Critique of the 2017 epileptic seizure and epilepsy classifications

Advances in human intracranial electroencephalography research, guidelines and good practices

Since the second-half of the twentieth century, intracranial electroencephalography (iEEG), including both electrocorticography (ECoG) and stereo-electroencephalography (sEEG), has provided an intimate view into the human brain. At the interface between fundamental research and the clinic, iEEG provides both high temporal resolution and high spatial specificity but comes with constraints, such as the individual's tailored sparsity of electrode sampling. Over the years, researchers in neuroscience developed their practices to make the most of the iEEG approach. Here we offer a critical review of iEEG research practices in a didactic framework for newcomers, as well addressing issues encountered by proficient researchers. The scope is threefold: (i) review common practices in iEEG research, (ii) suggest potential guidelines for working with iEEG data and answer frequently asked questions based on the most widespread practices, and (iii) based on current neurophysiological knowledge and methodologies, pave the way to good practice standards in iEEG research. The organization of this paper follows the steps of iEEG data processing. The first section contextualizes iEEG data collection. The second section focuses on localization of intracranial electrodes. The third section highlights the main pre-processing steps. The fourth section presents iEEG signal analysis methods. The fifth section discusses statistical approaches. The sixth section draws some unique perspectives on iEEG research. Finally, to ensure a consistent nomenclature throughout the manuscript and to align with other guidelines, e.g., Brain Imaging Data Structure (BIDS) and the OHBM Committee on Best Practices in Data Analysis and Sharing (COBIDAS), we provide a glossary to disambiguate terms related to iEEG research.

Epilepsy-Connect: An Integrated Knowledgebase for Characterizing Alterations in Consciousness State of Pharmacoresistant Epilepsy Patients

Alterations in consciousness state are a defining characteristic of focal epileptic seizures. Consequently, understanding the complex changes in neurocognitive networks which underpin seizure-induced alterations in consciousness state is important for advancement in seizure classification. Comprehension of these changes are complicated by a lack of data standardization; however, the use of a common terminological system or ontology in a patient registry minimizes this issue. In this paper, we introduce an integrated knowledgebase called Epilepsy-Connect to improve the understanding of changes in consciousness states during focal seizures of pharmacoresistant epilepsy patients. This registry catalogues over 809 seizures from 70 patients at University Hospital's Epilepsy Center who were undergoing stereotactic electroencephalography (SEEG) monitoring as part of an evaluation for surgical intervention. Although Epilepsy-Connect focuses on consciousness states, it aims to enable users to leverage data from an informatics platform to analyze epilepsy data in a streamlined manner. Epilepsy-Connect is available at https://bmhinformatics.case.edu/Epilepsyconnect/login/.

Evaluation of the International League Against Epilepsy 1981, 1989, and 2017 classifications of seizure semiology and etiology in a population-based cohort of children and adults with epilepsy

Objective

The International League Against Epilepsy (ILAE) has revised the classification of epilepsies and seizures on several occasions since the original classification published in 1964. It is unclear if these changes have impacted the characterization of epilepsy, including the clinical validity of seizure semiology or epilepsy outcomes in resource‐poor areas. We aim to address this important knowledge gap.

Methods

We reviewed the clinical seizure semiology and etiological data of 483 persons with epilepsy identified from a population‐based survey in rural Kenya. The seizure semiology and etiological data were classified using the 1981 (for seizures) and 1989 (for epilepsy) ILAE criteria and then reclassified according to the ILAE‐2017 criteria. Logistic regression models adjusted for potential confounders were used to measure the associations between the seizure semiology and different clinical and electroencephalographic features of epilepsy.

Results

Focal (formerly localization‐related) and generalized epilepsies were lower in ILAE‐2017 (56% and 29%) than that of ILAE‐1989 (61% and 34%), P < .001 and P < .001. Combined focal and generalized epilepsy type in ILAE‐2017 accounted for 11% of epilepsies. Individual seizure types were statistically similar in both ILAE‐1981 and 2017. New classification categories in ILAE‐2017 such as unknown seizures and epilepsies were identified, and the proportions were similar to the unclassified category in ILAE‐1989, 6% and 5%, respectively. The most common causes of epilepsy were symptomatic (76%) in the ILAE‐1989 criteria, with infectious (45%) and structural (36%) causes were highest in the ILAE‐2017 criteria.

Significance

Our study confirms that the two ILAE classification schemes are broadly consistent, but the introduction of the combined onset seizure category in ILAE‐2017 significantly reduces the proportion of mutually exclusive focal and generalized seizures. The comprehensive classification of etiology categories in ILAE‐2017 will facilitate appropriate treatment and improve prognosis.

Executive deficits in neuropsychological testing differentiate between autoimmune temporal lobe epilepsy caused by limbic encephalitis and temporal lobe epilepsies with non-autoimmune etiologies

OBJECTIVE

Patients with temporal lobe epilepsy caused by autoimmune limbic encephalitis (AI-TLE) clinically resemble patients with temporal lobe epilepsy with non-autoimmune etiologies (NAI-TLE) but have a different prognosis and require specific adjusted therapies. The objective of this study was to investigate whether patients with these forms of TLE can be discerned by means of neuropsychological assessment.

METHODS

Data from 103 patients with TLE (n = 39 with AI-TLE and n = 64 with NAI-TLE, including n = 39 with hippocampal sclerosis [HS] and n = 25 with low-grade epilepsy-associated tumors [LEAT]) and 25 healthy controls who underwent comprehensive neuropsychological assessments were analyzed retrospectively. The neuropsychological characteristics (mean z-scores) were compared between groups using one-way ANOVA, independent-samples t-tests, and discriminant function analysis (DFA).

RESULTS

The groups of patients with TLE showed significantly lower performance in attentional, visuospatial, verbal memory, and nonverbal memory functions compared to the healthy controls. Solely in the domain of executive functions, patients with AI-TLE showed significantly lower performance compared to patients with NAI-TLE regarding cognitive flexibility (p = 0.002) and verbal fluency (p = 0.018). Moreover, the DFA identified cognitive flexibility to be most appropriate to differentiate between patients with AI-TLE and patients with HS. Group membership was correctly predicted through neuropsychological assessment alone in 66.7% of the patients using cross-validation.

SIGNIFICANCE

We were able to identify specific neuropsychological features in our sample of patients with AI-TLE. While all groups of patients with TLE showed the expected TLE-typical memory impairments, significant differences between patients with AI-TLE and NAI-TLE were present only in the cognitive domain of executive functions. This finding facilitates the choice of suitable psychometric tests in clinical routine and, thus, the clinical differential diagnosis between these entities.

A web-based algorithm to rapidly classify seizures for the purpose of drug selection

OBJECTIVE

To develop and validate a pragmatic algorithm that classifies seizure types, to facilitate therapeutic decision-making.

METHODS

Using a modified Delphi method, five experts developed a pragmatic classification of nine types of epileptic seizures or combinations of seizures that influence choice of medication, and constructed a simple algorithm, freely available on the internet. The algorithm consists of seven questions applicable to patients with seizure onset at the age of 10 years or older. Questions to screen for nonepileptic attacks were added. Junior physicians, nurses, and physician assistants applied the algorithm to consecutive patients in a multicenter prospective validation study (ClinicalTrials.gov identifier: NCT03796520). The reference standard was the seizure classification by expert epileptologists, based on all available data, including electroencephalogram (EEG), video-EEG monitoring, and neuroimaging. In addition, physicians working in underserved areas assessed the feasibility of using the web-based algorithm in their clinical setting.

RESULTS

A total of 262 patients were assessed, of whom 157 had focal, 51 had generalized, and 10 had unknown onset epileptic seizures, and 44 had nonepileptic paroxysmal events. Agreement between the algorithm and the expert classification was 83.2% (95% confidence interval = 78.6%-87.8%), with an agreement coefficient (AC1) of .82 (95% confidence interval = .77-.87), indicating almost perfect agreement. Thirty-two health care professionals from 14 countries evaluated the feasibility of the web-based algorithm in their clinical setting, and found it applicable and useful for their practice (median = 6.5 on 7-point Likert scale).

SIGNIFICANCE

The web-based algorithm provides an accurate classification of seizure types, which can be used for selecting antiseizure medications in adolescents and adults.

On seizure semiology

The clinical expression of seizures represents the main symptomatic burden of epilepsy. Neural mechanisms of semiologic production in epilepsy, especially for complex behaviors, remain poorly known. In a framework of epilepsy as a network rather than as a focal disorder, we can think of semiology as being dynamically produced by a set of interconnected structures, in which specific rhythmic interactions, and not just anatomical localization, are likely to play an important part in clinical expression. This requires a paradigm shift in how we think about seizure organization, including from a presurgical evaluation perspective. Semiology is a key data source, albeit with significant methodological challenges for its use in research, including observer bias and choice of semiologic categories. Better understanding of semiologic categorization and pathophysiological correlates is relevant to seizure classification systems. Advances in knowledge of neural mechanisms as well as anatomic correlates of different semiologic patterns could help improve knowledge of epilepsy networks and potentially contribute to therapeutic innovations.

Wada test results contribute to the prediction of change in verbal learning and verbal memory function after temporal lobe epilepsy surgery

In recent years, the clinical usefulness of the Wada test (WT) has been debated among researchers in the field. Therefore, we aimed to assess its contribution to the prediction of change in verbal learning and verbal memory function after epilepsy surgery. Data from 56 patients with temporal lobe epilepsy who underwent WT and subsequent surgery were analyzed retrospectively. Additionally, a standard neuropsychological assessment evaluating attentional, learning and memory, visuospatial, language, and executive function was performed both before and 12 months after surgery. Hierarchical linear regression analyses were used to determine the incremental value of WT results over socio-demographic, clinical, and neuropsychological characteristics in predicting postsurgical change in patients' verbal learning and verbal memory function. The incorporation of WT results significantly improved the prediction models of postsurgical change in verbal learning (∆R² = 0.233, p = .032) and verbal memory function (∆R² = 0.386, p = .005). Presurgical performance and WT scores accounted for 41.8% of the variance in postsurgical change in verbal learning function, and 51.1% of the variance in postsurgical change in verbal memory function. Our findings confirm that WT results are of significant incremental value for the prediction of postsurgical change in verbal learning and verbal memory function. Thus, the WT contributes to determining the risks of epilepsy surgery and, therefore, remains an important part of the presurgical work-up of selected patients with clear clinical indications.

Design and implementation of electronic health record common data elements for pediatric epilepsy: Foundations for a learning health care system

OBJECTIVE

Common data elements (CDEs) are standardized questions and answer choices that allow aggregation, analysis, and comparison of observations from multiple sources. Clinical CDEs are foundational for learning health care systems, a data-driven approach to health care focused on continuous improvement of outcomes. We aimed to create clinical CDEs for pediatric epilepsy.

METHODS

A multiple stakeholder group (clinicians, researchers, parents, caregivers, advocates, and electronic health record [EHR] vendors) developed clinical CDEs for routine care of children with epilepsy. Initial drafts drew from clinical epilepsy note templates, CDEs created for clinical research, items in existing registries, consensus documents and guidelines, quality metrics, and outcomes needed for demonstration projects. The CDEs were refined through discussion and field testing. We describe the development process, rationale for CDE selection, findings from piloting, and the CDEs themselves. We also describe early implementation, including experience with EHR systems and compatibility with the International League Against Epilepsy classification of seizure types.

RESULTS

Common data elements were drafted in August 2017 and finalized in January 2020. Prioritized outcomes included seizure control, seizure freedom, American Academy of Neurology quality measures, presence of common comorbidities, and quality of life. The CDEs were piloted at 224 visits at 10 centers. The final CDEs included 36 questions in nine sections (number of questions): diagnosis (1), seizure frequency (9), quality of life (2), epilepsy history (6), etiology (8), comorbidities (2), treatment (2), process measures (5), and longitudinal history notes (1). Seizures are categorized as generalized tonic-clonic (regardless of onset), motor, nonmotor, and epileptic spasms. Focality is collected as epilepsy type rather than seizure type. Seizure frequency is measured in nine levels (all used during piloting). The CDEs were implemented in three vendor systems. Early clinical adoption included 1294 encounters at one center.

SIGNIFICANCE

We created, piloted, refined, finalized, and implemented a novel set of clinical CDEs for pediatric epilepsy.

Assessing Cognitive Change and Quality of Life 12 Months After Epilepsy Surgery-Development and Application of Reliable Change Indices and Standardized Regression-Based Change Norms for a Neuropsychological Test Battery in the German Language

Objective

The establishment of patient-centered measures capable of empirically determining meaningful cognitive change after surgery can significantly improve the medical care of epilepsy patients. Thus, this study aimed to develop reliable change indices (RCIs) and standardized regression-based (SRB) change norms for a comprehensive neuropsychological test battery in the German language.

Methods

Forty-seven consecutive patients with temporal lobe epilepsy underwent neuropsychological assessments, both before and 12 months after surgery. Practice-effect-adjusted RCIs and SRB change norms for each test score were computed. To assess their usefulness, the presented methods were applied to a clinical sample, and binary logistic regression analyses were conducted to model the odds of achieving improvement in quality of life (QOL) after surgery.

Results

The determined RCIs at 90% confidence intervals and the SRB equations for each test score included in the test battery are provided. Cohen’s kappa analyses revealed a moderate mean agreement between the two measures, varying from slight to almost perfect agreement across test scores. Using these measures, a negative association between improvement in QOL and decline in verbal memory functions after surgery was detected (adjusted odds ratio = 0.09, p = 0.006).

Significance

To the best of our knowledge, this study is the first to develop RCIs and SRB change norms necessary for the objective determination of neuropsychological change in a comprehensive test battery in the German language, facilitating the individual monitoring of improvement and decline in each patients’ cognitive functioning and psychosocial situations after epilepsy surgery. The application of the described measures revealed a strong negative association between improvement in QOL and decline in verbal memory functions after surgery.

Current Classification of Seizures and Epilepsies: Scope, Limitations and Recommendations for Future Action

The classification of seizures and epilepsies by the International League Against Epilepsy (ILAE), 2017 is the most recent classification model which aimed to simplify terminologies that patients and their caregivers can easily understand, identify seizures that have both focal and generalized onset and incorporate missing seizures. We have exhaustively reviewed the studies, discussed its scope, outlined its limitations and gave recommendations that could help in forming subsequent reviews. We have also described the terminologies that have been replaced, redefined or removed to have a clear view of the previous and the current classification models. We have recommended the use of multidimensional classification model which incorporated the clinical semiology, disease location, etiology and associated comorbidities. The benefits of this model is for prompt diagnosis which will results into early management and then better patient outcomes. It would also have a profound effects on the kind of treatment patients might receive especially in developing countries where there are scarcity of the diagnostic techniques. Overall, in this study we have reviewed the current study on seizures and epilepsy classification model by ILAE, 2017 to clarify the descriptions and coverage, outlined some limitations and suggested recommendations.

The evolution of the concepts of seizures and epilepsy: What's in a name?

This review aims to highlight the historical hallmarks in the development of the concepts of seizures and epilepsy. It begins with a discussion of seizure semiology and terminology, followed by the pathophysiology of seizures. We then discuss the definition of epilepsy, its etiologies, and ultimately classification schemes. Each section starts with our current views and subsequently transports the reader back in time to understand how these views evolved and came to be what they are today. People living as early as in the prehistoric times may have been aware of the existence of seizures, and descriptions and terminology have been provided as early as 2500 BC. While names have been revised and updated through time, the meanings are seemingly unchanged. However, it is clearly evident that we have come a long way in understanding the pathophysiology and etiology of seizures and epilepsy, thus leading to our current classification schemes. No classification scheme will be perfect yet, until our understanding is advanced enough to create one based predominantly on scientific grounds. The goal is that it is relevant to clinical practice, leading to a more precise diagnosis to guide targeted treatments.

Hyperventilation-induced high-amplitude rhythmic slowing: A mimicker of absence seizures in children

PURPOSE

Hyperventilation (HV) in children can lead to HV-induced high-amplitude rhythmic slowing (HIHARS) on the EEG (electroencephalogram) which is sometimes associated with altered awareness (AA) and concomitant semiological features. Our aims were to determine the frequency of HIHARS in children, to assess if the associated semiological features were temporally related to HV, and to evaluate if specific semiological features can differentiate HIHARS with AA from absence seizures.

METHODS

Consecutive children with suspected new onset seizure(s) underwent HV and awareness testing during video-EEG acquisition. Hyperventilation-induced high-amplitude rhythmic slowing was defined as 2.5- to 5-Hz generalized rhythmic slowing with amplitude ≥100 μv lasting for ≥3 s. The associated semiological features were compared between the group of children with HIHARS and AA, an age- and gender-matched control group without HIHARS, and in children who experienced absence seizures during HV.

RESULTS

One hundred sixteen children with a mean age of 9.8 years were included. Hyperventilation-induced high-amplitude rhythmic slowing occurred in 39 children (33.6%) with AA documented in 30 (76.9%). The probability of developing AA during HIHARS was significantly and positively correlated with the HIHARS duration. The frequencies of HIHARS were not significantly different between children diagnosed with seizure(s) and those with nonepileptic spells. Hyperventilation cessation and staring did not occur in any child of the control group. Fidgeting and yawning were significantly more common in the group with HIHARS with AA while staring and blinking were significantly more frequent in the group of children with absence seizures.

CONCLUSIONS

We ascertained that HIHARS with AA is a relatively common occurrence in children and most likely represents an age-related nonepileptic phenomenon. When associated with fidgeting or yawning, it can help differentiate this phenomenon from absence seizures. However, recording the concomitant presence of generalized spike wave discharges on the EEG remains essential to confirm the diagnosis of absence seizures.

[New classification of epileptic seizures : A critical evaluation of the changes]

In the new classification of epileptic seizures by the International League Against Epilepsy (ILAE), a multitude of changes are recommended particularly for seizures of focal origin. In addition to aspects of the nomenclature, this involves the introduction of different levels of classification with respect to the state of consciousness and the evolution to a bilateral tonic-clonic seizure, the inclusion of the first semiological seizure element in the classification and a new operationalization of the state of consciousness. This leads partly to specification in the description but in some areas also to counterintuitive changes in the classification. The advantages and disadvantages of this reorganization for the clinical practice are critically discussed with reference to the most important modifications.