Seizure-related complication rate in a residential population with epilepsy and intellectual disability (ECOMRAID-trial).

INTRODUCTION: The aim of the ECOMRAID trial (Epileptic seizure related Complication RAte in residential population of persons with epilepsy and Intellectual Disability) was to study seizure-related complications (status epilepticus, respiratory complications, or other severe complications) in people with epilepsy and intellectual disability living in a residential setting. The results of the present study are a prerequisite for performing a prospective study into the effectiveness of nocturnal surveillance patients with high risk for Sudden unexpected death in epilepsy (SUDEP). MATERIAL AND METHODS: A retrospective study was conducted in three general residential care institutions and one residential specialized epilepsy clinic. In this 5-year cohort, we collected the following data: age (at inclusion and in case of death), sex, type of residential care, different types of complications, rescue/emergency medication administration, transfers to another department (internal midcare / monitoring unit or general hospital) and a self-designed SUDEP risk score. Our primary research questions were to assess the number of patients who experienced seizure-related complications and their individual complication rates. The secondary research questions were to document the relationship of these complications with the SUDEP risk score, with the type of residential living, and with the frequency of interventions by caregivers. RESULTS: We included 370 patients (1790 patient-years) and in 135 of them, we found 717 seizure-related complications. The following complication rates were found: all complications: at 36%, status epilepticus: at 13%, respiratory complications: at 5%, and other complications at 26%. In residential care institutions, we found fewer patients with complications compared to the specialized epilepsy clinic (all complications 24% vs 42%, OR 0.44, p < 0.01; status epilepticus 5% vs 17%, OR 0.27, p < 0.01; other: complications 19% vs 30%, OR 0.56, p < 0.05). In residential care institutions, we found more "other complications" than in the specialized epilepsy clinic (89% vs 71%, OR 3.13, p < 0.0001). The annual frequency of all complications together was higher in residential care institutions (range 0 to 21 vs 0 to 10, p < 0.05). Rescue medication was given to 75% of the patients, but more often in the specialized epilepsy clinic (median 2.6 vs 0.5 times/patient/year, p < 0.001). In the specialized epilepsy clinic, more patients were transferred to a midcare / monitoring unit or general hospital (56% vs 9%, OR 13.44, p < 0.0001) with higher yearly frequencies (median 0.2 vs 0.0, p < 0.001). There were no reported cases of SUDEP. The median SUDEP risk score was higher in the specialized epilepsy clinic (5 vs 4, p < 0.05) and was weakly correlated with the status epilepticus (ρ = 0.20, p < 0.001) and (total) complication rate (ρ = 0.18, p < 0.001). CONCLUSION: We found seizure-related complications in more than one-third of the patients with epilepsy and intellectual disability living in a residential setting over a period of 5 years. The data also quantify seizure-related complications in patients with epilepsy and intellectual disability.

Subgroup classification in patients with psychogenic non-epileptic seizures.

INTRODUCTION: In this open non-controlled clinical cohort study, the applicability of a theoretical model for the diagnosis of psychogenic non-epileptic seizures (PNES) was studied in order to define a general psychological profile and to specify possible subgroups. METHODS: Forty PNES patients were assessed with a PNES "test battery" consisting of eleven psychological instruments, e.g., a trauma checklist, the global cognitive level, mental flexibility, speed of information processing, personality factors, dissociation, daily hassles and stress and coping factors. RESULTS: The total PNES group was characterized by multiple trauma, personality vulnerability (in a lesser extent, neuropsychological vulnerabilities), no increased dissociation, many complaints about daily hassles that may trigger seizures and negative coping strategies that may contribute to prolongation of the seizures. Using factor analysis, specific subgroups were revealed: a 'psychotrauma subgroup', a 'high vulnerability somatizing subgroup' (with high and low cognitive levels) and a 'high vulnerability sensitive personality problem subgroup'. CONCLUSION: Using a theoretical model in PNES diagnosis, PNES seem to be a symptom of distinct underlying etiological factors with different accents in the model. Hence, describing a general profile seems to conceal specific subgroups with subsequent treatment implications. This study identified three factors, representing two dimensions of the model, that are essential for subgroup classification: psychological etiology (psychotrauma or not), vulnerability, e.g., the somatization tendency, and sensitive personality problems/characteristics ('novelty seeking'). For treatment, this means that interventions could be tailored to the main underlying etiological problem. Also, further research could focus on differentiating subgroups with subsequent treatment indications and possible different prognoses.

A framework to integrate EEG-correlated fMRI and intracerebral recordings.

EEG-correlated functional MRI (EEG-fMRI) has been used to indicate brain regions associated with interictal epileptiform discharges (IEDs). This technique enables the delineation of the complete epileptiform network, including multifocal and deeply situated cortical areas. Before EEG-fMRI can be used as an additional diagnostic tool in the preoperative work-up, its added value should be assessed in relation to intracranial EEG recorded from depth electrodes (SEEG) or from the cortex (ECoG), currently the clinical standard. In this study, we propose a framework for the analysis of the SEEG data to investigate in a quantitative way whether EEG-fMRI reflects the same cortical areas as identified by the IEDs present in SEEG recordings. For that purpose, the data of both modalities were analyzed with a general linear model at the same time scale and within the same spatial domain. The IEDs were used as predictors in the model, yielding for EEG-fMRI the brain voxels that were related to the IEDs and, similarly for SEEG, the electrodes that were involved. Finally, the results of the regression analysis were projected on the anatomical MRI of the patients. To explore the usefulness of this quantitative approach, a sample of five patients was studied who both underwent EEG-fMRI and SEEG recordings. For clinical validation, the results of the SEEG analysis were compared to the standard visual review of IEDs in SEEG and to the identified seizure onset zone, the resected area, and outcome of surgery. SEEG analysis revealed a spatial pattern for the most frequent and dominant IEDs present in the data of all patients. The electrodes with the highest correlation values were in good concordance with the electrodes that showed maximal amplitude during those events in the SEEG recordings. These results indicate that the analysis of SEEG data at the time scale of EEG-fMRI, using the same type of regression model, is a promising way to validate EEG-fMRI data. In fact, the BOLD areas with a positive hemodynamic response function were closely related to the spatial pattern of IEDs in the SEEG recordings in four of the five patients. The areas of significant BOLD that were not located in the vicinity of depth electrodes, were mainly characterized by negative hemodynamic responses. Furthermore, the area with a positive hemodynamic response function overlapped with the resected area in three patients, while it was located at the edge of the resection area for one. To conclude, the results of this study encourage the application of EEG-fMRI to guide the implantation of depth electrodes as prerequisite for successful epilepsy surgery.

Patients with psychogenic non-epileptic seizures referred to a tertiary epilepsy centre: patient characteristics in relation to diagnostic delay.

OBJECTIVE: This clinical study examines patient and seizure characteristics of patients with psychogenic non-epileptic seizures (PNES) in a tertiary epilepsy centre. The main focus was whether a new subgroup of PNES patients emerged with a relatively short referral time and possible specific characteristics. METHODS: All PNES patients referred to a specialist program in our centre between mid 2007 and mid 2009 were consecutively included. This yielded a study cohort of 90 patients. RESULTS: The majority of the patients have a patient history with many medical symptoms and they were or had been in treatment by a medical specialist. Furthermore diffuse psychological/psychiatric symptoms and subsequent treatments are also remarkably common, in general without a clear psychological diagnosis. The average time between seizure onset and referral to an epilepsy centre is remarkably low (4.29 years). About 50% of the patients were referred within 2 years of seizure onset. This 'active high speed referral group' had significantly more previous psychological complaints, significantly more previous psychological/psychiatric treatments and a trend towards more previous medical investigations. CONCLUSION: There seems to be a new subgroup of PNES patients with a short referral time, characterized by a more active attitude towards examination of the symptoms in combination with an active attitude to apply for treatment. However, the PNES cohort as a whole is characterized by having somatoform symptoms based on a process of somatization.

Automatic breath-to-breath analysis of nocturnal polysomnographic recordings.

Diagnosis of sleep-disordered breathing is based on the presence of an abnormal breathing pattern during sleep. In this study, an algorithm was developed for the offline breath-to-breath analysis of the nocturnal respiratory recordings. For that purpose, respiratory signals (nasal airway pressure, thoracic and abdominal movements) were divided into half waves using period amplitude analysis. Individual breaths were characterized by the parameters of the half waves (duration, amplitude, and slope). These values can be used to discriminate between normal and abnormal breaths. This algorithm was applied to six polysomnographic recordings to distinguish abnormal breathing events (apneas and hypopneas). The algorithm was robust for the identification of breaths (sensitivity = 96.8%, positive prediction value (PPV) = 99.5%). The detection of apneas and hypopneas was compared to the manual scoring of two experienced sleep technicians: sensitivity was, respectively, 89.2 and 88.9%, PPV was 54.1 and 59.3%. The classification of apneas into central, obstructive, or mixed was in concordance with the observers in 68% of the apneas. Although the algorithm tended to detect more hypopneas than the clinical standard, this study shows that the extraction of breath-to-breath parameters is useful for detection of abnormal respiratory events and provides a basis for further characterization of these events.

Psychogenic non-epileptic seizures--definition, etiology, treatment and prognostic issues: a critical review.

In this review we systematically assess our currently available knowledge about psychogenic non-epileptic seizures (PNES) with an emphasis on the psychological mechanisms that underlie PNES, possibilities for psychological treatment as well as prognosis. Relevant studies were identified by searching the electronic databases. Case reports were not considered. 93 papers were identified; 65 of which were studies. An open non-randomized design, comparing patients with PNES to patients with epilepsy is the dominant design. A working definition for PNES is proposed. With respect to psychological etiology, a heterogeneous set of factors have been identified. Not all factors have a similar impact, though. On the basis of this review we propose a model with several factors that may interact in both the development and prolongation of PNES. These factors involve psychological etiology, vulnerability, shaping, as well as triggering and prolongation factors. A necessary first step of intervention in patients with PNES seems to be explaining the diagnosis with care. Although the evidence for the efficacy of additional treatment strategies is limited, variants of cognitive (behavioural) therapy showed to be the preferred type of treatment for most patients. The exact choice of treatment should be based on individual differences in the underlying factors. Outcome can be measured in terms of seizure occurrence (frequency, severity), but other measures might be of greater importance for the patient. Prognosis is unclear but studies consistently report that 1/3rd to 1/4th of the patients become chronic.

Psychogenic non-epileptic seizures--diagnostic issues: a critical review.

In this review we systematically assess our current knowledge about psychogenic non-epileptic seizures (PNES), epidemiology, etiology, with an emphasis on the diagnostic issues. Relevant studies were identified by searching the electronic databases. Case reports were not considered. Articles were included when published after 1980 up till 2005 (26 years). A total of 84 papers were identified; 60 of which were actual studies. Most studies have serious methodological limitations. An open non-randomized design, comparing patients with PNES to patients with epilepsy is the dominant design. The incidence of PNES in the general population is low. However, a relatively high prevalence is seen in patients referred to epilepsy centres (15-30%). Caution is needed in the clinical interpretation of ictal features suggested to be pathognomic for PNES. Video-EEG is widely considered to be the gold standard for diagnosing PNES. Still the differential diagnosis epileptic/non-epileptic seizures can be difficult. Despite the current available technical facilities, the mean latency between onset of PNES and final diagnosis as being non-epileptic and psychogenic is approximately 7 years. One of the reasons for diagnostic delay is that the diagnosis of PNES is often limited to a 'negative' process and consequently PNES is characterized as a 'non-disease' (i.e. 'not epilepsy'). The psychological diagnosis is thus an important, although not a conclusive, 'second phase' aspect of medical decision making. Specific relations between seizure presentation and underlying psychological mechanisms are not conclusive. A classification between major motor manifestations and unresponsiveness is recognized. With respect to psychological etiology, a heterogeneous set of factors have been identified that may be involved in the causation, development and provocation of PNES.

[Electrode grids are available for the selection of patients with refractory epilepsy for epilepsy surgery]. / Elektrodematjes beschikbaar om patiënten met refractaire epilepsie te selecteren voor epilepsiechirurgie.

In 60-85% of patients with refractory epilepsy, surgical excision of that part of the brain that is considered to be responsible for the development of epileptic seizures leads to the disappearance of the attacks. In the Netherlands, 60-70 patients undergo epilepsy surgery every year; this is a small number in comparison to the number of potential candidates. Patients with medically refractory epilepsy without structural damage on the MRI or with a lesion in or near specialised areas of the cortex could also be examined and then treated surgically. It is important that such patients be referred earlier for possible surgical treatment of their epilepsy.

Efficacy and safety of levetiracetam in clinical practice: results of the SKATE trial from Belgium and The Netherlands.

OBJECTIVE: Aim of the study was to assess the efficacy and safety of levetiracetam as add-on treatment in patients with partial-onset epilepsy in clinical practice. METHODS: In this observational, multi-centre study patients were treated with levetiracetam for 16 weeks. From a starting dose of 1000 mg/day, dose levels were adjusted at 2-weekly intervals in 1000-mg steps, to a maximum of 3000 mg/day, based on seizure control and tolerance. Analysis of efficacy was based on reduction in seizure frequency relative to baseline, 50% and 100% responder rates (for partial seizures and all seizure types combined) and percentage of patients using levetiracetam at the end of the study. Analysis of safety was based on occurrence of adverse events. RESULTS: The present analysis concerns the results of patients recruited in Belgium and The Netherlands. Of the 251 patients included in the study, 86.9% completed 16 weeks of treatment. Reduction in frequency of partial-onset seizures was 62.2%, with 19.3% of the patients becoming seizure free and 56.6% having a reduction in seizure frequency of > or = 50%. These percentages were more or less the same when calculated for all seizure types combined. Tolerance of levetiracetam treatment was good, with most adverse events being only mild to moderate in severity, and only 10.0% of the adverse events leading to discontinuation from the study. Asthenia, somnolence, dizziness and headache were the most frequently reported adverse events. CONCLUSION: Levetiracetam is effective and safe as add-on treatment for partial-onset seizures in clinical practice.

Epileptogenesis and rational therapeutic strategies.

The understanding of neurobiological mechanisms of epileptogenesis is essential for rational approaches for a possible disease modification as well as treatment of underlying causes of the epilepsies. More effort is necessary to translate results from basic investigations into new approaches for clinical research and to better understand a relationship with findings from clinical studies. The following report is a condensed synapsis in which molecular mechanisms of epileptogenesis, pharmacological modulation of epileptogenesis, evidence based therapy, refractoriness and prediction of outcome is provided in order to stimulate further collaborative international research.