Citations

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.

AbstractObjectiveWe published a list of “must‐know” routine EEG (rEEG) findings for trainees based on expert opinion. Here, we studied the accuracy and inter‐rater agreement (IRA) of these “must‐know” rEEG findings among international experts.MethodsA previously validated online rEEG examination was disseminated to EEG experts. It consisted of a survey and 30 multiple‐choice questions predicated on the previously published “must‐know” rEEG findings divided into four domains: normal, abnormal, normal variants, and artifacts. Questions contained de‐identified 10–20‐s epochs of EEG that were considered unequivocal examples by five EEG experts.ResultsThe examination was completed by 258 international EEG experts. Overall mean accuracy and IRA (AC1) were 81% and substantial (0.632), respectively. The domain‐specific mean accuracies and IRA were: 76%, moderate (0.558) (normal); 78%, moderate (0.575) (abnormal); 85%, substantial (0.678) (normal variants); 85%, substantial (0.740) (artifacts). Academic experts had a higher accuracy than private practice experts (82% vs. 77%; p = .035). Country‐specific overall mean accuracies and IRA were: 92%, almost perfect (0.836) (U.S.); 86%, substantial (0.762) (Brazil); 79%, substantial (0.646) (Italy); and 72%, moderate (0.496) (India). In conclusion, collective expert accuracy and IRA of “must‐know” rEEG findings are suboptimal and heterogeneous.SignificanceWe recommend the development and implementation of pragmatic, accessible, country‐specific ways to measure and improve the expert accuracy and IRA.

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.