Development of a stereo-EEG based seizure matching system for clinical decision making in epilepsy surgery.

Objective.The proportion of patients becoming seizure-free after epilepsy surgery has stagnated. Large multi-center stereo-electroencephalography (SEEG) datasets can allow comparing new patients to past similar cases and making clinical decisions with the knowledge of how cases were treated in the past. However, the complexity of these evaluations makes the manual search for similar patients impractical. We aim to develop an automated system that electrographically and anatomically matches seizures to those in a database. Additionally, since features that define seizure similarity are unknown, we evaluate the agreement and features among experts in classifying similarity.Approach.We utilized 320 SEEG seizures from 95 consecutive patients who underwent epilepsy surgery. Eight international experts evaluated seizure-pair similarity using a four-level similarity score. As our primary outcome, we developed and validated an automated seizure matching system by employing patient data marked by independent experts. Secondary outcomes included the inter-rater agreement (IRA) and features for classifying seizure similarity.Main results.The seizure matching system achieved a median area-under-the-curve of 0.76 (interquartile range, 0.1), indicating its feasibility. Six distinct seizure similarity features were identified and proved effective: onset region, onset pattern, propagation region, duration, extent of spread, and propagation speed. Among these features, the onset region showed the strongest correlation with expert scores (Spearman's rho = 0.75,p< 0.001). Additionally, the moderate IRA confirmed the practicality of our approach with an agreement of 73.9% (7%), and Gwet's kappa of 0.45 (0.16). Further, the interoperability of the system was validated on seizures from five centers.Significance.We demonstrated the feasibility and validity of a SEEG seizure matching system across patients, effectively mirroring the expertise of epileptologists. This novel system can identify patients with seizures similar to that of a patient being evaluated, thus optimizing the treatment plan by considering the results of treating similar patients in the past, potentially improving surgery outcome.

Prognostic value of the 5-SENSE Score to predict focality of the seizure-onset zone as assessed by stereoelectroencephalography: a prospective international multicentre validation study.

Introduction: Epilepsy surgery is the only curative treatment for patients with drug-resistant focal epilepsy. Stereoelectroencephalography (SEEG) is the gold standard to delineate the seizure-onset zone (SOZ). However, up to 40% of patients are subsequently not operated as no focal non-eloquent SOZ can be identified. The 5-SENSE Score is a 5-point score to predict whether a focal SOZ is likely to be identified by SEEG. This study aims to validate the 5-SENSE Score, improve score performance by incorporating auxiliary diagnostic methods and evaluate its concordance with expert decisions. Methods and analysis: Non-interventional, observational, multicentre, prospective study including 200 patients with drug-resistant epilepsy aged ≥15 years undergoing SEEG for identification of a focal SOZ and 200 controls at 22 epilepsy surgery centres worldwide. The primary objective is to assess the diagnostic accuracy and generalisability of the 5-SENSE in predicting focality in SEEG in a prospective cohort. Secondary objectives are to optimise score performance by incorporating auxiliary diagnostic methods and to analyse concordance of the 5-SENSE Score with the expert decisions made in the multidisciplinary team discussion. Ethics and dissemination: Prospective multicentre validation of the 5-SENSE score may lead to its implementation into clinical practice to assist clinicians in the difficult decision of whether to proceed with implantation. This study will be conducted in accordance with the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (2014). We plan to publish the study results in a peer-reviewed full-length original article and present its findings at scientific conferences. Trial registration number: NCT06138808.

Centromedian region thalamic responsive neurostimulation mitigates idiopathic generalized and multifocal epilepsy with focal to bilateral tonic-clonic seizures.

OBJECTIVE: Although >30% of epilepsy patients have drug-resistant epilepsy (DRE), typically those with generalized or multifocal disease have not traditionally been considered surgical candidates. Responsive neurostimulation (RNS) of the centromedian (CM) region of the thalamus now appears to be a promising therapeutic option for this patient population. We present outcomes following CM RNS for 13 patients with idiopathic generalized epilepsy (IGE) and eight with multifocal onsets that rapidly generalize to bilateral tonic-clonic (focal to bilateral tonic-clonic [FBTC]) seizures. METHODS: A retrospective review of all patients undergoing bilateral CM RNS by the senior author through July 2022 were reviewed. Electrodes were localized and volumes of tissue activation were modeled in Lead-DBS. Changes in patient seizure frequency were extracted from electronic medical records. RESULTS: Twenty-one patients with DRE underwent bilateral CM RNS implantation. For 17 patients with at least 1 year of postimplantation follow-up, average seizure reduction from preoperative baseline was 82.6% (SD = 19.0%, median = 91.7%), with 18% of patients Engel class 1, 29% Engel class 2, 53% Engel class 3, and 0% Engel class 4. There was a trend for average seizure reduction to be greater for patients with nonlesional FBTC seizures than for other patients. For patients achieving at least Engel class 3 outcome, median time to worthwhile seizure reduction was 203.5 days (interquartile range = 110.5-343.75 days). Patients with IGE with myoclonic seizures had a significantly shorter time to worthwhile seizure reduction than other patients. The surgical targeting strategy evolved after the first four subjects to achieve greater anatomic accuracy. SIGNIFICANCE: Patients with both primary and rapidly generalized epilepsy who underwent CM RNS experienced substantial seizure relief. Subsets of these patient populations may particularly benefit from CM RNS. The refinement of lead targeting, tuning of RNS system parameters, and patient selection are ongoing areas of investigation.

Specific afterdischarge properties can enhance the clinical utility of electrical stimulation mapping during intracranial monitoring.

OBJECTIVE: Extraoperative electrical cortical stimulation (ECS) facilitates defining the seizure onset zone (SOZ) and eloquent cortex. The clinical relevance of stimulation-induced afterdischarges (ADs) is not well defined. METHODS: Fifty-five patients who underwent intracranial electroencephalogram evaluations with ECS were retrospectively identified. ADs were identified in these recordings and categorized by pattern, location, and association with stimulation-induced seizures. RESULTS: ADs were generated in 1774/9285 (19%) trials. Rhythmic spikes and irregular ADs within the stimulated bipolar contact pair were predictive of location within the SOZ compared to non-epileptogenic/non-irritative cortex (rhythmic spikes OR 2.24, p = 0.0098; irregular OR 1.39; p = 0.013). ADs immediately preceding stimulated seizures occurred at lower stimulation intensity thresholds compared to other stimulations (mean 2.94 ± 0.28 mA vs. 4.16 ± 0.05 mA respectively; p = 0.0068). CONCLUSIONS: Changes in AD properties can provide clinically relevant data in extraoperative stimulation mapping. SIGNIFICANCE: Although not exclusive to the SOZ, the generation of rhythmic spikes may suggest that a stimulation location is within the SOZ, while decreased stimulation intensity thresholds eliciting ADs may alert clinicians to a heightened probability of seizure generation with subsequent stimulation.

Hippocampal barques and their manifestation as 14&6 Hz positive spikes during sleep.

OBJECTIVE: This study investigates variations in hippocampal barque occurrence during sleep and compares findings to respective variations of their scalp manifestation as 14&6/sec positive spikes. METHODS: From 11 epilepsy patients, 12 non-epileptogenic hippocampi with barques were identified for this study. Using the first seizure-free whole-night sleep stereo-encephalography (sEEG) recording, we performed sleep staging and measured the occurrence of barques and 14&6/sec positive spikes variants. RESULTS: Hippocampal barques (total count: 9,183; mean count per record: 765.2 ± 251.2) occurred predominantly during non-rapid eye movement (NREM) II sleep (total: 5,744; mean: 478.6 ± 176.1; 62.2 ± 6.0%) and slow-wave sleep (SWS) (total: 2,950; mean: 245.83 ± 92.9; 32.0 ± 6.2%), with rare to occasional occurrence in NREM I (total: 85; mean: 7.0 ± 2.8; 0.9 ± 0.4%), rapid eye movement (REM) (total: 153; mean: 12.75 ± 4.0; 1.7 ± 0.6) and wakefulness (total: 251; mean: 20.9 ± 6.3; 2.9 ± 0.9%). Barque rate increased during SWS (mean: 2.7 ± 1.0 per min) compared to NREM II (2.2 ± 1.0 per min) and other states (wakefulness: 0.1 ± 0.0 per min; NREM I: 0.3 ± 0.1 per min; REM: 0.1 ± 0.0 per min). The 14&6/sec positive spikes variant (total count: 2,406; mean: 343.7 ± 106.7) was present in NREM II (total: 2,059; mean: 249.1 ± 100.2, 84.9 ± 3.6%) and SWS (total: 347; mean: 49.5 ± 12.8, 15.0 ± 3.6%) stages, and absent from the rest of sleep and wakefulness. While all 14&6/sec positive spikes correlated with barques, only 44.7 ± 6.1% of barques manifested as 14&6/sec positive spikes. CONCLUSIONS: Hippocampal barques are predominant in NREM II and SWS, and tend to increase their presence during SWS. Their scalp manifestation as 14&6/sec positive spikes is confounded by wakefulness, REM and NREM I stages, and "masked" by the co-occurrence of NREM II and SWS slow waves, and overlapping reactive micro-arousal elements. SIGNIFICANCE: Our study highlighted the overnight profile of hippocampal barques, in relation to the respective profile of their scalp manifestation, the 14&6/sec positive spikes variant.

Barques are generated in posterior hippocampus and phase reverse over lateral posterior hippocampal surface.

OBJECTIVE: To investigate whether barques can be localized across the hippocampal longitudinal axis with sufficient specificity. METHODS: We identified 51 focal epilepsy patients implanted with a minimum of two electrodes - unilateral anterior and posterior - in either hippocampus. We used visual inspection of the intracranial electroencephalogram (iEEG) and 3D brain volume spectrum-based statistical parametric mapping (SPM) to localize barques. RESULTS: In 18/51 patients (35.29%), barques were identified in 22/70 (31.42%) hippocampi. In all hippocampi (100%), barques were present in the posterior hippocampus, while 9 (40.90%) showed concurrent non-independent barque activity anteriorly (P < 0.0001). Statistical parametric mapping confirmed the posterior barque localization, with significant differences in t-values (t(27) = 8.08, P < 0.0001) and z-scores (t(24) = 6.85, P < 0.0001) between anterior and posterior hippocampal barque activity. Posterior lateral extrahippocampal contacts demonstrated phase reversals of positive polarity during barque activity (P = 0.0092, compared to anterior extrahippocampal contacts). CONCLUSIONS: This study highlights the posterior hippocampal predominance of barques. Our findings are concordant with the posterior distribution of the scalp manifestation of barques as "14&6/sec positive spikes". The posterio-lateral hippocampal barque phase reversal can explain the positive polarity of scalp 14&6/sec spikes. SIGNIFICANCE: Understanding the properties of barques is critical for the iEEG interpretation in epilepsy surgery evaluations that include the hippocampus.

Responsive neurostimulation of the thalamus improves seizure control in idiopathic generalised epilepsy: initial case series.

OBJECTIVES: Up to 40% of patients with idiopathic generalised epilepsy (IGE) are drug resistant and potentially could benefit from intracranial neuromodulation of the seizure circuit. We present outcomes following 2 years of thalamic-responsive neurostimulation for IGE. METHODS: Four patients with pharmacoresistant epilepsy underwent RNS System implantation in the bilateral centromedian (CM) nucleus region. Electrophysiological data were extracted from the clinical patient data management system and analysed using a specialised platform (BRAINStim). Postoperative visualisation of electrode locations was performed using Lead-DBS. Seizure outcomes were reported using the Engel scale. RESULTS: Patients experienced a 75%-99% reduction in seizure frequency with decreased seizure duration and severity (Engel class IB, IC, IIA and IIIA), as well as significant improvements in quality of life. Outcomes were durable through at least 2 years of therapy. Detection accuracy for all patients overall decreased over successive programming epochs from a mean of 96.5% to 88.3%. Most electrodes used to deliver stimulation were located in the CM (7/10) followed by the posterior dorsal ventral lateral (2/2), posterior ventral posterior lateral (3/4) and posterior ventral ventral lateral (2/3). In all patients, stimulation varied from 0.2 to 2.0 mA and amplitude only increased over successive epochs. The raw percentage of intracranial electroencephalography recordings with stimulations delivered to electrographic seizures was 24.8%, 1.2%, 7.6% and 8.8%. CONCLUSION: Closed-loop stimulation of the CM region may provide significant improvement in seizure control and quality of life for patients with drug-resistant IGE. Optimal detection and stimulation locations and parameters remain an active area of investigation for accelerating and fine-tuning clinical responses.

Development and Validation of the 5-SENSE Score to Predict Focality of the Seizure-Onset Zone as Assessed by Stereoelectroencephalography.

Importance: Stereoelectroencephalography (SEEG) has become the criterion standard in case of inconclusive noninvasive presurgical epilepsy workup. However, up to 40% of patients are subsequently not offered surgery because the seizure-onset zone is less focal than expected or cannot be identified. Objective: To predict focality of the seizure-onset zone in SEEG, the 5-point 5-SENSE score was developed and validated. Design, Setting, and Participants: This was a monocentric cohort study for score development followed by multicenter validation with patient selection intervals between February 2002 to October 2018 and May 2002 to December 2019. The minimum follow-up period was 1 year. Patients with drug-resistant epilepsy undergoing SEEG at the Montreal Neurological Institute were analyzed to identify a focal seizure-onset zone. Selection criteria were 2 or more seizures in electroencephalography and availability of complete neuropsychological and neuroimaging data sets. For validation, patients from 9 epilepsy centers meeting these criteria were included. Analysis took place between May and July 2021. Main Outcomes and Measures: Based on SEEG, patients were grouped as focal and nonfocal seizure-onset zone. Demographic, clinical, electroencephalography, neuroimaging, and neuropsychology data were analyzed, and a multiple logistic regression model for developing a score to predict SEEG focality was created and validated in an independent sample. Results: A total of 128 patients (57 women [44.5%]; median [range] age, 31 [13-58] years) were analyzed for score development and 207 patients (97 women [46.9%]; median [range] age, 32 [16-70] years) were analyzed for validation. The score comprised the following 5 predictive variables: focal lesion on structural magnetic resonance imaging, absence of bilateral independent spikes in scalp electroencephalography, localizing neuropsychological deficit, strongly localizing semiology, and regional ictal scalp electroencephalography onset. The 5-SENSE score had an optimal mean (SD) probability cutoff for identifying a focal seizure-onset zone of 37.6 (3.5). Area under the curve, specificity, and sensitivity were 0.83, 76.3% (95% CI, 66.7-85.8), and 83.3% (95% CI, 72.30-94.1), respectively. Validation showed 76.0% (95% CI, 67.5-84.0) specificity and 52.3% (95% CI, 43.0-61.5) sensitivity. Conclusions and Relevance: High specificity in score development and validation confirms that the 5-SENSE score predicts patients where SEEG is unlikely to identify a focal seizure-onset zone. It is a simple and useful tool for assisting clinicians to reduce unnecessary invasive diagnostic burden on patients and overutilization of limited health care resources.

Intracranial monitoring contributes to seizure freedom for temporal lobectomy patients with nonconcordant preoperative data.

OBJECTIVE: The question of whether a patient with presumed temporal lobe seizures should proceed directly to temporal lobectomy surgery versus undergo intracranial monitoring arises commonly. We evaluate the effect of intracranial monitoring on seizure outcome in a retrospective cohort of consecutive subjects who specifically underwent an anterior temporal lobectomy (ATL) for refractory temporal lobe epilepsy (TLE). METHODS: We performed a retrospective analysis of 85 patients with focal refractory TLE who underwent ATL following: (a) intracranial monitoring via craniotomy and subdural/depth electrodes (SDE/DE), (b) intracranial monitoring via stereotactic electroencephalography (sEEG), or (c) no intracranial monitoring (direct ATL-dATL). For each subject, the presurgical primary hypothesis for epileptogenic zone localization was characterized as unilateral TLE, unilateral TLE plus (TLE+), or TLE with bilateral/poor lateralization. RESULTS: At one-year and most recent follow-up, Engel Class I and combined I/II outcomes did not differ significantly between the groups. Outcomes were better in the dATL group compared to the intracranial monitoring groups for lesional cases but were similar in nonlesional cases. Those requiring intracranial monitoring for a hypothesis of TLE+had similar outcomes with either intracranial monitoring approach. sEEG was the only approach used in patients with bilateral or poorly lateralized TLE, resulting in 77.8% of patients seizure-free at last follow-up. Importantly, for 85% of patients undergoing SEEG, recommendation for ATL resulted from modifying the primary hypothesis based on iEEG data. SIGNIFICANCE: Our study highlights the value of intracranial monitoring in equalizing seizure outcomes in difficult-to-treat TLE patients undergoing ATL.

Hippocampal spindles and barques are normal intracranial electroencephalographic entities.

OBJECTIVE: To assess whether hippocampal spindles and barques are markers of epileptogenicity. METHODS: Focal epilepsy patients that underwent stereo-electroencephalography implantation with at least one electrode in their hippocampus were selected (n = 75). The occurrence of spindles and barques in the hippocampus was evaluated in each patient. We created pairs of pathologic and pathology-free groups according to two sets of criteria: 1. Non-invasive diagnostic criteria (patients grouped according to focal epilepsy classification). 2. Intracranial neurophysiological criteria (patient's hippocampi grouped according to their seizure onset involvement). RESULTS: Hippocampal spindles and barques appear equally often in both pathologic and pathology-free groups, both for non-invasive (Pspindles = 0.73; Pbarques = 0.46) and intracranial criteria (Pspindles = 0.08; Pbarques = 0.26). In Engel Class I patients, spindles occurred with similar incidence both within the non-invasive (P = 0.67) and the intracranial criteria group (P = 0.20). Barques were significantly more frequent in extra-temporal lobe epilepsy defined by either non-invasive (P = 0.01) or intracranial (P = 0.01) criteria. CONCLUSIONS: Both spindles and barques are normal entities of the hippocampal intracranial electroencephalogram. The presence of barques may also signify lack of epileptogenic properties in the hippocampus. SIGNIFICANCE: Understanding that hippocampal spindles and barques do not reflect epileptogenicity is critical for correct interpretation of epilepsy surgery evaluations and appropriate surgical treatment selection.

Expert-Level Intracranial Electroencephalogram Ictal Pattern Detection by a Deep Learning Neural Network.

Background: Decision-making in epilepsy surgery is strongly connected to the interpretation of the intracranial EEG (iEEG). Although deep learning approaches have demonstrated efficiency in processing extracranial EEG, few studies have addressed iEEG seizure detection, in part due to the small number of seizures per patient typically available from intracranial investigations. This study aims to evaluate the efficiency of deep learning methodology in detecting iEEG seizures using a large dataset of ictal patterns collected from epilepsy patients implanted with a responsive neurostimulation system (RNS). Methods: Five thousand two hundred and twenty-six ictal events were collected from 22 patients implanted with RNS. A convolutional neural network (CNN) architecture was created to provide personalized seizure annotations for each patient. Accuracy of seizure identification was tested in two scenarios: patients with seizures occurring following a period of chronic recording (scenario 1) and patients with seizures occurring immediately following implantation (scenario 2). The accuracy of the CNN in identifying RNS-recorded iEEG ictal patterns was evaluated against human neurophysiology expertise. Statistical performance was assessed via the area-under-precision-recall curve (AUPRC). Results: In scenario 1, the CNN achieved a maximum mean binary classification AUPRC of 0.84 ± 0.19 (95%CI, 0.72-0.93) and mean regression accuracy of 6.3 ± 1.0 s (95%CI, 4.3-8.5 s) at 30 seed samples. In scenario 2, maximum mean AUPRC was 0.80 ± 0.19 (95%CI, 0.68-0.91) and mean regression accuracy was 6.3 ± 0.9 s (95%CI, 4.8-8.3 s) at 20 seed samples. We obtained near-maximum accuracies at seed size of 10 in both scenarios. CNN classification failures can be explained by ictal electro-decrements, brief seizures, single-channel ictal patterns, highly concentrated interictal activity, changes in the sleep-wake cycle, and progressive modulation of electrographic ictal features. Conclusions: We developed a deep learning neural network that performs personalized detection of RNS-derived ictal patterns with expert-level accuracy. These results suggest the potential for automated techniques to significantly improve the management of closed-loop brain stimulation, including during the initial period of recording when the device is otherwise naïve to a given patient's seizures.

Quantifying a frequency modulation response biomarker in responsive neurostimulation.

Objective.Responsive neurostimulation (RNS) is an effective treatment for controlling seizures in patients with drug-resistant focal epilepsy who are not suitable candidates for resection surgery. A lack of tools for detecting and characterizing potential response biomarkers, however, contributes to a limited understanding of mechanisms by which RNS improves seizure control. We developed a method to quantify ictal frequency modulation, previously identified as a biomarker of clinical responsiveness to RNS.Approach.Frequency modulation is characterized by shifts in power across spectral bands during ictal events, over several months of neurostimulation. This effect was quantified by partitioning each seizure pattern into segments with distinct spectral content and measuring the extent of change from the baseline distribution of spectral content using the squared earth mover's distance.Main results.We analyzed intracranial electroencephalography data from 13 patients who received RNS therapy, six of whom exhibited frequency modulation on expert evaluation. Patients in the frequency modulation group had, on average, significantly larger and more sustained changes in their squared earth mover's distances (mean = 13.97 × 10-3± 1.197 × 10-3). In contrast, those patients without expert-identified frequency modulation exhibited statistically insignificant or negligible distances (mean = 4.994 × 10-3± 0.732 × 10-3).Significance.This method is the first step towards a quantitative, feedback-driven system for systematically optimizing RNS stimulation parameters, with an ultimate goal of truly personalized closed-loop therapy for epilepsy.

Comparison of medial distal tibial angle in EOS imaging and weightbearing X-ray.

BACKGROUND: The medial distal tibial angle (MDTA) is used for measurement of ankle alignment. Standard to measure MDTA is weightbearing mortise view. EOS imaging becomes more popular for limb alignment analysis using low-dose radiation. As MDTA might vary in EOS, comparison between both radiographic techniques has been performed. METHODS: MDTA was compared between both techniques in 43 cases by defining the mechanical tibial axis in different ways (X-ray low, EOS low, EOS high). For each method MDTA, intra- and interobserver reliability has been compared. RESULTS: The correlation between the different methods were measured by ICC (intraclass coefficient) and were ICC 0.86 (X-ray low/EOS low), ICC 0.85 (X-ray low/EOS high) and ICC 0.97 (EOS low/EOS high). Intra- and interobserver reliability were in each case ICC > 0.95. CONCLUSION: ICC showed a substantial to excellent agreement between all methods. EOS is appropriate to determine MDTA and can be used for assessment of coronar deformities of the distal tibia.

Ictal Onset Signatures Predict Favorable Outcomes of Laser Thermal Ablation for Mesial Temporal Lobe Epilepsy.

Background: Laser interstitial thermal therapy (LiTT) has emerged as a minimally invasive option for surgical treatment of refractory epilepsy. However, LiTT of the mesial temporal (MT) structures is still inferior to anterior temporal lobectomy (ATL) in terms of postoperative outcome. In this pilot study, we identify intracranial EEG (iEEG) biomarkers that distinguish patients with favorable outcome from those with poor outcome after MT LiTT. Methods: We performed a retrospective review of 9 adult refractory epilepsy patients who underwent stereotactic electroencephalography (sEEG) followed by LiTT of MT structures. Their iEEG was retrospectively reviewed in both time and frequency domains. Results: In the time-domain, the presence of sustained 14-30 Hz in MT electrodes coupled with its absence from extra-MT electrodes at ictal onset was highly correlated with favorable outcomes, whereas the appearance of sustained 14-30 Hz or >30 Hz activity in extra-MT sites was negatively correlated to favorable outcomes. In the frequency domain, a declining spectral phase, beginning at the high frequency range (>14 Hz) at ictal onset and following a smooth progressive decline toward lower frequencies as the seizure further evolved, was positively correlated with improved outcomes. On the contrary, low frequency (<14 Hz) patterns and "crescendo-decrescendo" patterns with an early increasing frequency component at ictal onset that reaches the high-beta and low gamma bands before decreasing smoothly, were both correlated with poor surgical outcomes. Conclusions: This pilot study demonstrates the first evidence that iEEG analysis can provide neurophysiological markers for successful MT LiTT and therefore we strongly advocate for systematic sEEG investigations before offering MT LiTT to TLE and MTLE patients.

Differential association of subtypes of epileptiform activity with outcome after cardiac arrest.

BACKGROUND: Epileptiform activity is common after cardiac arrest, although intensity of electroencephalographic (EEG) monitoring may affect detection rates. Prior work has grouped these patterns together as "malignant," without considering discrete subtypes. We describe the incidence of distinct patterns in the ictal-interictal spectrum at two centers and their association with outcomes. METHODS: We analyzed a retrospective cohort of comatose post-arrest patients admitted at two academic centers from January 2011 to October 2014. One center uses routine continuous EEG, the other acquires "spot" EEG at the treating physicians' discretion. We reviewed all available EEG data and classified epileptiform patterns. We abstracted antiepileptic drugs (AEDs) administrations from the electronic medical record. We compared apparent incidence of each pattern between centers, and compared outcomes (awakening from coma, survival to discharge, discharge modified Rankin Scale (mRS) 0-2) across EEG patterns and number of AEDs administered. RESULTS: We included 818 patients. Routine continuous EEG was associated with a higher apparent incidence of polyspike burst-suppression (25% vs 13% P < 0.001). Frequency of other epileptiform findings did not differ. Among patients with any epileptiform pattern, only 2/258 (1%, 95%CI 0-3%) were discharged with mRS 0-2, although 24/258 (9%, 95%CI 6-14%) awakened and 36/258 (14%, 95%CI 10-19%) survived. The proportions that awakened and survived decreased in a stepwise manner with progressively worse EEG patterns (range 38% to 2% and 32% to 7%, respectively). Among patients receiving ≥3 AEDs, only 5/80 (6%, 95%CI 2-14%) awakened and 1/80 (1%, 95%CI 0-7%) had a mRS 0-2. CONCLUSION: We found high rates of epileptiform EEG findings, regardless of intensity of EEG monitoring. The association of distinct ictal-interictal EEG findings with outcome was variable.

Features of Simultaneous Scalp and Intracranial EEG That Predict Localization of Ictal Onset Zone.

OBJECTIVE: To assess the utility of simultaneous scalp EEG in patients with focal epilepsy undergoing intracranial EEG evaluation after a detailed presurgical testing, including an inpatient scalp video EEG evaluation. METHODS: Patients who underwent simultaneous scalp and intracranial EEG (SSIEEG) monitoring were classified into group 1 or 2 depending on whether the seizure onset zone was delineated or not. Seizures were analyzed using the following 3 EEG features at the onset of seizures latency, location, and pattern. RESULTS: The criteria showed at least one of the following features when comparing SSIEEG: prolonged latency, absence of anatomical congruence, lack of concordance of EEG pattern in 11.11% (1/9) of the patients in group 1 and 75 % (3/4) of the patients in group 2. These 3 features were not present in any of the 5 patients who had Engel class I outcome compared with 1 of the 2 patients (50%) who had seizure recurrence after resective surgery. The mean latency of seizure onset in scalp EEG compared with intracranial EEG of patients in group 1 was 17.48 seconds (SD = 16.07) compared with 4.33 seconds (SD = 11.24) in group 2 ( P = .03). None of the seizures recorded in patients in group 1 had a discordant EEG pattern in SSIEEG. CONCLUSION: Concordance in EEG features like latency, location, and EEG pattern, at the onset of seizures in SSIEEG is associated with a favorable outcome after epilepsy surgery in patients with intractable focal epilepsy. SIGNIFICANCE: Simultaneous scalp EEG complements intracranial EEG evaluation even after a detailed inpatient scalp video EEG evaluation and could be part of standard intracranial EEG studies in patients with intractable focal epilepsy.

Neurostimulant use is associated with improved survival in comatose patients after cardiac arrest regardless of electroencephalographic substrate.

AIM: Identify EEG patterns that predict or preclude favorable response in comatose post-arrest patients receiving neurostimulants. METHODS: We examined a retrospective cohort of consecutive electroencephalography (EEG)-monitored comatose post-arrest patients. We classified the last day of EEG recording before neurostimulant administration based on continuity (continuous/discontinuous), reactivity (yes/no) and malignant patterns (periodic discharges, suppression burst, myoclonic status epilepticus or seizures; yes/no). In subjects who did not receive neurostimulants, we examined the last 24h of available recording. For our primary analysis, we used logistic regression to identify EEG predictors of favorable response to treatment (awakening). RESULTS: In 585 subjects, mean (SD) age was 57 (17) years and 227 (39%) were female. Forty-seven patients (8%) received a neurostimulant. Neurostimulant administration independently predicted improved survival to hospital discharge in the overall cohort (adjusted odds ratio (aOR) 4.00, 95% CI 1.68-9.52) although functionally favorable survival did not differ. No EEG characteristic predicted favorable response to neurostimulants. In each subgroup of unfavorable EEG characteristics, neurostimulants were associated with increased survival to hospital discharge (discontinuous background: 44% vs 7%, P=0.004; non-reactive background: 56% vs 6%, P<0.001; malignant patterns: 63% vs 5%, P<0.001). CONCLUSION: EEG patterns described as ominous after cardiac arrest did not preclude survival or awakening after neurostimulant administration. These data are limited by their observational nature and potential for selection bias, but suggest that EEG patterns alone should not affect consideration of neurostimulant use.

Does immune suppression during stress occur to promote physical performance?

Two adaptationist hypotheses have been proposed to explain why stress, particularly elevation of stress hormones (i.e. glucocorticoids), tends to suppress immune functions. One is that immune suppression represents efforts to minimize autoimmune responses to self-antigens released as organisms cope with stressors (i.e. the autoimmune-avoidance hypothesis). The other is that immune suppression occurs to promote a shunting of resources to life processes more conducive to survival of the stressor (i.e. the re-allocation hypothesis). Here in wild-caught house sparrows (Passer domesticus), we tested the second hypothesis, asking whether sustained elevation of baseline glucocorticoids, due to captivity, caused a greater rate of decline in immune functions than flight performance. A greater decline in immune functions than flight performance would support the re-allocation hypothesis. As in previous studies, we found that captivity tended to alter baseline corticosterone, suggesting that house sparrows experience captivity as a stressor. Captivity also affected several constitutive and induced innate immune metrics: bacterial (Escherichia coli) killing activity of blood and oxidative burst of leukocytes both changed in a manner consistent with immune disregulation. In contrast, breast muscle size and vertical flight (hovering) duration improved over captivity. Collectively, these changes provide indirect support for the re-allocation hypothesis, although within individuals, changes in immune and physical performance were unrelated.