders ("per-capita analysis"), uneven number of EEG recordings ("per-session analysis"), and uneven number of epochs ("per-epoch analysis"). We analyzed gender, anesthetic number, and adjusted status epilepticus severity score (aSTESS) as confounders. RESULTS: In 135,765 QBSR values over 160 EEG recordings (median 2.17 h every ≥24 h) from 17 patients on Propofol, Midazolam, and/or Ketamine, QBSR was deeper in the favorable group (p < 0.001) on initial unadjusted analysis. However, on adjusted multivariate analysis, there was consistently no association between QBSR and outcome. Higher aSTESS consistently associated with unfavorable outcome on per-capita (p = 0.033), per-session (p = 0.048) and per-epoch (p < 0.001) analyses. Greater maximal number of non-barbiturate anesthetic associated with favorable outcome on per-epoch analysis (p < 0.001). CONCLUSIONS: There was no association between depth of EEG suppression using non-barbiturate anesthetic and RSE patient outcome based on QBSR from serial intermittent EEG. A per-epoch association between non-barbiturate anesthetic and favorable outcome suggests an effect from non-suppressive time-varying EEG content. SIGNIFICANCE: Targeting and following deeper burst suppression through non-barbiturate anesthetics on serial intermittent EEG monitoring of RSE is of limited utility.

Can REM Sleep Localize the Epileptogenic Zone? A Systematic Review and Analysis.

Epilepsy is a common and debilitating neurological disease. When medication cannot control seizures in up to 40% of cases, surgical resection of epileptogenic tissue is a clinically and cost- effective therapy to achieve seizure freedom. To simultaneously resect minimal yet sufficient cortex, exquisite localization of the epileptogenic zone (EZ) is crucial. However, localization is not straightforward, given relative difficulty of capturing seizures, constraints of the inverse problem in source localization, and possible disparate locations of symptomatogenic vs. epileptogenic regions. Thus, attention has been paid to which state of vigilance best localizes the EZ, in the hopes that one or another sleep-wake state may hold the key to improved accuracy of localization. Studies investigating this topic have employed diverse methodologies and produced diverse results. Nonetheless, rapid eye movement sleep (REM) has emerged as a promising sleep-wake state, as epileptic phenomena captured in REM may spatially correspond more closely to the EZ. Cortical neuronal asynchrony in REM may spatially constrain epileptic phenomena to reduce propagation away from the source generator, rendering them of high localizing value. However, some recent work demonstrates best localization in sleep-wake states other than REM, and there are reports of REM providing clearly false localization. Moreover, synchronistic properties and basic mechanisms of human REM remain to be fully characterized. Amidst these uncertainties, there is an urgent need for recording and analytical techniques to improve accuracy of localization. Here we present a systematic review and quantitative analysis of pertinent literature on whether and how REM may help localize epileptogenic foci. To help streamline and accelerate future work on the intriguing anti-epileptic properties of REM, we also introduce a simple, conceptually clear set-theoretic framework to conveniently and rigorously describe the spatial properties of epileptic phenomena in the brain.

Critically ill benign EEG variants: Is there such a thing?

Despite growing use of critical care electroencephalography (ccEEG) to detect seizures and status epilepticus in the intensive care unit (ICU), integrating ccEEG findings with traditionally described benign EEG variants (BEVs) is a relatively new concept. BEV-like waveforms are now increasingly encountered in the ICU, and have also been explicitly included in proposed definitions of brief potentially ictal rhythmic discharges (BIRDs) in the ICU, bringing to the fore the question of if and which EEG patterns in critically ill patients can be safely deemed "benign". Though well-characterized as benign in healthy outpatients at low pre-test risk for neurologic disease, the significance of BEVs in the ICU remains largely unknown. Simultaneously, there has been mounting evidence to suggest that certain BEVs can arise from heterogeneous intracranial sources, including some pathologic generators. We conducted an extensive literature review on all known BEVs to assess what is known of BEVs in the ICU. Here we discuss critically ill BEVs and how to interpret them.