It is currently unknown how often and in which ways a genetic diagnosis given to a patient with epilepsy is associated with clinical management and outcomes. To evaluate how genetic diagnoses in patients with epilepsy are associated with clinical management and outcomes. This was a retrospective cross-sectional study of patients referred for multigene panel testing between March 18, 2016, and August 3, 2020, with outcomes reported between May and November 2020. The study setting included a commercial genetic testing laboratory and multicenter clinical practices. Patients with epilepsy, regardless of sociodemographic features, who received a pathogenic/likely pathogenic (P/LP) variant were included in the study. Case report forms were completed by all health care professionals. Genetic test results. Clinical management changes after a genetic diagnosis (ie, 1 P/LP variant in autosomal dominant and X-linked diseases; 2 P/LP variants in autosomal recessive diseases) and subsequent patient outcomes as reported by health care professionals on case report forms. Among 418 patients, median (IQR) age at the time of testing was 4 (1-10) years, with an age range of 0 to 52 years, and 53.8% (n = 225) were female individuals. The mean (SD) time from a genetic test order to case report form completion was 595 (368) days (range, 27-1673 days). A genetic diagnosis was associated with changes in clinical management for 208 patients (49.8%) and usually (81.7% of the time) within 3 months of receiving the result. The most common clinical management changes were the addition of a new medication (78 [21.7%]), the initiation of medication (51 [14.2%]), the referral of a patient to a specialist (48 [13.4%]), vigilance for subclinical or extraneurological disease features (46 [12.8%]), and the cessation of a medication (42 [11.7%]). Among 167 patients with follow-up clinical information available (mean [SD] time, 584 [365] days), 125 (74.9%) reported positive outcomes, 108 (64.7%) reported reduction or elimination of seizures, 37 (22.2%) had decreases in the severity of other clinical signs, and 11 (6.6%) had reduced medication adverse effects. A few patients reported worsening of outcomes, including a decline in their condition (20 [12.0%]), increased seizure frequency (6 [3.6%]), and adverse medication effects (3 [1.8%]). No clinical management changes were reported for 178 patients (42.6%). Results of this cross-sectional study suggest that genetic testing of individuals with epilepsy may be materially associated with clinical decision-making and improved patient outcomes.
Hyperventilation (HV) is most effective in activation of generalized absence seizures during routine EEG studies. It is also used as an activation technique in the epilepsy monitoring unit, with limited data on its utility. This prospective study was undertaken to determine the effectiveness of daily hyperventilation sessions in precipitating events in the epilepsy monitoring unit. The authors performed hyperventilation for 3 minutes on a daily basis on patients admitted to our epilepsy monitoring unit. They considered events to be activated by HV if they occurred during or within 3 minutes of the procedure. They asked the patient if the precipitated event was typical, and compared the precipitated events to those that occurred spontaneously during the monitoring period. They evaluated 79 consecutive patients; 54 had localization related epilepsy, 24 had psychogenic nonepileptic events only, and 1 patient had spells of unknown nature. Six patients with epilepsy had epileptic seizure activation (three auras, two complex partial seizures and one secondarily generalized tonic clonic seizures), and eight patients with nonepileptic spells had precipitation of nonepileptic events. Two patients with both epilepsy and psychogenic nonepileptic events had a nonepileptic event activated. Spontaneous and activated epileptic seizures did not differ in their clinical characteristics. Daily supervised HV is effective in inducing partial seizures as well as psychogenic nonepileptic events in the epilepsy monitoring unit. Daily HV may be effective in shortening the duration of video EEG monitoring, consequently reducing its cost.
Summary 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 EQM s 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 ERAH s 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). ERAH s 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 .
The goal of the project is to determine characteristics of academic neurophysiologist EEG interpreters (EEGers), which predict good interrater agreement (IRA) and to determine the number of EEGers needed to develop an ideal standardized testing and training data set for epileptiform transient (ET) detection algorithms.A three-phase scoring method was used. In phase 1, 19 EEGers marked the location of ETs in two hundred 30-second segments of EEG from 200 different patients. In phase 2, EEG events marked by at least 2 EEGers were annotated by 18 EEGers on a 5-point scale to indicate whether they were ETs. In phase 3, a third opinion was obtained from EEGers on any inconsistencies between phase 1 and phase 2 scoring.The IRA for the 18 EEGers was only fair. A select group of the EEGers had good IRA and the other EEGers had low IRA. Board certification by the American Board of Clinical Neurophysiology was associated with better IRA performance but other board certifications, years of fellowship training, and years of practice were not. As the number of EEGers used for scoring is increased, the amount of change in the consensus opinion decreases steadily and is quite low as the group size approaches 10.The IRA among EEGers varies considerably. The EEGers must be tested before use as scorers for ET annotation research projects. The American Board of Clinical Neurophysiology certification is associated with improved performance. The optimal size for a group of experts scoring ETs in EEG is probably in the 6 to 10 range.
Background For patients with drug-resistant epilepsy, surgery may be effective in controlling their disease. Surgical evaluation may involve localization of the language areas using functional magnetic resonance imaging (fMRI) or Wada testing. We evaluated the accuracy of task-based fMRI versus Wada-based language lateralization in a cohort of our epilepsy patients. Methods In a single-center, retrospective analysis, we identified patients with medically intractable epilepsy who participated in presurgical language mapping (n = 35) with fMRI and Wada testing. Demographic variables and imaging metrics were obtained. We calculated the laterality index (LI) from task-evoked fMRI activation maps across language areas during auditory and reading tasks to determine lateralization. Possible scores for LI range from −1 (strongly left-hemisphere dominant) to 1 (strongly right-hemisphere dominant). Concordance between fMRI and Wada was estimated using Cohen’s Kappa coefficient. Association between the LI scores from the auditory and reading tasks was tested using Spearman’s rank correlation coefficient. Results The fMRI-based laterality indices were concordant with results from Wada testing in 91.4% of patients during the reading task ( κ = .55) and 96.9% of patients during the auditory task ( κ = .79). The mean LIs for the reading and auditory tasks were −0.52 ± 0.43 and −0.68 ± 0.42, respectively. The LI scores for the language and reading tasks were strongly correlated, r(30) = 0.57 ( p = 0.001). Conclusion Our findings suggest that fMRI is generally an accurate, low-risk alternative to Wada testing for language lateralization. However, when fMRI indicates atypical language lateralization (e.g., bilateral dominance), patients may benefit from subsequent Wada testing or intraoperative language mapping.
Epitel has developed Epilog, a miniature, wireless, wearable electroencephalography (EEG) sensor. Four Epilog sensors are combined as part of Epitel's Remote EEG Monitoring platform (REMI) to create 10 channels of EEG for remote patient monitoring. REMI is designed to provide comprehensive spatial EEG recordings that can be administered by non-specialized medical personnel in any medical center. The purpose of this study was to determine how accurate epileptologists are at remotely reviewing Epilog sensor EEG in the 10-channel “REMI montage,” with and without seizure detection support software. Three board certified epileptologists reviewed the REMI montage from 20 subjects who wore four Epilog sensors for up to 5 days alongside traditional video-EEG in the EMU, 10 of whom experienced a total of 24 focal-onset electrographic seizures and 10 of whom experienced no seizures or epileptiform activity. Epileptologists randomly reviewed the same datasets with and without clinical decision support annotations from an automated seizure detection algorithm tuned to be highly sensitive. Blinded consensus review of unannotated Epilog EEG in the REMI montage detected people who were experiencing electrographic seizure activity with 90% sensitivity and 90% specificity. Consensus detection of individual focal onset seizures resulted in a mean sensitivity of 61%, precision of 80%, and false detection rate (FDR) of 0.002 false positives per hour (FP/h) of data. With algorithm seizure detection annotations, the consensus review mean sensitivity improved to 68% with a slight increase in FDR (0.005 FP/h). As seizure detection software, the automated algorithm detected people who were experiencing electrographic seizure activity with 100% sensitivity and 70% specificity, and detected individual focal onset seizures with a mean sensitivity of 90% and mean false alarm rate of 0.087 FP/h. This is the first study showing epileptologists' ability to blindly review EEG from four Epilog sensors in the REMI montage, and the results demonstrate the clinical potential to accurately identify patients experiencing electrographic seizures. Additionally, the automated algorithm shows promise as clinical decision support software to detect discrete electrographic seizures in individual records as accurately as FDA-cleared predicates.
