Singh, Jaysingh

Abstract Neuromodulation is approved for the treatment of drug‐resistant epilepsy. It has been increasingly utilized over the past two decades with the approval of deep brain stimulation (DBS) and responsive neurostimulation (RNS) in addition to vagus nerve stimulation (VNS)—particularly in patients who are not deemed to be good resective surgical candidates or in case of patient preference. In this seminar in epileptology article, we address learning objective 3.7 “Demonstrate knowledge of indications, limitations and risks for vagal nerve stimulation and other neuromodulation techniques” of the International League Against Epilepsy curriculum for epileptologists. We will review the indications for neuromodulation, device programming, surgical considerations for implantation, side effects, effects on sleep, and mood. This is complemented by case examples that provide perspective for trainees, along with an outlook on future directions for neuromodulation in epilepsy. This article aims to serve as a learning resource for trainees in neurology, clinical neurophysiology, and epileptology by providing guidance in how to navigate the landscape of neuromodulation in epilepsy.

AbstractWith continued advancement in computational technologies, the analysis of electroencephalography (EEG) has shifted from pure visual analysis to a noninvasive computational technique called EEG source imaging (ESI), which involves mathematical modeling of dipolar and distributed sources of a given scalp EEG pattern. ESI is a noninvasive phase I test for presurgical localization of the seizure onset zone in focal epilepsy. It is a relatively inexpensive modality, as it leverages scalp EEG and magnetic resonance imaging (MRI) data already collected typically during presurgical evaluation. With an adequate number of electrodes and combined with patient‐specific MRI‐based head models, ESI has proven to be a valuable and accurate clinical diagnostic tool for localizing the epileptogenic zone. Despite its advantages, however, ESI is routinely used at only a minority of epilepsy centers. This paper reviews the current evidence and practical fundamentals for using ESI of interictal and ictal epileptic activity during the presurgical evaluation of drug‐resistant patients. We identify common errors in processing and interpreting ESI studies, describe the differences in approach needed for localizing interictal and ictal EEG discharges through practical examples, and describe best practices for optimizing the diagnostic information available from these studies.

Introduction: Nonconvulsive seizures (NCSs) are common in critically ill adult patients with acute neurologic conditions. However, the effect of NCSs on patient outcome remains unclear. In this study, we aimed to determine the effect of NCSs on short-term outcome and to assess the clinical and EEG factors associated with NCSs. Methods: We retrospectively identified 219 adult patients from the EEG reporting system who underwent continuous EEG (cEEG) monitoring between January 2018 and June 2018. Patients with anoxic brain injury were excluded from the study. Clinical, laboratory, and EEG data were reviewed to determine potentially predictive factors of NCSs. The impact of NCSs on in-hospital mortality, length of stay, and disability on discharge was measured; an modified Rankin scale of three or greater was considered disabled. Results: Of the 219 patients included in our study, a total of 14% (n = 31) had NCSs on continuous EEG, of which 42% (n = 13) had their first seizure discharge recorded during the first hour of continuous EEG monitoring. The presence of clinical seizures before continuous EEG (odds ratio = 1.787; 95% confidence interval = 1.197–2.667, P = 0.0045), history of epilepsy (odds ratio = 1.508; 95% confidence interval = 1.027–2.215, P = 0.035), and comatose state (29 vs. 16%; P = 0.0006) were associated with NCSs. Among EEG characteristics, the presence of interictal epileptiform discharges (P < 0.0001), lateralized rhythmic delta activity (P = 0.02), and lateralized periodic discharges (P < 0.0001) were associated with NCSs. Nonconvulsive seizures were significantly associated with longer in-hospital stay (23.68 ± 24.84 vs. 17.14 ± 20.52; P = 0.036) and disability on discharge (87% [n = 27] vs. 13% [n = 4], P = 0.02). However, there was no significant association between NCS and in-hospital mortality (9.6% [n = 3] vs. 10.6% [n = 20]; P = 0.1). Conclusions: Nonconvulsive seizures are associated with longer in-hospital stay and disability on discharge but not with in-hospital mortality in adult patients.

Objective: After-hours EEG is increasingly used in hospital patients. Although the detection of seizures and interictal epileptiform discharges has been shown to be higher with prolonged EEG (pEEG) than routine-duration EEG, the relative value for particular indications can inform utilization. Method: The Mayo EEG Report System was queried for after-hours emergent routine EEG (ErEEG) and pEEG performed between January 2015 and June 2015. Total 296 after-hours ErEEG were identified, of which 140 converted into pEEG were included in the study for direct comparison of two modalities. Indications were categorized as: mental status changes, recent seizures rule out continued nonconvulsive seizures, spells, and prognosis after anoxic brain injury. Categorical data were analyzed using the McNemar and Fisher exact tests; a P value of 0.05 was considered significant. Result: Prolonged EEG was superior to ErEEG for detection of interictal epileptiform discharges (61 vs. 48/140, P = 0.004) and seizures (29 vs. 17/140, P = 0.012). Seizure detection was greater for pEEG than ErEEG for the indication of evaluating for subclinical seizures after recent observed clinical seizures (14/41 [34.1%] versus 4/41 [9.8%], P = 0.002). There was no significant difference between modalities for seizure detection in patients undergoing evaluation of spells or mental status changes without previous observed seizures. Detection of seizures on pEEG was higher for recordings greater than 24 hours (8/46, 17%, P = 0.014) and 48 hours (19/26, 73%, P < 0.001) than recordings less than 24 hours (2/68, 3%). Seizure detection was higher with pEEG in comatose patients than ErEEG (17/51, 33% vs. 12/89, 13%; P = 0.009). Conclusions: Increased value was demonstrated for pEEG over ErEEG in patients undergoing evaluation after observed recent clinical seizures and for coma. No significant difference was found between ErEEG and pEEG for seizure detection in the relatively small subgroups of patients with mental status changes other than coma and without preceding seizure or spells.

Summary Objective To validate predictive models for neural antibody positivity and immunotherapy response in epilepsy. Methods We conducted a retrospective study of epilepsy cases at Mayo Clinic (Rochester‐ MN ; Scottsdale‐ AZ , and Jacksonville‐ FL ) in whom autoimmune encephalopathy/epilepsy/dementia autoantibody testing profiles were requested (06/30/2014‐06/30/2016). An Antibody Prevalence in Epilepsy ( APE ) score, based on clinical characteristics, was assigned to each patient. Among patients who received immunotherapy, a Response to Immunotherapy in Epilepsy ( RITE ) score was assigned. Favorable seizure outcome was defined as >50% reduction of seizure frequency at the first follow‐up . Results Serum and cerebrospinal fluid (CSF) from 1,736 patients were sent to the Mayo Clinic Neuroimmunology Laboratory for neural autoantibody evaluation. Three hundred eighty‐seven of these patients met the diagnostic criteria for epilepsy. Central nervous system (CNS)–specific antibodies were detected in 44 patients. Certain clinical features such as new‐onset epilepsy, autonomic dysfunction, viral prodrome, faciobrachial dystonic seizures/oral dyskinesia, inflammatory CSF profile, and mesial temporal magnetic resonance imaging (MRI) abnormalities had a significant association with positive antibody results. A significantly higher proportion of antibody‐positive patients had an APE score ≥4 (97.7% vs. 21.6%, p < 0.01). Sensitivity and specificity of an APE score ≥4 to predict presence of specific neural auto‐antibody were 97.7% and 77.9%, respectively. In the subset of patients who received immunotherapy (77), autonomic dysfunction, faciobrachial dystonic seizures/oral dyskinesia, early initiation of immunotherapy, and presence of antibodies targeting plasma membrane proteins (cell‐surface antigens) were associated with favorable seizure outcome. Sensitivity and specificity of a RITE score ≥7 to predict favorable seizure outcome were 87.5% and 83.8%, respectively. Significance APE and RITE scores can aid diagnosis, treatment, and prognostication of autoimmune epilepsy. A PowerPoint slide summarizing this article is available for download in the Supporting Information section here .