Tatum, William O

Abstract Emotional experiences during focal seizures are often misinterpreted as psychiatric disorders. We aimed to evaluate symptoms involving affective symptoms at seizure onset. We aimed to identify the most prevalent affective symptoms at seizure onset and characterize their localizing and lateralizing value. We performed a scoping review based on Preferred Reporting Items for Systematic reviews and Meta‐Analyses–extension for Scoping Reviews guidelines. A systematic search identified records from 4 databases: PubMed, Embase, CINAHL (via EBSCOhost), and Web of Science. Two reviewers independently screened titles/abstracts and full texts; discrepancies were resolved by consensus. This review focused on patients with focal seizures, as affective symptoms may occur in generalized epilepsies. The affective symptoms: fear, anxiety, panic, sadness, mystic, ecstatic, sexual, and mirth were identified, and semiology was evaluated in accordance with ILAE guidelines. Symptom onset, frequency, brain localization, and video‐EEG monitoring technique were evaluated to assess localization and lateralization of regional networks. Scalp EEG, invasive EEG recordings, and electrical stimulation were analyzed. A total of 1276 documents were identified, with 98 studies included for review. Fear was the most frequently reported ictal emotion, identified in 274 patients (66%), predominantly in temporal lobe epilepsy. Sadness and sexual, ecstatic symptoms were also consistently associated with temporal networks. Mirth was more frequently reported with frontal onset seizures. Evidence, primarily from Class IV studies, reported right hemispheric predominance for ecstasy, mystic, and sexual symptoms at seizure onset. Ictal affective symptoms at seizure onset yield localizing information. The limbic system, especially the temporal lobe, followed by the frontal lobe, was the most common site of origin. Fear was the most common spontaneous and electrically elicited symptom, followed by anxiety. While bi‐hemispheric lateralization occurred, right lateralization predominated. Recognizing paroxysmal affective symptoms as ictal phenomena may reduce misdiagnosis and aid presurgical evaluation in drug‐resistant focal epilepsy.

Abstract Objective To measure the relative levels of signal and noise in expert diagnosis of epilepsy. Methods Twenty multinational epileptologists independently reviewed 50 vignettes of adult and pediatric patients presenting with suspected seizure(s) on two separate occasions with a ≥30‐day washout period. Experts provided a diagnosis of epilepsy or non‐epilepsy based on clinical information and, if requested, routine EEG and neuroimaging data. Cases had an established clinical diagnosis of epilepsy or non‐epilepsy based on capture of habitual paroxysmal events on video‐EEG or long‐term clinical follow‐up. Experts' judgments were analyzed to decompose variability into different sources: signal (objective differences between cases), level noise (experts' bias toward over/under‐diagnosis), pattern noise (experts' idiosyncratic reactions to specific case features), and occasion noise (inconsistency across occasions). Results The probability of an expert making a different diagnosis for a given case on two different occasions was 16%. The probability of two different experts making a different diagnosis for the same case was 26%. Signal (case “difficulty”) accounted for 66–69% of total variation, with 31–34% attributable to noise. Level noise was the largest contributor in the absence of EEG/neuroimaging results (23%), while pattern noise dominated when test results were available (24%). Occasion noise contributed relatively little (1%) but was still sufficient to cause diagnostic reversals in 16–22% between occasions. Significance The degree of noise in expert diagnosis of epilepsy is substantial, stemming primarily from physicians' idiosyncratic interpretations of case features and variable dispositions toward over‐ or under‐diagnosis. Strategies to improve reliability are needed, including standardized data collection protocols and structured decision algorithms. For “difficult cases,” where expert reliability and accuracy are lowest, our findings support current clinical practice which favors early referral for video‐EEG monitoring over reliance on diagnostic anchoring. This diagnostic pathway may become more accessible with advances in EEG technology (e.g., wearable devices) and artificial intelligence.

Abstract The International League Against Epilepsy (ILAE) has updated the operational classification of epileptic seizures, building upon the framework established in 2017. This revision, informed by the implementation experience, involved a working group appointed by the ILAE Executive Committee. Comprising 37 members from all ILAE regions, the group utilized a modified Delphi process, requiring a consensus threshold of more than two thirds for any proposal. Following public comments, the Executive Committee appointed seven additional experts to the revision task force to address and incorporate the issues raised, as appropriate. The updated classification maintains four main seizure classes: Focal, Generalized, Unknown (whether focal or generalized), and Unclassified. Taxonomic rules distinguish classifiers, which are considered to reflect biological classes and directly impact clinical management, from descriptors, which indicate other important seizure characteristics. Focal seizures and those of unknown origin are further classified by the patient's state of consciousness (impaired or preserved) during the seizure, defined operationally through clinical assessment of awareness and responsiveness. If the state of consciousness is undetermined, the seizure is classified under the parent term, that is, the main seizure class (focal seizure or seizure of unknown origin). Generalized seizures are grouped into absence seizures, generalized tonic–clonic seizures, and other generalized seizures, now including recognition of negative myoclonus as a seizure type. Seizures are described in the basic version as with or without observable manifestations, whereas an expanded version utilizes the chronological sequence of seizure semiology. This updated classification comprises four main classes and 21 seizure types. Special emphasis was placed on ensuring translatability into languages beyond English. Its aim is to establish a common language for all health care professionals involved in epilepsy care, from resource‐limited areas to highly specialized centers, and to provide accessible terms for patients and caregivers.

Abstract Tumor-related epilepsy (TRE) is a frequent and major consequence of brain tumors. Management of TRE is required throughout the course of disease and a deep understanding of diagnosis and treatment is key to improving quality of life. Gross total resection is favored from both an oncologic and epilepsy perspective. Shared mechanisms of tumor growth and epilepsy exist, and emerging data will provide better targeted therapy options. Initial treatment with antiseizure medications (ASM) in conjunction with surgery and/or chemoradiotherapy is typical. The first choice of ASM is critical to optimize seizure control and tolerability considering the effects of the tumor itself. These agents carry a potential for drug–drug interactions and therefore knowledge of mechanisms of action and interactions is needed. A review of adverse effects is necessary to guide ASM adjustments and decision-making. This review highlights the essential aspects of diagnosis and treatment of TRE with ASMs, surgery, chemotherapy, and radiotherapy while indicating areas of uncertainty. Future studies should consider the use of a standardized method of seizure tracking and incorporating seizure outcomes as a primary endpoint of tumor treatment trials.

AbstractBackground and purposeCerebral amyloid angiopathy (CAA) is a common cause of intracranial hemorrhage (ICH), which is a risk factor for seizures. The incidence and risk factors of seizures associated with a heterogeneous cohort of CAA patients have not been studied.MethodsWe conducted a retrospective study of patients with CAA treated at Mayo Clinic Florida between 1 January 2015 and 1 January 2021. CAA was defined using the modified Boston criteria version 2.0. We analyzed electrophysiological and clinical features, and comorbidities including lobar ICH, nontraumatic cortical/convexity subarachnoid hemorrhage (cSAH), superficial siderosis, and inflammation (CAA with inflammation [CAA‐ri]). Cognition and mortality were secondary outcomes. Univariate and multivariate analyses were performed to determine risk of seizures relative to clinical presentation.ResultsTwo hundred eighty‐four patients with CAA were identified, with median follow‐up of 35.7 months (interquartile range = 13.5–61.3 months). Fifty‐six patients (19.7%) had seizures; in 21 (37.5%) patients, seizures were the index feature leading to CAA diagnosis. Seizures were more frequent in females (p = 0.032) and patients with lobar ICH (p = 0.002), cSAH (p = 0.030), superficial siderosis (p < 0.001), and CAA‐ri (p = 0.005), and less common in patients with microhemorrhage (p = 0.006). After controlling for age and sex, lobar ICH (odds ratio [OR] = 2.1, 95% confidence interval [CI] = 1.1–4.2), CAA‐ri (OR = 3.8, 95% CI = 1.4–10.3), and superficial siderosis (OR = 3.7, 95% CI = 1.9–7.0) were independently associated with higher odds of incident seizures.ConclusionsSeizures are common in patients with CAA and are independently associated with lobar ICH, CAA‐ri, and superficial siderosis. Our results may be applied to optimize clinical monitoring and management for patients with CAA.

AbstractCorrectly diagnosing and classifying seizures and epilepsies is paramount to ensure the delivery of optimal care to patients with epilepsy. Focal seizures, defined as those that originate within networks limited to one hemisphere, are primarily subdivided into focal aware, focal impaired awareness, and focal to bilateral tonic–clonic seizures. Focal epilepsies account for most epilepsy cases both in children and adults. In children, focal epilepsies are typically subdivided in three groups: self‐limited focal epilepsy syndromes (e.g., self‐limited epilepsy with centrotemporal spikes), focal epilepsy of unknown cause but which do not meet criteria for a self‐limited focal epilepsy syndrome, and focal epilepsy of known cause (e.g., structural lesions—developmental or acquired). In adults, focal epilepsies are often acquired and may be caused by a structural lesion such as stroke, infection and traumatic brain injury, or brain tumors, vascular malformations, metabolic disorders, autoimmune, and/or genetic causes. In addition to seizure semiology, neuroimaging, neurophysiology, and neuropathology constitute the cornerstones of a diagnostic evaluation. Patients with focal epilepsy who become drug‐resistant should promptly undergo assessment in an epilepsy center. After excluding pseudo‐resistance, these patients should be considered for presurgical evaluation as a means to identify the location and extent of the epileptogenic zone and assess their candidacy for a surgical procedure. The goal of this seminar in epileptology is to summarize clinically relevant information concerning focal epilepsies. This contributes to the ILAE's mission to ensure that worldwide healthcare professionals, patients, and caregivers continue to have access to high‐quality educational resources concerning epilepsy.

Abstract The objective of this clinical practice guideline (CPG) is to provide recommendations for healthcare personnel working with patients with epilepsy on the use of wearable devices for automated seizure detection in patients with epilepsy, in outpatient, ambulatory settings. The Working Group of the International League Against Epilepsy (ILAE) and the International Federation of Clinical Neurophysiology (IFCN) developed the CPG according to the methodology proposed by the ILAE Epilepsy Guidelines Working Group. We reviewed the published evidence using The Preferred Reporting Items for Systematic Review and Meta‐Analysis (PRISMA) statement and evaluated the evidence and formulated the recommendations following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. We found high level of evidence for the accuracy of automated detection of generalized tonic‐clonic seizures (GTCS) and focal‐to‐bilateral tonic‐clonic seizures (FBTCS) and recommend the use of wearable automated seizure detection devices for selected patients when accurate detection of GTCS and FBTCS is recommended as a clinical adjunct. We also found a moderate level of evidence for seizure types without GTCS or FBTCS. However, it was uncertain whether the detected alarms resulted in meaningful clinical outcomes for the patients. We recommend using clinically validated devices for automated detection of GTCS and FBTCS, especially in unsupervised patients, where alarms can result in rapid intervention (weak/conditional recommendation). At present, we do not recommend clinical use of the currently available devices for other seizure types (weak/conditional recommendation). Further research and development are needed to improve the performance of automated seizure detection and to document their accuracy and clinical utility.