Search

Objective: This study was undertaken to evaluate how the challenges in the recruitment and retention of participants in clinical trials for focal onset epilepsy have changed over time. Methods: In this systematic analysis of randomized clinical trials of adjunct antiseizure medications for medication‐resistant focal onset epilepsy, we evaluated how the numbers of participants, sites, and countries have changed since the first such trial in 1990. We also evaluated the proportion of participants who completed each trial phase and their reasons for early trial exit. We analyzed these trends using mixed effects generalized linear models accounting for the influence of the number of trial sites and trial‐specific variability. Results: The number of participants per site has steadily decreased over decades, with recent trials recruiting fewer than five participants per site (reduction by.16 participants/site/year, p <.0001). Fewer participants also progressed from recruitment to randomization over time (odds ratio =.94/year, p =.014). Concurrently, there has been an increase in the placebo response over time (increase in median percent reduction of.4%/year, p =.02; odds ratio of increase in 50% responder rate of 1.03/year, p =.02), which was not directly associated with the number of sites per trial (p >.20). Significance: This historical analysis highlights the increasing challenges with participant recruitment and retention, as well as increasing placebo response. It serves as a call to action to change clinical trial design to address these challenges. [ABSTRACT FROM AUTHOR]

Objective: The objective of this study was to determine areas of consensus among an international panel of experts for the clinical presentation and diagnosis of epilepsy with eyelid myoclonia (EEM; formerly known as Jeavons syndrome) to improve a timely diagnosis. Methods: An international steering committee was convened of physicians and patients/caregivers with expertise in EEM. This committee summarized the current literature and identified an international panel of experts (comprising 25 physicians and five patients/caregivers). This international expert panel participated in a modified Delphi process, including three rounds of surveys to determine areas of consensus for the diagnosis of EEM. Results: There was a strong consensus that EEM is a female predominant generalized epilepsy syndrome with onset between 3 and 12 years of age and that eyelid myoclonia must be present to make the diagnosis. There was a strong consensus that eyelid myoclonia may go unrecognized for years prior to an epilepsy diagnosis. There was consensus that generalized tonic–clonic and absence seizures are typically or occasionally seen in patients. There was a consensus that atonic or focal seizures should lead to the consideration of reclassification or alternate diagnoses. There was a strong consensus that electroencephalography is required, whereas magnetic resonance imaging is not required for diagnosis. There was a strong consensus to perform genetic testing (either epilepsy gene panel or whole exome sequencing) when one or a combination of factors was present: family history of epilepsy, intellectual disability, or drug‐resistant epilepsy. Significance: This international expert panel identified multiple areas of consensus regarding the presentation and evaluation of EEM. These areas of consensus may be used to inform clinical practice to shorten the time to the appropriate diagnosis. [ABSTRACT FROM AUTHOR]

Objective: There are limited data about the treatment and management of epilepsy with eyelid myoclonia (EEM). The objective of this study was to determine areas of consensus among an international panel of experts for the management of EEM (formerly known as Jeavons syndrome). Methods: An international steering committee was convened of physicians and patients/caregivers with expertise in EEM. This committee summarized the current literature and identified an international panel of experts (comprising 25 physicians and five patients/caregivers). This panel participated in a modified Delphi process, including three rounds of surveys to determine areas of consensus for the treatment, other areas of management, and prognosis for EEM. Results: There was a strong consensus for valproic acid as the first‐line treatment, with levetiracetam or lamotrigine as preferable alternatives for women of childbearing age. There was a moderate consensus that ethosuximide and clobazam are also efficacious. There was a strong consensus to avoid sodium channel‐blocking medications, except for lamotrigine, as they may worsen seizure control. There was consensus that seizures typically persist into adulthood, with remission occurring in <50% of patients. There was less agreement about other areas of management, including dietary therapy, lens therapy, candidacy for driving, and outcome. Significance: This international expert panel identified multiple areas of consensus regarding the optimal management of EEM. These areas of consensus may inform clinical practice to improve the management of EEM. In addition, multiple areas with less agreement were identified, which highlight topics for further research. [ABSTRACT FROM AUTHOR]

Objective: In 2017, the American Academy of Neurology (AAN) convened the AAN Quality Measurement Set working group to define the improvement and maintenance of quality of life (QOL) as a key outcome measure in epilepsy clinical practice. A core outcome set (COS), defined as an accepted, standardized set of outcomes that should be minimally measured and reported in an area of health care research and practice, has not previously been defined for QOL in adult epilepsy. Methods: A cross‐sectional Delphi consensus study was employed to attain consensus from patients and caregivers on the QOL outcomes that should be minimally measured and reported in epilepsy clinical practice. Candidate items were compiled from QOL scales recommended by the AAN 2017 Quality Measurement Set. Inclusion criteria to participate in the Delphi study were adults with drug‐resistant epilepsy diagnosed by a physician, no prior diagnosis of psychogenic nonepileptic seizures or a cognitive and/or developmental disability, or caregivers of patients meeting these criteria. Results: A total of 109 people satisfied inclusion/exclusion criteria and took part in Delphi Round 1 (patients, n = 95, 87.2%; caregivers, n = 14, 12.8%), and 55 people from Round 1 completed Round 2 (patients, n = 43, 78.2%; caregivers, n = 12, 21.8%). One hundred three people took part in the final consensus round. Consensus was attained by patients/caregivers on a set of 36 outcomes that should minimally be included in the QOL COS. Of these, 32 of the 36 outcomes (88.8%) pertained to areas outside of seizure frequency and severity. Significance: Using patient‐centered Delphi methodology, this study defines the first COS for QOL measurement in clinical practice for adults with drug‐resistant epilepsy. This set highlights the diversity of factors beyond seizure frequency and severity that impact QOL in epilepsy. [ABSTRACT FROM AUTHOR]

Objective: We conducted clinical testing of an automated Bayesian machine learning algorithm (Epilepsy Seizure Assessment Tool [EpiSAT]) for outpatient seizure risk assessment using seizure counting data, and validated performance against specialized epilepsy clinician experts. Methods: We conducted a prospective longitudinal study of EpiSAT performance against 24 specialized clinician experts at three tertiary referral epilepsy centers in the United States. Accuracy, interrater reliability, and intra‐rater reliability of EpiSAT for correctly identifying changes in seizure risk (improvements, worsening, or no change) were evaluated using 120 seizures from four synthetic seizure diaries (seizure risk known) and 120 seizures from four real seizure diaries (seizure risk unknown). The proportion of observed agreement between EpiSAT and clinicians was evaluated to assess compatibility of EpiSAT with clinical decision patterns by epilepsy experts. Results: EpiSAT exhibited substantial observed agreement (75.4%) with clinicians for assessing seizure risk. The mean accuracy of epilepsy providers for correctly assessing seizure risk was 74.7%. EpiSAT accurately identified seizure risk in 87.5% of seizure diary entries, corresponding to a significant improvement of 17.4% (P =.002). Clinicians exhibited low‐to‐moderate interrater reliability for seizure risk assessment (Krippendorff's α = 0.46) with good intrarater reliability across a 4‐ to 12‐week evaluation period (Scott's π = 0.89). Significance: These results validate the ability of EpiSAT to yield objective clinical recommendations on seizure risk which follow decision patterns similar to those from specialized epilepsy providers, but with improved accuracy and reproducibility. This algorithm may serve as a useful clinical decision support system for quantitative analysis of clinical seizure frequency in clinical epilepsy practice. [ABSTRACT FROM AUTHOR]

Neuroimaging techniques applied to a variety of organisms—from zebrafish, to rodents to humans—can offer valuable insights into neuronal network properties and their dysfunction in epilepsy. A wide range of imaging methods used to monitor neuronal circuits and networks during evoked seizures in animal models and advances in functional magnetic resonance imaging (fMRI) applied to patients with epilepsy were discussed during the XIV Workshop on Neurobiology of Epilepsy (XIV WONOEP) organized in 2017 by the Neurobiology Commission of the International League Against Epilepsy (ILAE). We review the growing number of technological approaches developed, as well as the current state of knowledge gained from studies applying these advanced imaging approaches to epilepsy research. [ABSTRACT FROM AUTHOR]

Objective Low-cost evidence-based tools are needed to facilitate the early identification of patients with possible psychogenic nonepileptic seizures ( PNES). Prior to accurate diagnosis, patients with PNES do not receive interventions that address the cause of their seizures and therefore incur high medical costs and disability due to an uncontrolled seizure disorder. Both seizures and comorbidities may contribute to this high cost. Methods Based on data from 1,365 adult patients with video-electroencephalography-confirmed diagnoses from a single center, we used logistic and Poisson regression to compare the total number of comorbidities, number of medications, and presence of specific comorbidities in five mutually exclusive groups of diagnoses: epileptic seizures ( ES) only, PNES only, mixed PNES and ES, physiologic nonepileptic seizurelike events, and inconclusive monitoring. To determine the diagnostic utility of comorbid diagnoses and medication history to differentiate PNES only from ES only, we used multivariate logistic regression, controlling for sex and age, trained using a retrospective database and validated using a prospective database. Results Our model differentiated PNES only from ES only with a prospective accuracy of 78% (95% confidence interval =72-84%) and area under the curve of 79%. With a few exceptions, the number of comorbidities and medications was more predictive than a specific comorbidity. Comorbidities associated with PNES were asthma, chronic pain, and migraines (p < 0.01). Comorbidities associated with ES were diabetes mellitus and nonmetastatic neoplasm (p < 0.01). The population-level analysis suggested that patients with mixed PNES and ES may be a population distinct from patients with either condition alone. Significance An accurate patient-reported medical history and medication history can be useful when screening for possible PNES. Our prospectively validated and objective score may assist in the interpretation of the medication and medical history in the context of the seizure description and history. [ABSTRACT FROM AUTHOR]

Objective Our objective was to develop a generalized linear mixed model for predicting seizure count that is useful in the design and analysis of clinical trials. This model also may benefit the design and interpretation of seizure-recording paradigms. Most existing seizure count models do not include children, and there is currently no consensus regarding the most suitable model that can be applied to children and adults. Therefore, an additional objective was to develop a model that accounts for both adult and pediatric epilepsy. Methods Using data from , a patient-reported seizure diary tool with >1.2 million recorded seizures across 8 years, we evaluated the appropriateness of Poisson, negative binomial, zero-inflated negative binomial, and modified negative binomial models for seizure count data based on minimization of the Bayesian information criterion. Generalized linear mixed-effects models were used to account for demographic and etiologic covariates and for autocorrelation structure. Holdout cross-validation was used to evaluate predictive accuracy in simulating seizure frequencies. Results For both adults and children, we found that a negative binomial model with autocorrelation over 1 day was optimal. Using holdout cross-validation, the proposed model was found to provide accurate simulation of seizure counts for patients with up to four seizures per day. Significance The optimal model can be used to generate more realistic simulated patient data with very few input parameters. The availability of a parsimonious, realistic virtual patient model can be of great utility in simulations of phase II/ III clinical trials, epilepsy monitoring units, outpatient biosensors, and mobile Health (mHealth) applications. [ABSTRACT FROM AUTHOR]

Objective Temporal lobe epilepsy ( TLE) affects brain areas beyond the temporal lobes due to connections of the hippocampi and other temporal lobe structures. Using functional connectivity magnetic resonance imaging ( MRI), we determined the changes of hippocampal networks in TLE to assess for a more complete distribution of abnormality. Methods Regions of interest ( ROIs) were defined in the right and left hippocampi in three groups of participants: left TLE (n = 13), right TLE (n = 11), and healthy controls (n = 16). Brain regions functionally connected to these ROIs were identified by correlating resting-state low-frequency functional MRI (f MRI) blood oxygenation level-dependent (BOLD) signal fluctuations. The grouped results were compared using independent sample t-test. Results TLE was associated with increased hippocampal connectivity involving several key areas of the limbic network (temporal lobe, insula, thalamus), frontal lobes, angular gyrus, basal ganglia, brainstem, and cerebellum, along with reduced connectivity involving areas of the sensorimotor cortex (visual, somatosensory, auditory, primary motor) and the default mode network (precuneus). Left TLE had more marked connectivity changes than right TLE. Significance The observed connectivity changes in TLE indicate dysfunctional networks that underlie widespread brain involvement in TLE. There are identifiable differences in the connectivity of the hippocampi between left and right TLE. [ABSTRACT FROM AUTHOR]

Interictal electroencephalography (EEG) has clinically meaningful limitations in its sensitivity and specificity in the diagnosis of epilepsy because of its dependence on the occurrence of epileptiform discharges. We have developed a computer-aided diagnostic (CAD) tool that operates on the absolute spectral energy of the routine EEG and has both substantially higher sensitivity and negative predictive value than the identification of interictal epileptiform discharges. Our approach used a multilayer perceptron to classify 156 patients admitted for video-EEG monitoring. The patient population was diagnostically diverse; 87 were diagnosed with either generalized or focal seizures. The remainder of the patients were diagnosed with nonepileptic seizures. The sensitivity was 92% (95% confidence interval [CI] 85-97%) and the negative predictive value was 82% (95% CI 67-92%). We discuss how these findings suggest that this CAD can be used to supplement event-based analysis by trained epileptologists. [ABSTRACT FROM AUTHOR]