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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.

This study was undertaken to determine the dose-response relation between epileptiform activity burden and outcomes in acutely ill patients.A single center retrospective analysis was made of 1,967 neurologic, medical, and surgical patients who underwent16 hours of continuous electroencephalography (EEG) between 2011 and 2017. We developed an artificial intelligence algorithm to annotate 11.02 terabytes of EEG and quantify epileptiform activity burden within 72 hours of recording. We evaluated burden (1) in the first 24 hours of recording, (2) in the 12-hours epoch with highest burden (peak burden), and (3) cumulatively through the first 72 hours of monitoring. Machine learning was applied to estimate the effect of epileptiform burden on outcome. Outcome measure was discharge modified Rankin Scale, dichotomized as good (0-4) versus poor (5-6).Peak epileptiform burden was independently associated with poor outcomes (p 0.0001). Other independent associations included age, Acute Physiology and Chronic Health Evaluation II score, seizure on presentation, and diagnosis of hypoxic-ischemic encephalopathy. Model calibration error was calculated across 3 strata based on the time interval between last EEG measurement (up to 72 hours of monitoring) and discharge: (1) 5 days between last measurement and discharge, 0.0941 (95% confidence interval [CI] = 0.0706-0.1191); 5 to 10 days between last measurement and discharge, 0.0946 (95% CI = 0.0631-0.1290);10 days between last measurement and discharge, 0.0998 (95% CI = 0.0698-0.1335). After adjusting for covariates, increase in peak epileptiform activity burden from 0 to 100% increased the probability of poor outcome by 35%.Automated measurement of peak epileptiform activity burden affords a convenient, consistent, and quantifiable target for future multicenter randomized trials investigating whether suppressing epileptiform activity improves outcomes. ANN NEUROL 2021;90:300-311.

No clear evidence‐based treatment paradigm currently exists for refractory and super‐refractory status epilepticus, which can result in significant mortality and morbidity. While patients are typically treated with antiepileptic drugs and anesthetics, neurosurgical neuromodulation techniques can also be considered. We present a novel case in which responsive neurostimulation was used to effectively treat a patient who had developed super‐refractory status epilepticus, later consistent with epilepsia partialis continua, that was refractory to antiepileptic drugs, immunomodulatory therapies, and transcranial magnetic stimulation. This case demonstrates how regional therapy provided by responsive neurostimulation can be effective in treating super‐refractory status epilepticus through neuromodulation of seizure networks.

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 ([Image: see text]): 95 [93, 98]%) and for most variation in experts' precision vs sensitivity characteristics ([Image: 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.

We sought to investigate electroencephalographers’ real-world behaviors and opinions concerning reading routine EEG (rEEG) with or without clinical information. An eight-question, anonymous, online survey targeted at electroencephalographers was disseminated on social media from the authors’ personal accounts and emailed to authors’ select colleagues. A total of 389 responses were included. Most respondents reported examining clinical information before describing rEEG findings. Nonetheless, only a minority of respondents believe that EEG analysis/description should be influenced by clinical information. We recommend reviewing clinical data only after an unbiased EEG read to prevent history bias and ensure generation of reliable electrodiagnostic information.

ObjectiveTo examine the relationship between scalp EEG biomarkers of hyperexcitability in Alzheimer disease (AD) and to determine how these electric biomarkers relate to the clinical expression of seizures in AD.MethodsIn this cross-sectional study, we performed 24-hour ambulatory scalp EEGs on 43 cognitively normal elderly healthy controls (HC), 41 participants with early-stage AD with no history or risk factors for epilepsy (AD-NoEp), and 15 participants with early-stage AD with late-onset epilepsy related to AD (AD-Ep). Two epileptologists blinded to diagnosis visually reviewed all EEGs and annotated all potential epileptiform abnormalities. A panel of 9 epileptologists blinded to diagnosis was then surveyed to generate a consensus interpretation of epileptiform abnormalities in each EEG.ResultsEpileptiform abnormalities were seen in 53% of AD-Ep, 22% of AD-NoEp, and 4.7% of HC. Specific features of epileptiform discharges, including high frequency, robust morphology, right temporal location, and occurrence during wakefulness and REM, were associated with clinical seizures in AD. Multiple EEG biomarkers concordantly demonstrated a pattern of left temporal lobe hyperexcitability in early stages of AD, whereas clinical seizures in AD were often associated with bitemporal hyperexcitability. Frequent small sharp spikes were specifically associated with epileptiform EEGs and thus identified as a potential biomarker of hyperexcitability in AD.ConclusionEpileptiform abnormalities are common in AD but not all equivalent. Specific features of epileptiform discharges are associated with clinical seizures in AD. Given the difficulty recognizing clinical seizures in AD, these EEG features could provide guidance on which patients with AD are at high risk for clinical seizures.

Background Uncertain validity of epilepsy diagnoses within health insurance claims and other large datasets have hindered efforts to study and monitor care at the population level. Objectives To develop and validate prediction models using longitudinal Medicare administrative data to identify patients with actual epilepsy among those with the diagnosis. Research design, subjects, measures We used linked electronic health records and Medicare administrative data including claims to predict epilepsy status. A neurologist reviewed electronic health record data to assess epilepsy status in a stratified random sample of Medicare beneficiaries aged 65+ years between January 2012 and December 2014. We then reconstructed the full sample using inverse probability sampling weights. We developed prediction models using longitudinal Medicare data, then in a separate sample evaluated the predictive performance of each model, for example, area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. Results Of 20,945 patients in the reconstructed sample, 2.1% had confirmed epilepsy. The best-performing prediction model to identify prevalent epilepsy required epilepsy diagnoses with multiple claims at least 60 days apart, and epilepsy-specific drug claims: AUROC=0.93 [95% confidence interval (CI), 0.90-0.96], and with an 80% diagnostic threshold, sensitivity=87.8% (95% CI, 80.4%-93.2%), specificity=98.4% (95% CI, 98.2%-98.5%). A similar model also performed well in predicting incident epilepsy (k=0.79; 95% CI, 0.66-0.92). Conclusions Prediction models using longitudinal Medicare data perform well in predicting incident and prevalent epilepsy status accurately.

Greenhouse gas emissions are a global problem facing the dairy/beef industry. Novel feed additives consisting of seaweeds and hemp containing bioactive compounds are theorized to reduce enteric methane emissions. In this study we aimed to investigate the metabolic profiles of brown, red and green seaweeds and hemp using gas chromatography and liquid chromatography mass spectrometry. We used targeted and untargeted approaches, quantifying known halomethanes and phenolics, as well as identifying potentially novel bioactive compounds with anti-methanogenic properties. The main findings were: (a) Asparagopsis taxiformis contained halomethanes, with high concentrations of bromoform (4200 µg/g DW), six volatile halocarbons were tentatively identified; (b) no halomethanes were detected in the other studied seaweeds nor in hemp; (c) high concentrations of lignans were measured in hemp; (d) a high numbers of sulfated phenolic acids and unidentified sulfuric acid-containing compounds were detected in all seaweeds; (e) flavonoid glucosides and glucuronides were mainly identified in hemp; and (f) the condensed tannin gallocatechin was tentatively identified in Fucus sp. Using the combined metabolomics approach, an overview and in-depth information on secondary metabolites were provided. Halomethanes of Asparagopsis sp. have already been shown to be anti-methanogenic; however, metabolic profiles of seaweeds such as Dictyota and Sargassum have also been shown to contain compounds that may have anti-methanogenic potential.

The relationship between COVID-19 severity and viral load is unknown. Our objective was to assess the association between viral load and disease severity in COVID-19. In this single center observational study of adults with laboratory confirmed SARS-CoV-2, the first positive in-hospital nasopharyngeal swab was used to calculate the log10 copies/ml [log10 copy number (CN)] of SARS-CoV-2. Four categories based on level of care and modified sequential organ failure assessment score (mSOFA) at time of swab were determined. Median log10CN was compared between different levels of care and mSOFA quartiles. Median log10CN was compared in patients who did and did not receive influenza vaccine, and the correlation between log10CN and D-dimer was examined. We found that of 396 patients, 54.3% were male, and 25% had no major comorbidity. Hospital mortality was 15.7%. Median mSOFA was 2 (IQR 0–3). Median log10CN was 5.5 (IQR 3.3–8.0). Median log10CN was highest in non-intubated ICU patients [6.4 (IQR 4.4–8.1)] and lowest in intubated ICU patients [3.6 (IQR 2.6–6.9)] (p value

© 2019 The Authors Approximately 70% of the aquatic-based production of animals is fed aquaculture, whereby animals are provided with high-protein aquafeeds. Currently, aquafeeds are reliant on fish meal and fish oil sourced from wild-captured forage fish. However, increasing use of forage fish is unsustainable and, because an additional 37.4 million tons of aquafeeds will be required by 2025, alternative protein sources are needed. Beyond plant-based ingredients, fishery and aquaculture byproducts and insect meals have the greatest potential to supply the protein required by aquafeeds over the next 10–20 years. Food waste also has potential through the biotransformation and/or bioconversion of raw waste materials, whereas microbial and macroalgal biomass have limitations regarding their scalability and protein content, respectively. In this review, we describe the considerable scope for improved efficiency in fed aquaculture and discuss the development and optimization of alternative protein sources for aquafeeds to ensure a socially and environmentally sustainable future for the aquaculture industry.

INTRODUCTION: Vitamin C deficiency has been described in patients with sepsis. The post-cardiac arrest syndrome shares similarities to sepsis, however vitamin C levels in post-arrest patients have been incompletely characterized. We assessed vitamin C levels in a post-arrest population. METHODS: This was a retrospective observational study at a tertiary care center. A convenience sample of post-arrest, sepsis, and healthy control patients was selected from prior studies. Vitamin C levels were measured from samples obtained within 6-hours of emergency department admission. A subset of cardiac arrest patients had vitamin C levels additionally measured at 24-hours later. RESULTS: A total of 84 patients (34 healthy controls, 25 post-arrest, and 25 septic patients) were included. The median baseline vitamin C level in cardiac arrest patients was 0.33 mg/dL (0.05–0.83), as compared to 0.91mg/dL (0.69–1.48) in the healthy control group (p

Algae-based products have applications in the food and pharmaceutical industries, bioremediation of waste streams and biofuel production. Drying has been recognised to constitute the largest energy cost in algae processing, yet there is limited data or modelling characterising the drying kinetics of macroalgae. This research modelled the equilibrium moisture content of two macroalgae species, Ulva ohnoi, a saltwater alga and Oedogonium intermedium, a freshwater alga. The Guggenheim&ndash, Anderson&ndash, de Boer model was found to best represent experimental equilibrium moisture contents. Drying rate curves obtained under both convective and radiative conditions were fitted to an analytical solution of Fick&rsquo, s second law, including the modelled equilibrium moisture values. Effective diffusivity values for the two species are presented.

BACKGROUND: Burst suppression in mechanically ventilated intensive care unit (ICU) patients is associated with increased mortality. However, the relative contributions of propofol use and critical illness itself to burst suppression; of burst suppression, propofol, and critical illness to mortality; and whether preventing burst suppression might reduce mortality, have not been quantified. METHODS: The dataset contains 471 adults from seven ICUs, after excluding anoxic encephalopathy due to cardiac arrest or intentional burst suppression for therapeutic reasons. We used multiple prediction and causal inference methods to estimate the effects connecting burst suppression, propofol, critical illness, and in-hospital mortality in an observational retrospective study. We also estimated the effects mediated by burst suppression. Sensitivity analysis was used to assess for unmeasured confounding. RESULTS: The expected outcomes in a “counterfactual” Randomized Controlled Trial (cRCT) that assigned patients to mild vs. severe illness is expected to show a difference in burst suppression burden of 39%, 95% CI [8–66]%, and in mortality of 35% [29–41]%. Assigning patients to maximal (100%) burst suppression burden is expected to increase mortality by 12% [7–17]% compared to 0% burden. Burst suppression mediates 10% [2–21]% of the effect of critical illness on mortality. A high cumulative propofol dose (1316 mg/kg) is expected to increase burst suppression burden by 6% [0.8–12]% compared to a low dose (284 mg/kg). Propofol exposure has no significant direct effect on mortality; its effect is entirely mediated through burst suppression. CONCLUSIONS: Our analysis clarifies how important factors contribute to mortality in ICU patients. Burst suppression appears to contribute to mortality but is primarily an effect of critical illness rather than iatrogenic use of propofol.

We present nonlinear resistive MHD simulations of the response of a rotating plasma to an error field when the plasma has weakly damped linear tearing modes (TM's), stabilized by pressure gradient and favorable curvature. Favorable curvature leads to the Glasser effect: the occurrence of real frequencies and stabilization with positive stability index $\Delta'$. A cylinder with hollow pressure is used to model the toroidal favorable curvature. Linear simulations with rotation and an error field $\tilde{\psi}_w$ show, in agreement with analytic results, that the peak reconnected flux occurs for a rotation rate near the TM phase velocity. Nonlinear simulations with small $\tilde{\psi}_w$ show that the real frequency and stabilization by favorable average curvature are masked by a nonlinear effect that occurs for very thin islands: flattening of the pressure across the island, mainly due to sound wave propagation. This flattening causes the disappearance of real frequencies destabilization of the mode, allowing it to grow to large amplitude similar to a $\beta=0$ unstable TM. The flattening of the current for larger islands saturates the mode nonlinearly. In the post-saturation phase, the interaction of the error field with the destabilized spontaneous tearing mode, which rotates with the plasma, leads to oscillations in the Maxwell torque and therefore modulations in the plasma rotation. The islands also rotate with modulated phase velocity, undergoing small-amplitude oscillations due to these modulations. We also present a quasilinear model with an unstable spontaneous TM and error fields, showing that the superposition of these fields results in similar oscillations., Comment: 13 pages, 10 figures

BACKGROUND: Although most patients with medically refractory temporal lobe epilepsy (TLE) experience seizure freedom after anterior temporal lobectomy, approximately 40% may continue to have seizures. Functional network integration, as measured with preoperative resting-state functional MRI, may help stratify patients who are more likely to experience postoperative seizure freedom. PURPOSE: To relate preoperative resting-state functional MRI and surgical outcome in patients with medically refractory TLE. MATERIALS AND METHODS: Data from patients with medically intractable TLE were retrospectively analyzed. Patients underwent preoperative resting-state functional MRI between March 2010 and April 2013 and subsequent unilateral anterior temporal lobectomy. Postoperative seizure-free status was categorized using the Engel Epilepsy Surgery Outcome Scale. Global and regional resting-state functional MRI network properties on preoperative functional MRI scans related to integration were calculated and statistically compared between patients who experienced complete postoperative seizure freedom (Engel class IA) and all others (Engel class IB to class IV) using t tests and multiple logistic regression. RESULTS: Forty patients (mean age, 34 years ± 15 [standard deviation]; 21 female) were evaluated. Preoperative global network integration was different (P = .01) between patients who experienced seizure freedom after surgery and all other patients, with 9% lower leaf fraction and 10% lower tree hierarchy in patients with ongoing seizures. Preoperative regional network integration in the contralateral temporoinsular region was different (P = .04) between patients in these two groups. Specifically, the group-level leaf proportion was 59% lower in the entorhinal cortex, 73% lower in the inferior temporal gyrus, 43% lower in the temporal pole, and 69% lower in the insula in patients with ongoing seizures after surgery. When using multivariate regression, contralateral temporoinsular leaf proportion (P = .002) and epilepsy duration (P = .04) were predictive of postoperative seizure freedom, while age (P > .70) and age at seizure onset (P > .50) were not. CONCLUSION: Lower network integration globally and involving the contralateral temporoinsular cortex on preoperative resting-state functional MRI scans is associated with ongoing postoperative seizures in patients with temporal lobe epilepsy. © RSNA, 2020

We hypothesize that epileptiform abnormalities (EAs) in the electroencephalogram (EEG) during the acute period following traumatic brain injury (TBI) independently predict first-year post-traumatic epilepsy (PTE1 ). We analyze PTE1 risk factors in two cohorts matched for TBI severity and age (n = 50). EAs independently predict risk for PTE1 (odds ratio [OR], 3.16 [0.99, 11.68]); subdural hematoma is another independent risk factor (OR, 4.13 [1.18, 39.33]). Differences in EA rates are apparent within 5 days following TBI. Our results suggest that increased EA prevalence identifies patients at increased risk for PTE1 , and that EAs acutely post-TBI can identify patients most likely to benefit from antiepileptogenesis drug trials. Ann Neurol 2018;83:858-862.

OBJECTIVES: An increasing body of evidence supports a significant contributory role for pancreatic α-cell dysfunction in the pathophysiology of diabetic ketoacidosis (DKA). In normal physiology, high glucose levels stimulate insulin and inhibit glucagon secretion, while low glucose stimulates glucagon but inhibits insulin release. This regulatory mechanism is progressively lost in diabetes mellitus (DM), where diminished insulin levels are accompanied by hyperglucagonemia leading to the further aggravation of hyperglycemia caused by insulin deficiency. Glucagon is produced via the posttranslational modification of proglucagon in a process that also produces other proglucagon molecules including major proglucagon fragment (MPGF) and glucagon like peptide-1 (GLP-1). Here we hypothesized that DKA is associated with α-cell dysfunction leading to elevated levels of proglucagon molecules. METHODS: We measured levels of glucagon, GLP-1 and MPGF as indices of glucagon synthesis/α-cell function in the plasma of patients with DKA and in healthy controls. The inclusion criteria for DKA patients were glucose > 250 mg/dL, pH

Objective In mesial temporal lobe (mTL) epilepsy, seizure onset can precede the appearance of a scalp EEG ictal pattern by many seconds. The ability to identify this early, occult mTL seizure activity could improve lateralization and localization of mTL seizures on scalp EEG. Methods Using scalp EEG spectral features and machine learning approaches on a dataset of combined scalp EEG and foramen ovale electrode recordings in patients with mTL epilepsy, we developed an algorithm, SCOPE-mTL, to detect and lateralize early, occult mTL seizure activity, prior to the appearance of a scalp EEG ictal pattern. Results Using SCOPE-mTL, 73% of seizures with occult mTL onset were identified as such, and no seizures that lacked an occult mTL onset were identified as having one. Predicted mTL seizure onset times were highly correlated with actual mTL seizure onset times (r = 0.69). 50% of seizures with early mTL onset were lateralizable prior to scalp ictal onset, with 94% accuracy. Conclusions SCOPE-mTL can identify and lateralize mTL seizures prior to scalp EEG ictal onset, with high sensitivity, specificity, and accuracy. Significance Quantitative analysis of scalp EEG can provide important information about mTL seizures, even in the absence of a visible scalp EEG ictal correlate.

Super‐refractory status epilepticus (SRSE) is associated with high morbidity and mortality. Treatment of SRSE is complicated by progressive cortical hyperexcitability believed to result in part from synaptic GABA receptor internalization and desensitization. Allopregnanolone, a neurosteroid that positively modulates synaptic and extrasynaptic GABAA receptors, has been proposed as a novel treatment. We describe the first two patients with SRSE who were each successfully treated with a 120‐h continuous infusion of allopregnanolone. Both patients recovered from prolonged SRSE with good cognitive outcomes.

SummaryObjective Evaluate the seizure-reduction response and safety of brain-responsive stimulation in adults with medically intractable partial-onset seizures of neocortical origin. Methods Patients with partial seizures of neocortical origin were identified from prospective clinical trials of a brain-responsive neurostimulator (RNS System, NeuroPace). The seizure reduction over years 2–6 postimplantation was calculated by assessing the seizure frequency compared to a preimplantation baseline. Safety was assessed based on reported adverse events. Additional analyses considered safety and seizure reduction according to lobe and functional area (e.g., eloquent cortex) of seizure onset. Results There were 126 patients with seizures of neocortical onset. The average follow-up was 6.1 implant years. The median percent seizure reduction was 70% in patients with frontal and parietal seizure onsets, 58% in those with temporal neocortical onsets, and 51% in those with multilobar onsets (last observation carried forward [LOCF] analysis). Twenty-six percent of patients experienced at least one seizure-free period of 6 months or longer and 14% experienced at least one seizure-free period of 1 year or longer. Patients with lesions on magnetic resonance imaging (MRI; 77% reduction, LOCF) and those with normal MRI findings (45% reduction, LOCF) benefitted, although the treatment response was more robust in patients with an MRI lesion (p = 0.02, generalized estimating equation [GEE]). There were no differences in the seizure reduction in patients with and without prior epilepsy surgery or vagus nerve stimulation. Stimulation parameters used for treatment did not cause acute or chronic neurologic deficits, even in eloquent cortical areas. The rates of infection (0.017 per patient implant year) and perioperative hemorrhage (0.8%) were not greater than with other neurostimulation devices. Significance Brain-responsive stimulation represents a safe and effective treatment option for patients with medically intractable epilepsy, including adults with seizures of neocortical onset, and those with onsets from eloquent cortex.

SummaryObjective To evaluate published algorithms for the identification of epilepsy cases in medical claims data using a unique linked dataset with both clinical and claims data. Methods Using data from a large, regional health delivery system, we identified all patients contributing biologic samples to the health system's Biobank (n = 36K). We identified all subjects with at least one diagnosis potentially consistent with epilepsy, for example, epilepsy, convulsions, syncope, or collapse, between 2014 and 2015, or who were seen at the epilepsy clinic (n = 1,217), plus a random sample of subjects with neither claims nor clinic visits (n = 435); we then performed a medical chart review in a random subsample of 1,377 to assess the epilepsy diagnosis status. Using the chart review as the reference standard, we evaluated the test characteristics of six published algorithms. Results The best-performing algorithm used diagnostic and prescription drug data (sensitivity = 70%, 95% confidence interval [CI] 66–73%; specificity = 77%, 95% CI 73–81%; and area under the curve [AUC] = 0.73, 95%CI 0.71–0.76) when applied to patients age 18 years or older. Restricting the sample to adults aged 18–64 years resulted in a mild improvement in accuracy (AUC = 0.75,95%CI 0.73–0.78). Adding information about current antiepileptic drug use to the algorithm increased test performance (AUC = 0.78, 95%CI 0.76–0.80). Other algorithms varied in their included data types and performed worse. Significance Current approaches for identifying patients with epilepsy in insurance claims have important limitations when applied to the general population. Approaches incorporating a range of information, for example, diagnoses, treatments, and site of care/specialty of physician, improve the performance of identification and could be useful in epilepsy studies using large datasets.

Three strains of coxsackievirus B3 (CVB3) differ by single mutations in capsid protein VP1 or VP3 and also differ in stability at 37°C in tissue culture medium. Among these strains, the CVB3/28 parent strain has been found to be uniquely sensitive to a component in fetal bovine serum (FBS) identified as serum albumin. In cell culture medium, serum increased the rate of CVB3/28 conversion to noninfectious particles at least 2-fold. The effect showed a saturable dose response. Rates of conversion to noninfectious virus with high concentrations of soluble coxsackievirus and adenovirus receptor (sCAR) were similar with and without FBS, but FBS amplified the catalytic effect of 100 nM sCAR nearly 3-fold. Such effects in other systems are due to nonessential activating cofactors. IMPORTANCE A factor other than the virus receptor expressed by target cells has been found to accelerate the loss of an enterovirus (CVB3/28) infectious titer, with little effect on nearly identical mutant strains. The destabilizing factor in fetal bovine serum, identified as albumin, does not interfere with the catalytic activity of soluble receptor at saturating receptor concentrations and amplifies the catalytic activity of the soluble receptor at a concentration that otherwise produces about one-third the saturated receptor-catalyzed rate of virus decay. This finding evidences the possibility that other virus-“priming” ligands may also be nonessential activating cofactors that serve to accelerate receptor-catalyzed viral eclipse.

Importance Interictal epileptiform discharges (IEDs) in electroencephalograms (EEGs) are a biomarker of epilepsy, seizure risk, and clinical decline. However, there is a scarcity of experts qualified to interpret EEG results. Prior attempts to automate IED detection have been limited by small samples and have not demonstrated expert-level performance. There is a need for a validated automated method to detect IEDs with expert-level reliability. Objective To develop and validate a computer algorithm with the ability to identify IEDs as reliably as experts and classify an EEG recording as containing IEDs vs no IEDs. Design, Setting, and Participants A total of 9571 scalp EEG records with and without IEDs were used to train a deep neural network (SpikeNet) to perform IED detection. Independent training and testing data sets were generated from 13 262 IED candidates, independently annotated by 8 fellowship-trained clinical neurophysiologists, and 8520 EEG records containing no IEDs based on clinical EEG reports. Using the estimated spike probability, a classifier designating the whole EEG recording as positive or negative was also built. Main Outcomes and Measures SpikeNet accuracy, sensitivity, and specificity compared with fellowship-trained neurophysiology experts for identifying IEDs and classifying EEGs as positive or negative or negative for IEDs. Statistical performance was assessed via calibration error and area under the receiver operating characteristic curve (AUC). All performance statistics were estimated using 10-fold cross-validation. Results SpikeNet surpassed both expert interpretation and an industry standard commercial IED detector, based on calibration error (SpikeNet, 0.041; 95% CI, 0.033-0.049; vs industry standard, 0.066; 95% CI, 0.060-0.078; vs experts, mean, 0.183; range, 0.081-0.364) and binary classification performance based on AUC (SpikeNet, 0.980; 95% CI, 0.977-0.984; vs industry standard, 0.882; 95% CI, 0.872-0.893). Whole EEG classification had a mean calibration error of 0.126 (range, 0.109-0.1444) vs experts (mean, 0.197; range, 0.099-0.372) and AUC of 0.847 (95% CI, 0.830-0.865). Conclusions and Relevance In this study, SpikeNet automatically detected IEDs and classified whole EEGs as IED-positive or IED-negative. This may be the first time an algorithm has been shown to exceed expert performance for IED detection in a representative sample of EEGs and may thus be a valuable tool for expedited review of EEGs.

1. Evidence suggests that the restoration of plant diversity in grasslands not only brings benefits for biodiversity conservation, but also the delivery of ecosystem services. While biodiversity- function experiments show that greater plant diversity increases resistance of plant productivity to climate extremes, it is not known whether real-world management options for grassland restoration likewise stabilise ecosystem responses to extreme climate events.2. We used a long-term (23 year) field experiment in northern England to test the hypothesis that management aimed at biodiversity restoration increases the resistance and recovery of ecosystem carbon (C) fluxes to short-term summer drought. This was tested by measuring plant, soil and microbial responses to a simulated drought in experimental grassland plots where fertiliser application and seed addition have been managed to enhance plant species diversity.3. The cessation of fertiliser application brought about small increases in plant species richness. Additionally, cessation of fertiliser application reduced overall plant productivity and promoted hemi-parasitic plants at the expense of grasses and forbs.4. Resistance of CO2 fluxes to drought, measured as ecosystem respiration, was greater in non-fertilised plots, as lower plant biomass reduced water demand, likely aided by proportionally more hemi-parasitic plants further reducing plant biomass. Additionally, legumes increased under drought thereby contributing to overall resistance of plant productivity.5. Recovery of soil microbial C and nitrogen was more rapid after rewetting than soil microbial community composition, irrespective of restoration treatment, suggesting high resilience of soil microbial communities to drought.6. Synthesis and applications. This study shows that while grassland diversity restoration management increases the resistance of C fluxes to drought, it also reduces agricultural yields, revealing a trade-off for land managers. Furthermore legumes, promoted through long-term restoration treatments, can help to maintain plant community productivity under drought by increasing their biomass. As such, grassland management strategies not only have consequences for ecosystem processes, but also the capacity to withstand extreme weather events.

Purpose Stereotactic radiosurgery (SRS) may be an alternative to anterior temporal lobectomy (ATL) for mesial temporal lobe epilepsy (MTLE). Visual field defects (VFD) occur in 9–100% of patients following open surgery for MTLE. Postoperative VFD after minimally invasive versus open surgery may differ. Methods This prospective trial randomized patients with unilateral hippocampal sclerosis and concordant video-EEG findings to SRS versus ATL. Humphries perimetry was obtained at 24 m after surgery. VFD ratios (VFDR = proportion of missing homonymous hemifield with 0 = no VFD, 0.5 = complete superior quadrantanopsia) quantified VFD. Regressions of VFDR were evaluated against treatment arm and covariates. MRI evaluated effects of volume changes on VFDR. The relationships of VFDR with seizure remission and driving status 3 years after surgery were evaluated. Results No patients reported visual changes or had abnormal bedside examinations, but 49 of 54 (91%) of patients experienced VFD on formal perimetry. Neither incidence nor severity of VFDR differed significantly by treatment arm. VFDR severity was not associated with seizure remission or driving status. Conclusion The nature of VFD was consistent with lesions of the optic radiations. Effective surgery (defined by seizure remission) of the mesial temporal lobe results in about a 90% incidence of typical VFD regardless of method.

A 64-year-old right-handed man presented to the emergency department with a 4-week history of bilateral blurred and distorted vision. He reported that objects in his central visual field appeared to change shape and were disproportionately large or small. He also reported intermittent flashes of light with altered color perception. His medical history was notable for prostate cancer treated with prostatectomy, Bell palsy at age 25, gastroesophageal reflux disease, and bilateral refractive errors. His family had also noted intermittent episodes of confusion and anger over the preceding weeks along with difficulty recognizing family members. He endorsed minimal right-sided periorbital headache but reported no diplopia, weakness, paresthesiae, numbness, speech changes, or history of similar symptoms. He had no recent history of fever, illness, or infectious exposures. He had no history of seizures or migraine. He was taking omeprazole and did not smoke or use alcohol or illicit drugs.

Lidia M V R Moura,1 Thiago S Carneiro,1 Andrew J Cole,1 John Hsu,2,3 Barbara G Vickrey,4 Daniel B Hoch1 1Department of Neurology, 2Mongan Institute for Health Policy, Department of Medicine, Massachusetts General Hospital, 3Department of Health Care Policy, Harvard Medical School, Boston, MA, 4Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA Background and aim: Adherence to treatment is a critical component of epilepsy management. This study examines whether addressing antiepileptic drug (AED) side effects at every visit is associated with increased patient-reported medication adherence.Patients and methods: This study identified 243 adults with epilepsy who were seen at two academic outpatient neurology settings and had at least two visits over a 3-year period. Demographic and clinical characteristics were abstracted. Evidence that AED side effects were addressed was measured through 1) phone interview (patient-reported) and 2) medical records abstraction (physician-documented). Medication adherence was assessed using the validated Morisky Medication Adherence Scale-4. Complete adherence was determined as answering “no” to all questions.Results: Sixty-two (25%) patients completed the interviews. Participants and nonparticipants were comparable with respect to demographic and clinical characteristics; however, a smaller proportion of participants had a history of drug-resistant epilepsy than nonparticipants (17.7% vs 30.9%, P=0.04). Among the participants, evidence that AED side effects were addressed was present in 48 (77%) medical records and reported by 51 (82%) patients. Twenty-eight (45%) patients reported complete medication adherence. The most common reason for incomplete adherence was missed medication due to forgetfulness (n=31, 91%). There was no association between addressing AED side effects (neither physician-documented nor patient-reported) and complete medication adherence (P=0.22 and 0.20).Discussion and conclusion: Among patients with epilepsy, addressing medication side effects at every visit does not appear to increase patient-reported medication adherence. Keywords: epilepsy, antiepileptic drug side effects, medication adherence&nbsp

Background. The optimal surgery in lesional neocortical temporal lobe epilepsy is unknown. Hippocampal electrocorticography maximizes seizure freedom by identifying normal-appearing epileptogenic tissue for resection and minimizes neuropsychological deficit by limiting resection to demonstrably epileptogenic tissue. We examined whether standardized hippocampal electrocorticography (hippocampography) guides resection for more consistent hippocampectomy than unguided resection in conventional electrocorticography focused on the lesion. Methods. Retrospective chart reviews any kind of electrocorticography (including hippocampography) as part of combined lesionectomy, anterolateral temporal lobectomy, and hippocampectomy over 8 years . Patients were divided into mesial (i.e., hippocampography) and lateral electrocorticography groups. Primary outcome was deviation from mean hippocampectomy length. Results. Of 26 patients, fourteen underwent hippocampography-guided mesial temporal resection. Hippocampography was associated with 2.6 times more consistent resection. The range of hippocampal resection was 0.7 cm in the mesial group and 1.8 cm in the lateral group (p=0.01). 86% of mesial group versus 42% of lateral group patients achieved seizure freedom (p=0.02). Conclusions. By rationally tailoring excision to demonstrably epileptogenic tissue, hippocampography significantly reduces resection variability for more consistent hippocampectomy than unguided resection in conventional electrocorticography. More consistent hippocampal resection may avoid overresection, which poses greater neuropsychological risk, and underresection, which jeopardizes postoperative seizure freedom.

How the interactions between cortices through a specific white matter pathway change during cognitive processing in patients with epilepsy remains unclear. Here, we used surface-based structural connectivity analysis to examine the change in structural connectivity with Broca's area/the right Broca's homologue in the lateral temporal and inferior parietal cortices through the arcuate fasciculus (AF) in 17 patients with left temporal lobe epilepsy (TLE) compared with 17 healthy controls. Then, we investigated its functional relevance to the changes in task-related responses and task-modulated functional connectivity with Broca's area/the right Broca's homologue during a semantic classification task of a single word. The structural connectivity through the AF pathway and task-modulated functional connectivity with Broca's area decreased in the left midtemporal cortex. Furthermore, task-related response decreased in the left mid temporal cortex that overlapped with the region showing a decrease in the structural connectivity. In contrast, the region showing an increase in the structural connectivity through the AF overlapped with the regions showing an increase in task-modulated functional connectivity in the left inferior parietal cortex. These structural and functional changes in the overlapping regions were correlated. The results suggest that the change in the structural connectivity through the left frontal-temporal AF pathway underlies the altered functional networks between the frontal and temporal cortices during the language-related processing in patients with left TLE. The left frontal-parietal AF pathway might be employed to connect anterior and posterior brain regions during language processing and compensate for the compromised left frontal-temporal AF pathway. Hum Brain Mapp 37:4425-4438, 2016. © 2016 Wiley Periodicals, Inc.

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

The work presented here assesses the potential for the mobilisation of 11 trace elements (As, Be, Co, Cu, Mn, Ni, Pb, Sb, Se, V, Zn) during the thermal conversion of micro-and macroalgae that were cultivated in ash dam water. The volatility of the trace elements was quantified by mass balances based on elemental analyses of char and ash residues. The residues were prepared in a laboratory-scale fixed-bed reactor at a range of different temperatures (500-1100 degrees C) and gas atmospheres (N-2, 2% O-2 and CO2) to simulate pyrolysis, combustion and gasification processes. The results showed high volatilities for Se (similar to 79-97%) and As (similar to 51-79%) below 500 degrees C. Zn, Pb and Sb were mainly volatilised above 700 degrees C. The different gas atmospheres had little influence on the volatility of these elements, which increased sharply to more than 90% with increasing temperature from 700 to 1100 degrees C. Volatilities for V, Mn, Cu, Co, Ni and Be were relatively minor over the full range of investigated operating conditions. Samples of each alga and their thermal conversion residues were subject to batch leaching in water. All of the tested trace elements, except for Pb and Be, were partially leached from the algae. Vanadium was up to 4-5 times more leachable in the combustion residues than in the algae. The other trace elements were generally less leachable following thermal conversion. The trace elements were more stable in residues prepared under pyrolysis and gasification conditions than in residues prepared under combustion conditions at the same temperature.

We directly assessed mesial temporal activity using intracranial foramen ovale electrodes in two patients with Alzheimer's disease (AD) without a history or EEG evidence of seizures. We detected clinically silent hippocampal seizures and epileptiform spikes during sleep, a period when these abnormalities were most likely to interfere with memory consolidation. The findings in these index cases support a model in which early development of occult hippocampal hyperexcitability may contribute to the pathogenesis of AD.

Extreme delta brush (EDB) is an EEG pattern unique to anti-NMDA encephalitis. It is correlated with seizures and status epilepticus in patients who have a prolonged course of illness. The etiology of the underlying association between EDB and seizures is not understood. We present a patient with anti-NMDA encephalitis who developed status epilepticus evolving from the high frequency activity of the extreme delta brush. This case demonstrates that EDB is not only a marker for a greater propensity for seizures but also directly implicated in seizure generation.

Chimeric antigen receptor-modified T cells (CAR-T) have emerged as a promising immunotherapeutic approach in relapsed/refractory haematolgical malignancies. Broader application is limited by unique toxicities, notably, neurotoxicity (NTX). Language dysfunction is among the most frequent symptoms of NTX, the underlying mechanisms of which remain to be elucidated. Electroencephalogram (EEG) is an important tool to monitor for NTX and may provide insights into language dysfunction.AimWe aimed to characterise language dysfunction and define electroencephalographic signatures after CAR-T cell therapy.MethodsWe reviewed the clinical presentation and EEG findings of 20 adult patients presenting with language dysfunction after CAR-T cell infusion. The cohort included a subset of patients treated with investigational CD19-directed CAR-T cells for non-Hodgkin’s lymphoma (n=17), acute lymphoblastic leukaemia (n=1), follicular lymphoma (n=1) and chronic lymphocytic leukaemia (n=1).ResultsLanguage dysfunction presented within 14 days of CAR-T cell infusion in 16 (84%) patients. Ten (50%) patients had mild word-finding difficulties and 10 (50%) had marked dysphasia with profound word-finding difficulties; the latter were all associated with generalised rhythmic delta activity or generalised periodic discharges on EEG.ConclusionsLanguage dysfunction after CAR-T cell therapy is associated with generalised EEG abnormalities.

Importance The validity of using electroencephalograms (EEGs) to diagnose epilepsy requires reliable detection of interictal epileptiform discharges (IEDs). Prior interrater reliability (IRR) studies are limited by small samples and selection bias. Objective To assess the reliability of experts in detecting IEDs in routine EEGs. Design, Setting, and Participants This prospective analysis conducted in 2 phases included as participants physicians with at least 1 year of subspecialty training in clinical neurophysiology. In phase 1, 9 experts independently identified candidate IEDs in 991 EEGs (1 expert per EEG) reported in the medical record to contain at least 1 IED, yielding 87 636 candidate IEDs. In phase 2, the candidate IEDs were clustered into groups with distinct morphological features, yielding 12 602 clusters, and a representative candidate IED was selected from each cluster. We added 660 waveforms (11 random samples each from 60 randomly selected EEGs reported as being free of IEDs) as negative controls. Eight experts independently scored all 13 262 candidates as IEDs or non-IEDs. The 1051 EEGs in the study were recorded at the Massachusetts General Hospital between 2012 and 2016. Main Outcomes and Measures Primary outcome measures were percentage of agreement (PA) and beyond-chance agreement (Gwet κ) for individual IEDs (IED-wise IRR) and for whether an EEG contained any IEDs (EEG-wise IRR). Secondary outcomes were the correlations between numbers of IEDs marked by experts across cases, calibration of expert scoring to group consensus, and receiver operating characteristic analysis of how well multivariate logistic regression models may account for differences in the IED scoring behavior between experts. Results Among the 1051 EEGs assessed in the study, 540 (51.4%) were those of females and 511 (48.6%) were those of males. In phase 1, 9 experts each marked potential IEDs in a median of 65 (interquartile range [IQR], 28-332) EEGs. The total number of IED candidates marked was 87 636. Expert IRR for the 13 262 individually annotated IED candidates was fair, with the mean PA being 72.4% (95% CI, 67.0%-77.8%) and mean κ being 48.7% (95% CI, 37.3%-60.1%). The EEG-wise IRR was substantial, with the mean PA being 80.9% (95% CI, 76.2%-85.7%) and mean κ being 69.4% (95% CI, 60.3%-78.5%). A statistical model based on waveform morphological features, when provided with individualized thresholds, explained the median binary scores of all experts with a high degree of accuracy of 80% (range, 73%-88%). Conclusions and Relevance This study’s findings suggest that experts can identify whether EEGs contain IEDs with substantial reliability. Lower reliability regarding individual IEDs may be largely explained by various experts applying different thresholds to a common underlying statistical model.

ObjectiveTo compare the expected quality-adjusted life-years (QALYs) in adult patients undergoing immediate vs deferred antiepileptic drug (AED) treatment after a first unprovoked seizure.MethodsWe constructed a simulated clinical trial (Markov decision model) to compare immediate vs deferred AED treatment after a first unprovoked seizure in adults. Three base cases were considered, representing patients with varying degrees of seizure recurrence risk and effect of seizures on quality of life (QOL). Cohort simulation was performed to determine which treatment strategy would maximize the patient's expected QALYs. Sensitivity analyses were guided by clinical data to define decision thresholds across plausible measurement ranges, including seizure recurrence rate, effect of seizure recurrence on QOL, and efficacy of AEDs.ResultsFor patients with a moderate risk of recurrent seizures (52.0% over 10 years after first seizure), immediate AED treatment maximized QALYs compared to deferred treatment. Sensitivity analyses showed that for the preferred choice to change to deferred AED treatment, key clinical measures needed to reach implausible values were 10-year seizure recurrence rate ≤38.0%, QOL reduction with recurrent seizures ≤0.06, and efficacy of AEDs on lowering seizure recurrence rate ≤16.3%.ConclusionOur model determined that immediate AED treatment is preferable to deferred treatment in adult first-seizure patients over a wide and clinically relevant range of variables. Furthermore, our analysis suggests that the 10-year seizure recurrence rate that justifies AED treatment (38.0%) is substantially lower than the 60% threshold used in the current definition of epilepsy.

Objectives Absence of somatosensory evoked potentials is considered a nearly perfect predictor of poor outcome after cardiac arrest. However, reports of good outcomes despite absent somatosensory evoked potentials and high rates of withdrawal of life-sustaining therapies have raised concerns that estimates of the prognostic value of absent somatosensory evoked potentials may be biased by self-fulfilling prophecies. We aimed to develop an unbiased estimate of the false positive rate of absent somatosensory evoked potentials as a predictor of poor outcome after cardiac arrest. Data sources PubMed. Study selection We selected 35 studies in cardiac arrest prognostication that reported somatosensory evoked potentials. Data extraction In each study, we identified rates of withdrawal of life-sustaining therapies and good outcomes despite absent somatosensory evoked potentials. We appraised studies for potential biases using the Quality in Prognosis Studies tool. Using these data, we developed a statistical model to estimate the false positive rate of absent somatosensory evoked potentials adjusted for withdrawal of life-sustaining therapies rate. Data synthesis Two-thousand one-hundred thirty-three subjects underwent somatosensory evoked potential testing. Five-hundred ninety-four had absent somatosensory evoked potentials; of these, 14 had good functional outcomes. The rate of withdrawal of life-sustaining therapies for subjects with absent somatosensory evoked potential could be estimated in 14 of the 35 studies (mean 80%, median 100%). The false positive rate for absent somatosensory evoked potential in predicting poor neurologic outcome, adjusted for a withdrawal of life-sustaining therapies rate of 80%, is 7.7% (95% CI, 4-13%). Conclusions Absent cortical somatosensory evoked potentials do not infallibly predict poor outcome in patients with coma following cardiac arrest. The chances of survival in subjects with absent somatosensory evoked potentials, though low, may be substantially higher than generally believed.

Objective Delayed cerebral ischemia (DCI) is a common, disabling complication of subarachnoid hemorrhage (SAH). Preventing DCI is a key focus of neurocritical care, but interventions carry risk and cannot be applied indiscriminately. Although retrospective studies have identified continuous electroencephalographic (cEEG) measures associated with DCI, no study has characterized the accuracy of cEEG with sufficient rigor to justify using it to triage patients to interventions or clinical trials. We therefore prospectively assessed the accuracy of cEEG for predicting DCI, following the Standards for Reporting Diagnostic Accuracy Studies. Methods We prospectively performed cEEG in nontraumatic, high-grade SAH patients at a single institution. The index test consisted of clinical neurophysiologists prospectively reporting prespecified EEG alarms: (1) decreasing relative alpha variability, (2) decreasing alpha-delta ratio, (3) worsening focal slowing, or (4) late appearing epileptiform abnormalities. The diagnostic reference standard was DCI determined by blinded, adjudicated review. Primary outcome measures were sensitivity and specificity of cEEG for subsequent DCI, determined by multistate survival analysis, adjusted for baseline risk. Results One hundred three of 227 consecutive patients were eligible and underwent cEEG monitoring (7.7-day mean duration). EEG alarms occurred in 96.2% of patients with and 19.6% without subsequent DCI (1.9-day median latency, interquartile range = 0.9-4.1). Among alarm subtypes, late onset epileptiform abnormalities had the highest predictive value. Prespecified EEG findings predicted DCI among patients with low (91% sensitivity, 83% specificity) and high (95% sensitivity, 77% specificity) baseline risk. Interpretation cEEG accurately predicts DCI following SAH and may help target therapies to patients at highest risk of secondary brain injury. Ann Neurol 2018;83:958-969.

ObjectiveTo investigate the correlation between characteristics of lateralized periodic discharges (LPDs) and glucose metabolism measured by 18F-fluorodeoxyglucose (FDG)–PET.MethodsWe retrospectively reviewed medical records to identify patients who underwent FDG-PET during EEG monitoring with LPDs present during the FDG uptake period. Two blinded board-certified neurophysiologists independently interpreted EEGs. FDG uptake was measured using standardized uptake value (SUV). Structural images were fused with PET images to aid with localization of SUV. Two PET readers independently measured maximum SUV. Relative SUV values were obtained by normalization of the maximum SUV to the SUV of pons (SUVRpons). LPD frequency was analyzed both as a categorical variable and as a continuous measure. Other secondary variables included duration, amplitude, presence of structural lesion, and “plus” EEG features such as rhythmic or fast sharp activity.ResultsNine patients were identified and 7 had a structural etiology for LPDs. Analysis using frequency as a categorical variable and continuous variable showed an association between increased LPD frequency and increased ipsilateral SUVRpons (p = 0.02). Metabolism associated with LPDs (0.5 Hz as a baseline) increased by a median of 100% at 1 Hz and for frequencies >1 Hz increased by a median of 309%. There were no statistically significant differences in SUVRpons for other factors including duration (p = 0.10), amplitude (p = 0.80), structural etiology (p = 0.55), or “plus” features such as rhythmic or fast sharp activity (p = 0.84).ConclusionsMetabolic activity increases monotonically with LPD frequency. LPD frequency should be a measure of interest when developing neuroprotection strategies in critical neurologic illness.

Objective To compare stereotactic radiosurgery (SRS) versus anterior temporal lobectomy (ATL) for patients with pharmacoresistant unilateral mesial temporal lobe epilepsy (MTLE). Methods This randomized, single-blinded, controlled trial recruited adults eligible for open surgery among 14 centers in the USA, UK, and India. Treatment was either SRS at 24 Gy to the 50% isodose targeting mesial structures, or standardized ATL. Outcomes were seizure remission (absence of disabling seizures between 25 and 36 months), verbal memory (VM), and quality of life (QOL) at 36-month follow-up. Results A total of 58 patients (31 in SRS, 27 in ATL) were treated. Sixteen (52%) SRS and 21 (78%) ATL patients achieved seizure remission (difference between ATL and SRS = 26%, upper 1-sided 95% confidence interval = 46%, P value at the 15% noninferiority margin = .82). Mean VM changes from baseline for 21 English-speaking, dominant-hemisphere patients did not differ between groups; consistent worsening occurred in 36% of SRS and 57% of ATL patients. QOL improved with seizure remission. Adverse events were anticipated cerebral edema and related symptoms for some SRS patients, and cerebritis, subdural hematoma, and others for ATL patients. Significance These data suggest that ATL has an advantage over SRS in terms of proportion of seizure remission, and both SRS and ATL appear to have effectiveness and reasonable safety as treatments for MTLE. SRS is an alternative to ATL for patients with contraindications for or with reluctance to undergo open surgery.

Chimeric antigen receptor (CAR) modified T cells emerged as promising immunotherapy in refractory lymphoid malignancies.1 Despite efficacy, toxicities include cytokine release syndrome (CRS) and neurotoxicity.1 We report EEG findings in patients with chemotherapy-refractory stage IV diffuse large B-cell lymphoma (DLBCL-4) who received CAR T cells and developed neurotoxicity.

In most countries the mining industry is required to rehabilitate disturbed land with native vegetation. A typical approach is to stockpile soils during mining and then use this soil to recreate landforms after mining. Soil that has been stockpiled for an extended period typically contains little or no organic matter and nutrient, making soil rehabilitation a slow and difficult process. Here, we take freshwater macroalgae ( Oedogonium ) cultivated in waste water at a coal-fired power station and use it as a feedstock for the production of biochar, then use this biochar to enhance the rehabilitation of two types of stockpiled soil – a ferrosol and a sodosol – from the adjacent coal mine. While the biomass had relatively high concentrations of some metals, due to its cultivation in waste water, the resulting biochar did not leach metals into the pore water of soil-biochar mixtures. The biochar did, however, contribute essential trace elements (particularly K) to soil pore water. The biochar had very strong positive effects on the establishment and growth of a native plant (Kangaroo grass, Themeda australis ) in both of the soils. The addition of the algal biochar to both soils at 10 t ha −1 reduced the time to germination by the grass and increased the growth and production of plant biomass. Somewhat surprisingly, there was no beneficial effect of a higher application rate (25 t ha −1 ) of the biochar in the ferrosol, which highlights the importance of matching biochar application rates to the requirements of different types of soil. Nevertheless, we demonstrate that algal biochar can be produced from biomass cultivated in waste water and used at low application rates to improve the rehabilitation of a variety of soils typical of coal mines. This novel process links biomass production in waste water to end use of the biomass in land rehabilitation, simultaneously addressing two environmental issues associated with coal-mining and processing.