[Classification of epileptic seizures. Comparison of two systems]

Could the 2017 ILAE and the four-dimensional epilepsy classifications be merged to a new "Integrated Epilepsy Classification"?

Over the last few decades the ILAE classifications for seizures and epilepsies (ILAE-EC) have been updated repeatedly to reflect the substantial progress that has been made in diagnosis and understanding of the etiology of epilepsies and seizures and to correct some of the shortcomings of the terminology used by the original taxonomy from the 1980s. However, these proposals have not been universally accepted or used in routine clinical practice. During the same period, a separate classification known as the "Four-dimensional epilepsy classification" (4D-EC) was developed which includes a seizure classification based exclusively on ictal symptomatology, which has been tested and adapted over the years. The extensive arguments for and against these two classification systems made in the past have mainly focused on the shortcomings of each system, presuming that they are incompatible. As a further more detailed discussion of the differences seemed relatively unproductive, we here review and assess the concordance between these two approaches that has evolved over time, to consider whether a classification incorporating the best aspects of the two approaches is feasible. To facilitate further discussion in this direction we outline a concrete proposal showing how such a compromise could be accomplished, the "Integrated Epilepsy Classification". This consists of five categories derived to different degrees from both of the classification systems: 1) a "Headline" summarizing localization and etiology for the less specialized users, 2) "Seizure type(s)", 3) "Epilepsy type" (focal, generalized or unknown allowing to add the epilepsy syndrome if available), 4) "Etiology", and 5) "Comorbidities & patient preferences".

A statistical method for predicting seizure onset zones from human single-neuron recordings

OBJECTIVE

Clinicians often use depth-electrode recordings to localize human epileptogenic foci. To advance the diagnostic value of these recordings, we applied logistic regression models to single-neuron recordings from depth-electrode microwires to predict seizure onset zones (SOZs).

APPROACH

We collected data from 17 epilepsy patients at the Barrow Neurological Institute and developed logistic regression models to calculate the odds of observing SOZs in the hippocampus, amygdala and ventromedial prefrontal cortex, based on statistics such as the burst interspike interval (ISI).

MAIN RESULTS

Analysis of these models showed that, for a single-unit increase in burst ISI ratio, the left hippocampus was approximately 12 times more likely to contain a SOZ; and the right amygdala, 14.5 times more likely. Our models were most accurate for the hippocampus bilaterally (at 85% average sensitivity), and performance was comparable with current diagnostics such as electroencephalography.

SIGNIFICANCE

Logistic regression models can be combined with single-neuron recording to predict likely SOZs in epilepsy patients being evaluated for resective surgery, providing an automated source of clinically useful information.

Semiologic seizure classification: the effectiveness of a modular education program for health professionals in pediatrics

We tested the effectiveness of a modular education program on Semiologic Seizure Classification (SSC) in helping health professionals in pediatrics correctly recognize seizures in childhood. The study samples included 20 residents, 20 nurses, and 10 EEG technicians working in pediatrics. The study was conducted in two steps. First, a modular education program comprising CD-ROMs including 58 video clips of epileptic seizures designed for the original SSC was developed. Second, each participant took a pretest by viewing the pretest CD-ROM, participated in the modular education program with a CD-ROM, and finally took a posttest with the posttest CD-ROM. The pretest scores were found to be low in each subgroup of the study population: the average scores were 8 for the residents (minimum 4-maximum 10), 2 for the nurses (min 0-max 4), and 2.5 for the EEG technicians (min 0-max 8). After participating in the modular education program, correct recognition of seizures increased in the posttest: the average scores were 15.5 for the residents (min 9-max 20), 15 for the nurses (min 13-max 20), and 13.5 for the EEG technicians (min 3-max 19). The increase in the scores in the subgroups and in all study groups in general was found to be statistically significant (P<0.05). The modular education program developed for SSC was found to be highly effective in teaching health professionals working in general pediatric clinics to correctly recognize seizure types.

A prospective comparison between two seizure classifications

The International Classification of Epileptic Seizures is the most widely used, but an alternative system based purely on ictal symptoms and signs has been proposed: the semiological classification. Our objective was to compare the two in a sample of patients evaluated at epilepsy centers. We collected 78 consecutive patients evaluated in outpatient epilepsy clinics who subsequently underwent noninvasive video-EEG monitoring at three centers. Patients with pseudoseizures were excluded. Seizures were first classified based on information obtained during clinic visits, and again after video-EEG monitoring. Each time, seizures were classified using both the International Classification and the semiological classification. Eventual epilepsy syndrome diagnosis was based on all the clinical data, video-EEG monitoring, and other independent tests including imaging studies. Sixty-six (87%) patients were classified as having 'complex partial seizures' in the International Classification. Using the semiological classification, these same 66 patients were classified as follows: automotor (34), dialeptic (17), hypermotor (13), hypomotor (2). Seizure classification changed between initial 'clinic-based' data and the 'monitoring-based' classification in 27 cases using the ILAE, vs. six using the semiological classification. Seizure classification tended to change significantly between pre- and post-monitoring using the ILAE but not the semiological classification. The term complex partial seizure included multiple categories of the semiological classification, and was very nonspecific. The semiological classification may be better suited for everyday clinic use, since it is based solely on clinical characteristics.