Faculty Bibliography

Based on a multicenter cohort of people with anti-NMDA receptor encephalitis (anti-NMDARE), we describe seizure phenotypes, electroencephalographic (EEG) findings, and anti-seizure treatment strategies. We also investigated whether specific electrographic features are associated with persistent seizures or status epilepticus after acute presentation. In this retrospective cohort study, we reviewed records of children and adults with anti-NMDARE between 2010 and 2014 who were included in the Rare Epilepsy of New York City database, which included the text of physician notes from five academic medical centers. Clinical history (e.g., seizure semiology) and EEG features (e.g., background organization, slowing, epileptiform activity, seizures, sleep architecture, extreme delta brush) were abstracted. We compared clinical features associated with persistent seizures (ongoing seizures after one month from presentation) and status epilepticus, using bivariate and multivariable analyses. Among the 38 individuals with definite anti-NMDARE, 32 (84%) had seizures and 29 (76%) had seizures captured on EEG. Electrographic-only seizures were identified in five (13%) individuals. Seizures started at a median of four days after initial symptoms (IQR: 3-6 days). Frontal lobe-onset focal seizures were most common (n=12; 32%). Most individuals (31/38; 82%) were refractory to anti-seizure medications. Status epilepticus was associated with younger age (15 years [9-20] vs. 23 years [18-27]; p=0.04) and Hispanic ethnicity (30 [80%] vs. 8 [36%]; p=0.04). Persistent seizures (ongoing seizures after one month from presentation) were associated with younger age (nine years [3-14] vs. 22 years [15-28]; p<0.01). Measured electrographic features were not associated with persistent seizures. Seizures associated with anti-NMDARE are primarily focal seizures originating in the frontal lobes. Younger patients may be at increased risk of epileptogenesis and status epilepticus. Continuous EEG monitoring helps identify subclinical seizures, but specific EEG findings may not predict the severity or persistence of seizures during hospitalization.

Seizures present in childhood with infinite diversity. History alone may suffice for diagnosis in some cases; more often additional evidence is needed to clarify events of concern. Electroencephalography (EEG) is a primary methodology used for seizure identification and management. Pediatric and adolescent health care providers are increasingly asked to make decisions about when and how to refer patients for eventual monitoring and must then be able to confidently interpret any resulting report(s). Comprehensive literature review was undertaken to provide a succinct and up-to-date overview aimed at general and subspecialty non-neurologist pediatric and adolescent health care providers to not only convey a solid general understanding of EEG and what it entails for patients and their families, but also foster a deeper understanding of the indications for monitoring-and how to interpret documented findings. In plain language this resultant guide reviews EEG basics, provides a crash course in the various types of EEG available, discusses broad indications for epilepsy monitoring, guides counseling and management for patients and their families both before and after EEG, and ultimately aids in the interpretation of both findings and prognosis. This review should allow both primary and subspecialty non-neurologic pediatric and adolescent health care providers to better identify when and how to best utilize EEG as part of a larger comprehensive clinical approach, distinguishing and managing both epileptic and nonepileptic disorders of concern while fostering communication across providers to facilitate and coordinate better holistic long-term care of pediatric and adolescent patients.

Nocturnal events of wide variety and concern are frequently reported by patients and their caregivers. To evaluate suspected abnormal events, primary care physicians must first be familiar with normal behaviors, movements and breathing patterns. Abnormal nocturnal events can then be categorized as nocturnal seizure, parasomnia, sleep-related movement disorder or sleep-related breathing disorder. Diagnoses in the above categories can be made clinically; however, it is important to know when to refer for additional evaluation. Comprehensive literature review was undertaken of nocturnal and sleep-related disorders. This guide reviews nocturnal seizures, normal and abnormal nonepileptic movements and behaviors, discusses broad indications for referral for electroencephalography (EEG) or polysomnography (PSG), and guides counseling and management for patients and their families, ultimately aiding in interpretation of both findings and prognosis. Epilepsy syndromes can result in seizures during sleep or adjacent periods of wakefulness. Parasomnias and sleep-related movement disorders tend to also occur in childhood and may be distinguished clinically. Referral to additional specialists for specific studies including EEG or PSG can be necessary, while other times a knowledgeable and vigilant clinician can contribute to a prompt diagnosis based on clinical features. Nocturnal events often can be managed with parental reassurance and watchful waiting, but treatment or evaluation may be needed. Sleep-related breathing disorders are important to recognize as they present very differently in children than in adults and early intervention can be life-saving. This review should allow both primary and subspecialty non-neurologic pediatric and adolescent health care providers to better utilize EEG and PSG as part of a larger comprehensive clinical approach, distinguishing and managing both epileptic and nonepileptic nocturnal disorders of concern while fostering communication across providers to facilitate and coordinate better holistic long-term care of pediatric and adolescent patients.

OBJECTIVE:Sudden unexpected death in epilepsy (SUDEP) is an important cause of mortality in epilepsy. However, there is a gap in how often providers counsel patients about SUDEP. One potential solution is to electronically prompt clinicians to provide counseling via automated detection of risk factors in electronic medical records (EMRs). We evaluated (1) the feasibility and generalizability of using regular expressions to identify risk factors in EMRs and (2) barriers to generalizability. METHODS:Data included physician notes for 3000 patients from one medical center (home) and 1000 from five additional centers (away). Through chart review, we identified three SUDEP risk factors: (1) generalized tonic-clonic seizures, (2) refractory epilepsy, and (3) epilepsy surgery candidacy. Regular expressions of risk factors were manually created with home training data, and performance was evaluated with home test and away test data. Performance was evaluated by sensitivity, positive predictive value, and F-measure. Generalizability was defined as an absolute decrease in performance by <0.10 for away versus home test data. To evaluate underlying barriers to generalizability, we identified causes of errors seen more often in away data than home data. To demonstrate how small revisions can improve generalizability, we removed three "boilerplate" standard text phrases from away notes and repeated performance. RESULTS:We observed high performance in home test data (F-measure range = 0.86-0.90), and low to high performance in away test data (F-measure range = 0.53-0.81). After removing three boilerplate phrases, away performance improved (F-measure range = 0.79-0.89) and generalizability was achieved for nearly all measures. The only significant barrier to generalizability was use of boilerplate phrases, causing 104 of 171 errors (61%) in away data. SIGNIFICANCE/CONCLUSIONS:Regular expressions are a feasible and probably a generalizable method to identify variables related to SUDEP risk. Our methods may be implemented to create large patient cohorts for research and to generate electronic prompts for SUDEP counseling.