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Objective: In patients with medically refractory focal epilepsy, stereotactic‐electroencephalography (SEEG) can aid in localizing epileptogenic regions for surgical treatment. SEEG, however, requires long hospitalizations to record seizures, and ictal interpretation can be incomplete or inaccurate. Our recent work showed that non‐directed resting‐state analyses may identify brain regions as epileptogenic or uninvolved. Our present objective is to map epileptogenic networks in greater detail and more accurately identify seizure‐onset regions using directed resting‐state SEEG connectivity. Methods: In 25 patients with focal epilepsy who underwent SEEG, 2 minutes of resting‐state, artifact‐free, SEEG data were selected and functional connectivity was estimated. Using standard clinical interpretation, brain regions were classified into four categories: ictogenic, early propagation, irritative, or uninvolved. Three non‐directed connectivity measures (mutual information [MI] strength, and imaginary coherence between and within regions) and four directed measures (partial directed coherence [PDC] and directed transfer function [DTF], inward and outward strength) were calculated. Logistic regression was used to generate a predictive model of ictogenicity. Results: Ictogenic regions had the highest and uninvolved regions had the lowest MI strength. Although both PDC and DTF inward strengths were highest in ictogenic regions, outward strengths did not differ among categories. A model incorporating directed and nondirected connectivity measures demonstrated an area under the receiver‐operating characteristic (ROC) curve (AUC) of 0.88 in predicting ictogenicity of individual regions. The AUC of this model was 0.93 when restricted to patients with favorable postsurgical seizure outcomes. Significance: Directed connectivity measures may help identify epileptogenic networks without requiring ictal recordings. Greater inward but not outward connectivity in ictogenic regions at rest may represent broad inhibitory input to prevent seizure generation. [ABSTRACT FROM AUTHOR]

In 2011, the American Academy of Neurology ( AAN) established eight epilepsy quality measures ( EQMs) for chronic epilepsy treatment to address deficits in quality of care. This study assesses the relationship between adherence to these EQMs and epilepsy-related adverse hospitalizations ( ERAHs). A retrospective chart review of 475 new epilepsy clinic patients with an ICD-9 code 345.1-9 between 2010 and 2012 was conducted. Patient demographics, adherence to AAN guidelines, and annual number of ERAHs were assessed. Fisher's exact test was used to assess the relationship between adherence to guidelines (as well as socioeconomic variables) and the presence of one or more ERAH per year. Of the eight measures, only documentation of seizure frequency, but not seizure type, correlated with ERAH (relative risk [ RR] 0.343, 95% confidence interval [CI] 0.176-0.673, p = 0.010). Among patients in the intellectually disabled population (n = 70), only review/request of neuroimaging correlated with ERAH ( RR 0.128, 95% CI 0.016-1.009, p = 0.004). ERAHs were more likely in African American patients ( RR 2.451, 95% CI 1.377-4.348, p = 0.008), Hispanic/Latino patients ( RR 4.016, 95% CI 1.721-9.346, p = 0.016), Medicaid patients ( RR 2.217, 95% CI 1.258-3.712, p = 0.009), and uninsured patients ( RR 2.667, 95% CI 1.332-5.348, p = 0.013). In this retrospective series, adherence to the eight AAN quality measures did not strongly correlate with annual ERAH. [ABSTRACT FROM AUTHOR]

Objective To determine the feasibility of administering a diazepam nasal spray formulation (diazepam- NS) to adults with epilepsy during a generalized tonic-clonic seizure or in the postictal period following a tonic-clonic or other seizure type, to assess pharmacokinetics and to assess tolerability. Methods An open-label study was conducted in patients admitted to the epilepsy monitoring unit. Eligible patients received a single dose of diazepam- NS approximating 0.2 mg/kg. Plasma diazepam concentrations were measured serially up to 12 h postdose, and maximum observed plasma concentration (Cmax); time to maximum concentration (Tmax); and the area under the plasma concentration-time curve for time zero to last sampling time (AUC0-12) were estimated and dose-normalized. Pharmacodynamic assessments included Kaplan-Meier analysis to determine the time-to-next seizure. Safety and tolerability were assessed. Results Of the 78 patients who consented, 30 had treatment and pharmacokinetic data. Ten patients were treated during a convulsive tonic-clonic seizure, seven within 5 min following the last clonic jerk, and 13 in the postictal period ≥5 min after a tonic-clonic or following other seizure-types. Diazepam median Tmax was 45 min. Dose-normalized mean Cmax and AUC0-12 values of diazepam were comparable among patients regardless of the timing of diazepam- NS administration in relation to seizure. Of those treated, 65% were seizure-free during the 12-h observation period and 35% had post-dose seizures. Treatment was well tolerated, with no unexpected safety findings: 74% had mild and 25% had moderate adverse events. Nasopharyngeal signs were resolved by 12 h postdose. Significance Diazepam can be delivered in effective therapeutic concentrations by a nasal spray device during the convulsive phase of tonic-clonic seizures or in the postictal periods following tonic-clonic or other seizure types. [ABSTRACT FROM AUTHOR]

Objective Methods Results Significance Epilepsy is a common neurological disorder affecting 1% of the global population. Loss of consciousness in focal impaired awareness seizures (FIASs) and focal‐to‐bilateral tonic–clonic seizures (FBTCSs) can be devastating, but the mechanisms are not well understood. Although ictal activity and interictal connectivity changes have been noted, the network states of focal aware seizures (FASs), FIASs, and FBTCSs have not been thoroughly evaluated with network measures ictally.We obtained electrographic data from 74 patients with stereoelectroencephalography (SEEG). Sliding window band power, functional connectivity, and segregation were computed on preictal, ictal, and postictal data. Five‐minute epochs of wake, rapid eye movement sleep, and deep sleep were also extracted. Connectivity of subcortical arousal structures was analyzed in a cohort of patients with both SEEG and functional magnetic resonance imaging (fMRI). Given that custom neuromodulation of seizures is predicated on detection of seizure type, a convolutional neural network was used to classify seizure types.We found that in the frontoparietal association cortex, an area associated with consciousness, both consciousness‐impairing seizures (FIASs and FBTCSs) and deep sleep had increases in slow wave delta (1–4 Hz) band power. However, when network measures were employed, we found that only FIASs and deep sleep exhibited an increase in delta segregation and a decrease in gamma segregation. Furthermore, we found that only patients with FIASs had reduced subcortical‐to‐neocortical functional connectivity with fMRI versus controls. Finally, our deep learning network demonstrated an area under the curve of .75 for detecting consciousness‐impairing seizures.This study provides novel insights into ictal network measures in FASs, FIASs, and FBTCSs. Importantly, although both FIASs and FBTCSs result in loss of consciousness, our results suggest that ictal network changes in FIASs uniquely resemble those that occur during deep sleep. Our results may inform novel neuromodulation strategies for preservation of consciousness in epilepsy. [ABSTRACT FROM AUTHOR]