Vagus nerve stimulation for treatment of drug-resistant epilepsy: a systematic review and meta-analysis.

To analyze the efficacy and safety of high-frequency VNS versus control (low-frequency VNS or no VNS) in patients with DRE using data from randomized controlled trials (RCTs). An electronic literature search was conducted on PubMed, EMBASE, and Cochrane Controlled Register of Trials (CENTRAL); 12 RCTs reporting seizure frequency or treatment response in studies containing a high-frequency VNS treatment arm (conventional VNS or transcutaneous VNS [tVNS]) compared to control (low-frequency VNS or no VNS) were included. Seizure frequency, treatment response (number of patients with ≥ 50% reduction in seizure frequency), quality of life (QOL), and adverse effects were analyzed. Seizure frequency was reported in 9 studies (718 patients). Meta-analysis with random-effects models favored high-frequency VNS over control (standardized mean difference = 0.82, 95%-CI = 0.39-1.24, p < .001). This remained significant for subgroup analyses of low-frequency VNS as the control, VNS modality, and after removing studies with moderate-to-high risk of bias. Treatment response was reported in 8 studies (758 patients). Random-effects models favored high-frequency VNS over control (risk ratio = 1.57, 95%-CI = 1.19-2.07, p < .001). QOL outcomes were reported descriptively in 4 studies (363 patients), and adverse events were reported in 11 studies (875 patients). Major side effects and death were not observed to be more common in high-frequency VNS compared to control. High-frequency VNS results in reduced seizure frequency and improved treatment response compared to control (low-frequency VNS or no VNS) in patients with drug-resistant epilepsy. Greater consideration for VNS in patients with DRE may be warranted to decrease seizure frequency in the management of these patients.

Validation of Serial Alberta Stroke Program Early CT Score as an Outcome Predictor in Thrombolyzed Stroke Patients.

BACKGROUND: The Alberta Stroke Program Early CT Score (ASPECTS) on baseline imaging is an established predictor of functional outcome in anterior circulation acute ischemic stroke (AIS). We studied ASPECTS before intravenous thrombolysis (IVT) and at 24 hours to assess its prognostic value. METHODS: Data for consecutive anterior circulation AIS patients treated with IVT from 2006 to 2013 were extracted from a prospectively managed registry at our tertiary center. Pre-thrombolysis and 24-hour ASPECTS were evaluated by 2 independent neuroradiologists. Outcome measures included symptomatic intracranial hemorrhage (SICH), modified Rankin Scale (mRS) at 90 days, and mortality. Unfavorable functional outcome was defined by mRS >1. Dramatic ASPECTS progression (DAP) was defined as deterioration in ASPECTS by 6 points or more. RESULTS: Of 554 AIS patients thrombolyzed during the study period, 400 suffered from anterior circulation infarction. The median age was 65 years (interquartile range (IQR): 59-70) and the median National Institutes of Health Stroke Scale score was 18 points (IQR: 12-22). Compared with the pre-IVT ASPECTS (area under the curve [AUC] = .64, 95% confidence interval [CI]: .54-.65, P = .001), ASPECTS on the 24-hour CT scan (AUC = .78, 95% CI: .73-.82, P < .001), and change in ASPECTS (AUC = .69, 95% CI: .64-.74, P < .001) were better predictors of unfavorable functional outcome at 3 months. DAP, noted in 34 (14.4%) patients with good baseline ASPECTS (8-10 points), was significantly associated with unfavorable functional outcome (odds ratio [OR]: 9.91, 95% CI: 3.37-29.19, P ≤ .001), mortality (OR: 21.99, 95% CI: 7.98-60.58, P < .001), and SICH (OR: 8.57, 95% CI: 2.87-25.59, P < .001). CONCLUSION: Compared with the pre-thrombolysis score, ASPECTS measured at 24 hours as well as serial change in ASPECTS is a better predictor of 3-month functional outcome.

Good Intracranial Collaterals Trump Poor ASPECTS (Alberta Stroke Program Early CT Score) for Intravenous Thrombolysis in Anterior Circulation Acute Ischemic Stroke.

BACKGROUND AND PURPOSE: In acute ischemic stroke, large early infarct size estimated by the Alberta Stroke Program Early CT Score (ASPECTS) is associated with poorer outcomes and is a relative contraindication for recanalization therapies. The state of the intracranial collateral circulation influences the functional outcome and may be a variable to consider before thrombolysis. We evaluated the prognostic effect of the collateral circulation in patients with thrombolyzed acute ischemic stroke who have large early infarct sizes as indicated by low ASPECTS. MATERIALS AND METHODS: Patients with anterior circulation acute ischemic stroke who received a computed tomographic angiogram and subsequent treatment with intravenous tissue-type plasminogen activator from 2010 to 2013 were studied. Two independent neuroradiologists determined their ASPECTS. We stratified patients using ASPECTS into 2 groups: large volume infarcts (ASPECTS≤7 points) and small volume infarcts (ASPECTS 8-10). In addition, we evaluated a third group with very large volume infarcts (ASPECTS≤5 points). We then analyzed the 3 subgroups using the Maas, Tan, and ASPECTS-collaterals grading systems of the computed tomographic angiogram intracranial collaterals. Good outcomes were defined by modified Rankin Scale score of 0 to 2 at 3 months. RESULTS: A total of 300 patients were included in the final analysis. For patients with very large volume infarcts (ASPECTS≤5 points), univariable analysis showed that younger age, male sex, lower National Institute of Health Stroke Scale (NIHSS), lower systolic blood pressure, and good collaterals by Maas, Tan, or ASPECTS-collaterals grading were predictors of good outcomes. On multivariate analysis, younger age (odds ratio, 0.93; 95% confidence interval, 0.89-0.97; P=0.002) and good collaterals by ASPECTS-collaterals system (odds ratio, 1.34; 95% confidence interval, 1.15-1.57; P<0.001) were associated with good outcomes. CONCLUSIONS: In patients with large and very large volume infarcts, good collaterals as measured by the ASPECTS-collaterals system is associated with improved outcomes and can help select patients for intravenous thrombolysis.

Intravenous Thrombolysis for Acute Ischemic Stroke due to Cervical Internal Carotid Artery Occlusion.

BACKGROUND: Internal carotid artery (ICA) occlusions are poorly responsive to intravenous thrombolysis with tissue plasminogen activator (IV-tPA) in acute ischemic stroke (AIS). Most study populations have combined intracranial and extracranial ICA occlusions for analysis; few have studied purely cervical ICA occlusions. We evaluated AIS patients with acute cervical ICA occlusion treated with IV-tPA to identify predictors of outcomes. METHODS: We studied 550 consecutive patients with AIS who received IV-tPA and identified 100 with pure acute cervical ICA occlusion. We evaluated the associations of vascular risk factors, National Institutes of Health Stroke Scale (NIHSS) score, and leptomeningeal collateral vessel status via 3 different grading systems, with functional recovery at 90 days, mortality, recanalization of the primary occlusion, and symptomatic intracranial hemorrhage (SICH). Modified Rankin Scale score 0-1 was defined as an excellent outcome. RESULTS: The 100 patients had mean age of 67.8 (range 32-96) and median NIHSS score of 19 (range 4-33). Excellent outcomes were observed in 27% of the patients, SICH in 8%, and mortality in 21%. Up to 54% of the patients achieved recanalization at 24 hours. On ordinal regression, good collaterals showed a significant shift in favorable outcomes by Maas, Tan, or ASPECTS collateral grading systems. On multivariate analysis, good collaterals also showed reduced mortality (OR .721, 95% CI .588-.888, P = .002) and a trend to less SICH (OR .81, 95% CI .65-1.007, P = .058). Interestingly, faster treatment was also associated with favorable functional recovery (OR 1.028 per minute, 95% CI 1.010-1.047, P = .001). CONCLUSIONS: Improved outcomes are seen in patients with early acute cervical ICA occlusion and better collateral circulation. This could be a valuable biomarker for decision making.

External validation of the Boston Acute Stroke Imaging Scale and M1-BASIS in thrombolyzed patients.

BACKGROUND AND PURPOSE: Radiological findings play an essential role in therapeutic decision making and prognostication in acute ischemic stroke (AIS). The Boston Acute Stroke Imaging Scale (BASIS) and Middle Cerebral Artery-BASIS (M1-BASIS) methodologies are rapid purely radiological instruments and easily applicable for patients with AIS. We validated these methods in patients with AIS treated with intravenous tissue-type plasminogen activator. METHODS: For BASIS, patients were labeled as having major stroke if there was occlusion of distal internal carotid artery, proximal (both M1 and M2 segments) of middle cerebral artery or the basilar artery, or an Alberta Stroke Program Early CT Score≤7. M1-BASIS differs from BASIS by classifying AIS patients with M2 occlusion as a minor stroke. We evaluated these classification systems for predicting functional outcomes (modified Rankin Scale score 0-1) at 3 months. RESULTS: Two hundred sixty-five consecutive AIS patients treated with intravenous tissue-type plasminogen activator were included. On multivariate analysis, younger age (odds ratio, 1.039, 95% confidence interval, 1.009-1.070; P=0.011), lower National Institutes of Health Stroke Scale score (odds ratio, 1.140; 95% confidence interval, 1.073-1.210; P<0.001), and minor stroke by M1-BASIS (odds ratio, 2.376; 95% confidence interval, 1.047-5.393; P=0.039) were independent predictors of good functional outcome. When compared with National Institutes of Health Stroke Scale, the receiver operating characteristic curves for both BASIS (area under the curve, 0.721) and M1-BASIS (area under the curve, 0.795) correlated well with clinical severity scores. M1-BASIS has an additive effect with the National Institutes of Health Stroke Scale score to predict good outcomes. CONCLUSIONS: The purely radiological M1-BASIS correlates well with the clinical severity of stroke and can be a reliable prognostication tool in thrombolyzed AIS patients. This system might find an important place in the current era of telestroke.

Intravenously administered tissue plasminogen activator useful in milder strokes? A meta-analysis.

BACKGROUND: The dilemma of whether to treat mild strokes with tPA is a chronic problem. We performed a meta-analysis and metaregression of the published literature to determine the best definition of mild strokes and if intravenously administered tissue plasminogen activator (IV-tPA) is beneficial. METHODS: PubMed, Embase, Science Direct, and Cochrane CENTRAL were searched from inception to May 2013. The search terms used were "stroke," "cerebral infarct," "mild stroke," "minor stroke," "small infarct," "modified Rankin scale," "National Institutes of Health Stroke Scale (NIHSS) score," "stroke thrombolysis," and their combinations. Studies were included if they (1) involved 5 or more human patients with stroke; (2) analyzed modified Rankin scale (mRS) scores as the main variables of interest; (3) presented outcomes for NIHSS scores less than 6, 5, 4, or 3 points. Good outcomes were defined as mRS scores 0-1, and other outcomes studied were intracranial hemorrhage and mortality. RESULTS: Of 894 articles, 30 articles met our criteria. Only 8 articles provided patients arms with and without tPA treatment. A total of 637 patients with IV-tPA treatment and 568 without thrombolysis were included in analysis. Good outcomes were associated with tPA and just reached statistical significance (pooled odds ratio [OR], 1.319; 95% confidence interval [CI], 1.004-1.733; z = 1.987; P = .047). There were moderate levels of heterogeneity between studies (τ(2) = .346; Q = 19.974; df = 7; P = .006; I(2) = 64.954). On metaregression of a-priori sources of heterogeneity within individuals, we found age (B = -.37; z = -2.496; P = .012) to be a significant moderator. Mortality was not significantly different between IV-tPA-treated and nonthrombolyzed groups (pooled OR 1.095; 95% CI, .438-2.738; z = .193; P = .847). CONCLUSIONS: Patients with mild stroke may derive benefit from intravenous thrombolysis without a significant increase in mortality.

Polymyxin-induced neuromuscular weakness: a case report.

Polymyxin-induced neuromuscular blockade is a rare but potentially fatal condition, with majority of cases that were reported between 1962 and 1973. We describe a patient who developed hypercapnic respiratory failure after initiation of polymyxin for multi-drug resistant Escherichia Coli bacteremia, due to polymyxin-induced neuromuscular dysfunction. After cessation of polymyxin, he regained full strength, had complete resolution of ptosis, and was successfully extubated. In light of the renewed use of polymyxin in this era of antimicrobial-resistance, this case aims to raise awareness about this rare but life-threatening condition, which is easily reversible with early recognition and prompt discontinuation of the drug.

Early and continuous neurologic improvements after intravenous thrombolysis are strong predictors of favorable long-term outcomes in acute ischemic stroke.

BACKGROUND: Intravenously administered tissue plasminogen activator (IV tPA) remains the only approved therapeutic agent for arterial recanalization in acute ischemic stroke (AIS). Considerable proportion of AIS patients demonstrate changes in their neurologic status within the first 24 hours of intravenous thrombolysis with IV tPA. However, there are little available data on the course of clinical recovery in subacute 2- to 24-hour window and its impact. We evaluated whether neurologic improvement at 2 and 24 hours after IV tPA bolus can predict functional outcomes in AIS patients at 3 months. METHODS: Data for consecutive AIS patients treated with IV tPA within 4.5 hours of symptom onset during 2007-2011 were prospectively entered in our thrombolyzed registry. National Institutes of Health Stroke Scale (NIHSS) scores were recorded before IV tPA bolus, at 2 and 24 hours. Early neurologic improvement (ENI) at 2 hours was defined as a reduction in NIHSS score by 10 or more points from baseline or an absolute score of 4 or less points at 2 hours. Continuous neurologic improvement (CNI) was defined as a reduction of NIHSS score by 8 or more points between 2 and 24 hours or an absolute score of 4 or less points at 24 hours. Favorable functional outcomes at 3 months were determined by modified Rankin Scale (mRS) score of 0-1. RESULTS: Of 2460 AIS patients admitted during the study period, 263 (10.7%) received IV tPA within the time window; median age was 64 years (range 19-92), with 63.9% being men, a median NIHSS score of 17 points (range 5-35), and a median onset-to-treatment time of 145 minutes (range 57-270). Overall, 130 (49.4%) thrombolyzed patients achieved an mRS score of 0-1 at 3 months. The female gender, age, and baseline NIHSS score were found to be significantly associated with CNI on univariate analysis. On multivariate analysis, NIHSS score at onset and female gender (odds ratio [OR]: 2.218, 95% confidence interval [CI]: 1.140-4.285; P=.024) were found to be independent predictors of CNI. Factors associated with favorable outcomes at 3 months on univariate analysis were younger age, female gender, hypertension, NIHSS score at onset, recanalization on transcranial Doppler (TCD) monitoring or repeat computed tomography (CT) angiography, ENI at 2 hours, and CNI. On multivariate analysis, NIHSS score at onset (OR per 1-point increase: .835, 95% CI: .751-.929, P<.001), 2-hour TCD recanalization (OR: 3.048, 95% CI: 1.537-6.046; P=.001), 24-hour CT angiographic recanalization (OR: 4.329, 95% CI: 2.382-9.974; P=.001), ENI at 2 hours (OR: 2.536, 95% CI: 1.321-5.102; P=.004), and CNI (OR: 7.253, 95% CI: 3.682-15.115; P<.001) were independent predictors of favorable outcomes at 3 months. CONCLUSIONS: Women are twice as likely to have CNI from the 2- to 24-hour period after IV tPA. ENI and CNI within the first 24 hours are strong predictors of favorable functional outcomes in thrombolyzed AIS patients.

Bridging the Gap: Tailoring an Approach to Treatment in Febrile Infection-Related Epilepsy Syndrome.

Cytokine profiling before immunotherapy is increasingly prevalent in febrile infection-related epilepsy syndrome (FIRES). In this case, an 18-year-old man presented with first-onset seizure after a nonspecific febrile illness. He developed super-refractory status epilepticus requiring multiple antiseizure medications and general anesthetic infusions. He was treated with pulsed methylprednisolone and plasma exchange and started on ketogenic diet. Contrast-enhanced MRI brain revealed postictal changes. EEG findings showed multifocal ictal runs and generalized periodic epileptiform discharges. CSF analysis, autoantibody testing, and malignancy screening were unremarkable. Genetic testing revealed variants of uncertain significance in the CNKSR2 and OPN1LW genes. Initial serum and CSF cytokine analyses performed on days 6 and 21 revealed that interleukin (IL)-6, IL-1RA, monocyte chemoattractant protein-1, macrophage inflammatory protein 1ß, and interferon γ were elevated predominantly in the CNS, a profile consistent with cytokine release syndrome. Tofacitinib was initially trialed on day 30 of admission. There was no clinical improvement, and IL-6 continued to rise. Tocilizumab was given on day 51 with significant clinical and electrographic response. Anakinra was subsequently trialed from days 99 to 103 because clinical ictal activity re-emerged on weaning anesthetics but stopped because of poor response. Serial cytokine profiles showed improvement after 7 doses of tocilizumab. There was corresponding improved seizure control. This case illustrates how personalized immunomonitoring may be helpful in cases of FIRES, where proinflammatory cytokines are postulated to act in epileptogenesis. There is an emerging role for cytokine profiling and close collaboration with immunologists for the treatment of FIRES. The use of tocilizumab may be considered in patients with FIRES with upregulated IL-6.

Combined balloon guide catheter, aspiration catheter, and stent retriever technique versus balloon guide catheter and stent retriever alone technique: a systematic review and meta-analysis.

BACKGROUND: The use of a combination of balloon guide catheter (BGC), aspiration catheter, and stent retriever in acute ischemic stroke thrombectomy has not been shown to be better than a stent retriever and BGC alone, but this may be due to a lack of power in these studies. We therefore performed a meta-analysis on this subject. METHODS: A systematic literature search was performed on PubMed, Scopus, Embase/Ovid, and the Cochrane Library from inception to October 20, 2021. Our primary outcomes were the rate of successful final reperfusion (Treatment in Cerebral Ischemia (TICI) 2c-3) and first pass effect (FPE, defined as TICI 2c-3 in a single pass). Secondary outcomes were 3 month functional independence (modified Rankin Scale score of 0-2), mortality, procedural complications, embolic complications, and symptomatic intracranial hemorrhage (SICH). A meta-analysis was performed using RevMan 5,4, and heterogeneity was assessed using the I2 test. RESULTS: Of 1629 studies identified, five articles with 2091 patients were included. For the primary outcomes, FPE (44.9% vs 45.4%, OR 1.04 (95% CI 0.90 to 1.22), I2=57%) or final successful reperfusion (64.5% vs 68.6%, OR 0.98 (95% CI 0.81% to 1.20%), I2=85%) was similar between the combination technique and stent retriever only groups. However, the combination technique had significantly less rescue treatment (18.8% vs 26.9%; OR 0.70 (95% CI 0.54 to 0.91), I2=0%). This did not translate into significant differences in secondary outcomes in functional outcomes, mortality, emboli, complications, or SICH. CONCLUSION: There was no significant difference in successful reperfusion and FPE between the combined techniques and the stent retriever and BGC alone groups. Neither was there any difference in functional outcomes, complications, or mortality.

Sodium-glucose cotransporter 2 inhibitors and neurological disorders: a scoping review.

Background: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) are a group of antidiabetic medications with a favourable cardiovascular, renal and overall safety profile. Given the limited treatment options available for neurological disorders, it is important to determine whether the pleiotropic effects of SGLT2i can be utilised in their prevention and management. Methods: All articles published before 20 March 2021 were systematically searched in MEDLINE, EMBASE, Scopus, Web of Science, APA PsycINFO and ClinicalTrials.gov. Overall, 1395 titles were screened, ultimately resulting in 160 articles being included in the qualitative analysis. Screening and data extraction were conducted by two independent authors and studies were excluded if they were not an original research study. Findings: Of the 160 studies, 134 addressed stroke, 19 cognitive impairment, 4 epilepsy and 4 movement disorders, encompassing a range from systematic reviews and randomised controlled trials to bioinformatic and animal studies. Most animal studies demonstrated significant improvements in behavioural and neurological deficits, which were reflected in beneficial changes in neurovascular units, synaptogenesis, neurotransmitter levels and target receptors' docking energies. The evidence from the minority clinical literature was conflicting and many studies did not reach statistical significance. Interpretation: SGLT2i may exert neurological benefits through three mechanisms: reduction in cardiovascular risk factors, augmentation of ketogenesis and anti-inflammatory pathways. Most clinical studies were observational, meaning that a causal relationship could not be established, while randomised controlled trials were heterogeneous and powered to detect cardiovascular or renal outcomes. We suggest that a longitudinal study should be conducted and specifically powered to detect neurological outcomes.

Improving automated diagnosis of epilepsy from EEGs beyond IEDs.

Objective.Clinical diagnosis of epilepsy relies partially on identifying interictal epileptiform discharges (IEDs) in scalp electroencephalograms (EEGs). This process is expert-biased, tedious, and can delay the diagnosis procedure. Beyond automatically detecting IEDs, there are far fewer studies on automated methods to differentiate epileptic EEGs (potentially without IEDs) from normal EEGs. In addition, the diagnosis of epilepsy based on a single EEG tends to be low. Consequently, there is a strong need for automated systems for EEG interpretation. Traditionally, epilepsy diagnosis relies heavily on IEDs. However, since not all epileptic EEGs exhibit IEDs, it is essential to explore IED-independent EEG measures for epilepsy diagnosis. The main objective is to develop an automated system for detecting epileptic EEGs, both with or without IEDs. In order to detect epileptic EEGs without IEDs, it is crucial to include EEG features in the algorithm that are not directly related to IEDs.Approach.In this study, we explore the background characteristics of interictal EEG for automated and more reliable diagnosis of epilepsy. Specifically, we investigate features based on univariate temporal measures (UTMs), spectral, wavelet, Stockwell, connectivity, and graph metrics of EEGs, besides patient-related information (age and vigilance state). The evaluation is performed on a sizeable cohort of routine scalp EEGs (685 epileptic EEGs and 1229 normal EEGs) from five centers across Singapore, USA, and India.Main results.In comparison with the current literature, we obtained an improved Leave-One-Subject-Out (LOSO) cross-validation (CV) area under the curve (AUC) of 0.871 (Balanced Accuracy (BAC) of 80.9%) with a combination of three features (IED rate, and Daubechies and Morlet wavelets) for the classification of EEGs with IEDs vs. normal EEGs. The IED-independent feature UTM achieved a LOSO CV AUC of 0.809 (BAC of 74.4%). The inclusion of IED-independent features also helps to improve the EEG-level classification of epileptic EEGs with and without IEDs vs. normal EEGs, achieving an AUC of 0.822 (BAC of 77.6%) compared to 0.688 (BAC of 59.6%) for classification only based on the IED rate. Specifically, the addition of IED-independent features improved the BAC by 21% in detecting epileptic EEGs that do not contain IEDs.Significance.These results pave the way towards automated detection of epilepsy. We are one of the first to analyze epileptic EEGs without IEDs, thereby opening up an underexplored option in epilepsy diagnosis.

Effect of perioperative seizures on mortality and recurrence in patients with brain metastases.

Objective: To identify the independent risk factors for 30-day perioperative seizures, as well as to evaluate the effect of perioperative seizures on overall mortality and tumor recurrence among patients who underwent surgical resection of brain metastases. Methods: Patients who underwent surgical resection of brain metastases at our institution between 2011 and 2019 were included. 30-day perioperative seizures were defined as the presence of any preoperative or postoperative seizures diagnosed by a neurosurgeon or neurologist within 30 days of metastases resection. Independent risk factors for 30-day perioperative seizures were evaluated using multivariate logistic regression models. Kaplan-Meier plots and Cox regression models were constructed to evaluate the effects of 30-day perioperative seizures on overall mortality and tumor recurrence. Subgroup analyses were conducted for 30-day preoperative and 30-day postoperative seizures. Results: A total of 158 patients were included in the analysis. The mean (SD) age was 59.3 (12.0) years, and 20 (12.7%) patients had 30-day perioperative seizures. The presence of 30-day preoperative seizures (OR=41.4; 95% CI=4.76, 924; p=0.002) was an independent risk factor for 30-day postoperative seizures. Multivariate Cox regression revealed that any 30-day perioperative seizure (HR=3.25; 95% CI=1.60, 6.62; p=0.001) was independently and significantly associated with overall mortality but not tumor recurrence (HR=1.95; 95% CI=0.78, 4.91; p=0.154). Conclusions: Among patients with resected brain metastases, the presence of any 30-day perioperative seizure was independently associated with overall mortality. This suggests that 30-day perioperative seizures may be a prognostic marker of poor outcome. Further research evaluating this association as well as the effect of perioperative antiepileptic drugs in patients with resected brain metastases may be warranted.

Using continuous electroencephalography in the management of delayed cerebral ischemia following subarachnoid hemorrhage.

BACKGROUND: Using clinical parameters to identify and monitor treatment response in patients with delayed cerebral ischemia (DCI) following subarachnoid hemorrhage is challenging. We sought to determine whether continuous electroencephalography (CEEG) aids the prediction of the clinical course and response to treatment of DCI. METHODS: Patients deemed high-risk for DCI based on the modified Fisher scale were prospectively monitored. A novel CEEG parameter measuring relative alpha power and variability in the anterior brain quadrants termed composite alpha index (CAI) was graphically displayed. Predictions of the status of patients for the ensuing day were made by an independent reviewer, first using clinical data then repeated following the addition of CAI trends. These were compared to the actual clinical state. The reviewer was blinded to the presence and treatment of DCI. Patients with DCI were further studied by trending the daily mean alpha power against the modulation of treatment and clinical evolution. RESULTS: Fifty-nine predictions were made in 12 patients (mean age 54.3 years, range 35-70; nine females) with Hunt-Hess grades ranging I-V. Sensitivity of predicting clinical deterioration with CEEG improved from 40 to 67% and clinical improvement from 8 to 50%. In three patients, CEEG was predictive greater than 24 h prior to clinical change. Tracking the daily mean alpha power accurately identified DCI recurrence and poor responders to first-line therapy at pre-clinical stages. CONCLUSION: CEEG is a useful non-invasive tool to supplement routine clinical parameters in the prediction of DCI. It can dynamically monitor the response to treatment and might aid pre-clinical management decisions.

Automated Adult Epilepsy Diagnostic Tool Based on Interictal Scalp Electroencephalogram Characteristics: A Six-Center Study.

The diagnosis of epilepsy often relies on a reading of routine scalp electroencephalograms (EEGs). Since seizures are highly unlikely to be detected in a routine scalp EEG, the primary diagnosis depends heavily on the visual evaluation of Interictal Epileptiform Discharges (IEDs). This process is tedious, expert-centered, and delays the treatment plan. Consequently, the development of an automated, fast, and reliable epileptic EEG diagnostic system is essential. In this study, we propose a system to classify EEG as epileptic or normal based on multiple modalities extracted from the interictal EEG. The ensemble system consists of three components: a Convolutional Neural Network (CNN)-based IED detector, a Template Matching (TM)-based IED detector, and a spectral feature-based classifier. We evaluate the system on datasets from six centers from the USA, Singapore, and India. The system yields a mean Leave-One-Institution-Out (LOIO) cross-validation (CV) area under curve (AUC) of 0.826 (balanced accuracy (BAC) of 76.1%) and Leave-One-Subject-Out (LOSO) CV AUC of 0.812 (BAC of 74.8%). The LOIO results are found to be similar to the interrater agreement (IRA) reported in the literature for epileptic EEG classification. Moreover, as the proposed system can process routine EEGs in a few seconds, it may aid the clinicians in diagnosing epilepsy efficiently.

Time-Frequency Decomposition of Scalp Electroencephalograms Improves Deep Learning-Based Epilepsy Diagnosis.

Epilepsy diagnosis based on Interictal Epileptiform Discharges (IEDs) in scalp electroencephalograms (EEGs) is laborious and often subjective. Therefore, it is necessary to build an effective IED detector and an automatic method to classify IED-free versus IED EEGs. In this study, we evaluate features that may provide reliable IED detection and EEG classification. Specifically, we investigate the IED detector based on convolutional neural network (ConvNet) with different input features (temporal, spectral, and wavelet features). We explore different ConvNet architectures and types, including 1D (one-dimensional) ConvNet, 2D (two-dimensional) ConvNet, and noise injection at various layers. We evaluate the EEG classification performance on five independent datasets. The 1D ConvNet with preprocessed full-frequency EEG signal and frequency bands (delta, theta, alpha, beta) with Gaussian additive noise at the output layer achieved the best IED detection results with a false detection rate of 0.23/min at 90% sensitivity. The EEG classification system obtained a mean EEG classification Leave-One-Institution-Out (LOIO) cross-validation (CV) balanced accuracy (BAC) of 78.1% (area under the curve (AUC) of 0.839) and Leave-One-Subject-Out (LOSO) CV BAC of 79.5% (AUC of 0.856). Since the proposed classification system only takes a few seconds to analyze a 30-min routine EEG, it may help in reducing the human effort required for epilepsy diagnosis.

Multi-Center Validation Study of Automated Classification of Pathological Slowing in Adult Scalp Electroencephalograms Via Frequency Features.

Pathological slowing in the electroencephalogram (EEG) is widely investigated for the diagnosis of neurological disorders. Currently, the gold standard for slowing detection is the visual inspection of the EEG by experts, which is time-consuming and subjective. To address those issues, we propose three automated approaches to detect slowing in EEG: Threshold-based Detection System (TDS), Shallow Learning-based Detection System (SLDS), and Deep Learning-based Detection System (DLDS). These systems are evaluated on channel-, segment-, and EEG-level. The three systems perform prediction via detecting slowing at individual channels, and those detections are arranged in histograms for detection of slowing at the segment- and EEG-level. We evaluate the systems through Leave-One-Subject-Out (LOSO) cross-validation (CV) and Leave-One-Institution-Out (LOIO) CV on four datasets from the US, Singapore, and India. The DLDS achieved the best overall results: LOIO CV mean balanced accuracy (BAC) of 71.9%, 75.5%, and 82.0% at channel-, segment- and EEG-level, and LOSO CV mean BAC of 73.6%, 77.2%, and 81.8% at channel-, segment-, and EEG-level. The channel- and segment-level performance is comparable to the intra-rater agreement (IRA) of an expert of 72.4% and 82%. The DLDS can process a 30 min EEG in 4 s and can be deployed to assist clinicians in interpreting EEGs.

BOLD signal changes preceding negative responses in EEG-fMRI in patients with focal epilepsy.

PURPOSE: In simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), increased neuronal activity from epileptiform spikes commonly elicits positive blood oxygenation level-dependent (BOLD) responses. Negative responses are also occasionally seen and have not been explained. Recent studies describe BOLD signal changes before focal EEG spikes. We aimed to systematically study if the undershoot of a preceding positive response might explain the negative BOLD seen in the focus. METHODS: Eighty-two patients with focal epilepsy who underwent EEG-fMRI at 3T were retrospectively studied. Studies with a focal negative BOLD response in the region of the spike field were reanalyzed using models with hemodynamic response functions (HRFs) peaking from -9 to +9 s around the spike. RESULTS: Eight patients met the inclusion criteria, showing negative BOLD responses in the spike field on standard analysis. None had positive BOLD responses immediately adjacent to the areas of deactivation. Regions of deactivation were found to have congruent preceding positive responses in two cases. These early activations were seen at the combined maps of -5 to -9 s. DISCUSSION: This study indicates that in a small proportion of patients with focal epilepsy in whom the standard analysis reveals focal negative responses, an earlier positive BOLD response is probably the cause. The origin of negative BOLD signal changes in the focus as a result of an epileptic event remains, however, unexplained in most of the patients in whom it occurs.

Automated Detection of Interictal Epileptiform Discharges from Scalp Electroencephalograms by Convolutional Neural Networks.

Visual evaluation of electroencephalogram (EEG) for Interictal Epileptiform Discharges (IEDs) as distinctive biomarkers of epilepsy has various limitations, including time-consuming reviews, steep learning curves, interobserver variability, and the need for specialized experts. The development of an automated IED detector is necessary to provide a faster and reliable diagnosis of epilepsy. In this paper, we propose an automated IED detector based on Convolutional Neural Networks (CNNs). We have evaluated the proposed IED detector on a sizable database of 554 scalp EEG recordings (84 epileptic patients and 461 nonepileptic subjects) recorded at Massachusetts General Hospital (MGH), Boston. The proposed CNN IED detector has achieved superior performance in comparison with conventional methods with a mean cross-validation area under the precision-recall curve (AUPRC) of 0.838[Formula: see text]±[Formula: see text]0.040 and false detection rate of 0.2[Formula: see text]±[Formula: see text]0.11 per minute for a sensitivity of 80%. We demonstrated the proposed system to be noninferior to 30 neurologists on a dataset from the Medical University of South Carolina (MUSC). Further, we clinically validated the system at National University Hospital (NUH), Singapore, with an agreement accuracy of 81.41% with a clinical expert. Moreover, the proposed system can be applied to EEG recordings with any arbitrary number of channels.