Pseudosleep events in patients with psychogenic non-epileptic seizures: prevalence and associations

OBJECTIVES: To determine the prevalence and clinical associations of a history of events during sleep in patients with psychogenic non-epileptic seizures (PNES, pseudoseizures), and to compare the prevalence of a history of sleep events with that in poorly controlled epilepsy. METHODS: Prospective study by semistructured interview of the history of event patterns and their clinical associations in 142 patients with video EEG confirmed PNES, and 100 patients with poorly controlled epilepsy. RESULTS: 84/142 patients with PNES (59%) and 47/100 with epilepsy (47%) gave a history of events during sleep (p = 0.062). In patients with PNES, significant associations were found between a history of sleep events and: convulsive clinical semiology, antiepileptic drug treatment, fatigue, suicide attempts, mood disorder, and physical abuse. A particularly strong association with social security benefit was also found (odds ratio 4.0, p<0.001). CONCLUSIONS: The prevalence of a history of sleep events is similar in PNES and epilepsy, and is of no value in discriminating between the two, although a history of events occurring exclusively during sleep does suggest epileptic seizures. The clinical associations found indicate that a combination of psychopathological and external influences may be important in determining whether or not a patient with PNES gives a history of events during sleep.     

Psychogenic pseudoepileptic seizures: clinical and electroencephalogram (EEG) video-tape recordings

This paper presents a clinical and electrophysiological analysis of type and duration of seizures recorded by means of long-term video electroencephalogram (EEG) monitoring, a method which enables accurate diagnosis of psychogenic pseudoepileptic seizures occurring with or without epileptic seizures. Analysis is based on 1083 patients, hospitalized at our department between 1990 and 1997, with a preliminary diagnosis of epilepsy. Psychogenic pseudoepileptic seizures were diagnosed in 85 patients (7.8%). In 48 patients, pseudoepileptic seizures alone were diagnosed (group 1), whereas 37 patients had a mixed condition in which pseudoepileptic seizures were accompanied by epileptic seizures (group 2). For comparison of duration of pseudo- and epileptic seizures a control group (group 3), consisting of 55 patients randomly selected from the population of patients suffering from epileptic seizures alone, was parceled out. Long-term video EEG monitoring was performed in 70 patients. In 55 (79%) of these patients 230 seizures (221 pseudoepileptic and nine epileptic) were recorded. In 30 patients (32%), the diagnosis was based on clinical observation of the seizures and on the number of EEG recordings, including activating procedures such as sleep deprivation, photostimulation, hyperventilation and anti-epileptic drug withdrawal. We found that the duration of epileptic seizures was significantly shorter than the duration of psychogenic pseudoepileptic seizures. Our study has exposed the difficulties involved in the diagnosis of psychogenic pseudoepileptic seizures and the negligible value of neuroimaging techniques and interictal EEG recordings in the differential diagnosis of epileptic versus nonepileptic seizures. In this study, psychogenic seizures were significantly more frequent in women than in men; patient history analysis did not confirm the hypothesis that sexual abuse may cause psychogenic seizures.     

First epileptic seizure in the elderly: electroclinical and etiological data in 341 patients

This study included 341 subjects aged over 60 years, 174 females and 167 males, (mean age 72-years), who experienced their first epileptic seizure and fulfilled all inclusion criteria over an 8-year period. Data were available from the physical examination, EEG, laboratory tests and CT scan or MRI for all patients. The international classification of epileptic seizures was applied, 41 p.cent of the seizures were generalized and 59 p.cent were partial. Status epilepticus occurred in 8 p.cent of the patients. The EEG recording was contributive to diagnosis or helpful for localizing the epileptic focus in 55 p.cent of the patients. Normal brain imaging was observed in 40 p.cent of the patients. The main etiology was cerebrovascular disease (33 p.cent), acute stroke (27 patients), or more often postvascular epilepsy (87 patients). Other etiologies were degenerative cortical dementia in 7 p.cent of the patients, metabolic and toxic disorders in 11 p.cent, and benign or malignant brain tumors in 6.5 p.cent. Thirty-two percent of the seizures were of unknown origin (cryptogenic seizures). No correlation was found between sex, age, and etiology. An antiepileptic drug treatment was initiated in 77 p.cent of the patients who were given either valproate (43 p.cent), carbamazepine (26 p.cent) or barbiturates (7 p.cent). These findings are in agreement with those reported in the reviewed literature.     

Prevalence, classification, and severity of epilepsy in children in western Norway

PURPOSE: To determine prevalence of active epilepsy in school children in a defined area and assess the usefulness of International League Against Epilepsy classification of seizures and epileptic syndromes, with special emphasis on frequency, additional handicaps, and therapeutic problems of severe cases. METHODS: The latest International League Against Epilepsy International Classification of Epileptic Seizures (ICES, 1981) and Epilepsies and Epileptic Syndromes (ICE, 1989) were used for determination of prevalence rates, seizure types, epilepsies and epileptic syndromes, and additional neurological deficits in all 6-to 12-year-old children with epilepsy in a Norwegian county. Children had neuropediatric and EEG examination, intelligence evaluation, and, when necessary, additional investigations. RESULTS: Prevalence of active epilepsy on January 1, 1995, was 5.1 per 1,000. Main seizure type and epilepsy syndrome could be classified in 98% and 90% of patients, respectively. Seizure types/epileptic syndromes were more often partial/localization related than generalized. Among generalized epilepsies, idiopathic forms were more frequent in girls, and cryptogenic and symptomatic forms more frequent in boys. Epileptogenic EEG activity was most often generalized or localized to one or two areas of the brain and was never found in 14% of patients. Symptomatic etiology was found in 46% of all children and in 81% of therapy-resistant cases, respectively. Over the years, 11% of children had never used antiepileptic drugs (AED), 62% had tried one or two AEDs, and 26% had tried from three to 15 AEDs. Twenty-five percent of children were without present AED treatment. Complementary/alternative medicine had been tried by 12% of children. CONCLUSIONS: Although most epilepsies could be classified, the number of cases in non-specific categories was relatively high. Symptomatic etiology was frequent, especially in therapy-resistant cases. Multidisciplinary therapeutic and habilitation approaches are often needed in childhood epilepsy.     

THE ELECTROENCEPHOLOGRAM AS AN AID IN REVEALING INTRACRANIAL ARTERIOVENOUS MALFORMATIONS

Routine electroencephalography was performed on 58 patients with an intracranial arteriovenous malformation. Local abnormal EEG findings were observed in 23 (40 %) of them, 15 (26 %) had a general abnormality, and in 20 (34 %) the EEG was normal. In two patients with a local abnormality the abnormality was contralateral to the AVM. There was no relation between EEG abnormality and age of patients or duration of the symptoms. The size and radiological density of the AVM were not related with the frequency of EEG abnormality, nor were any differences seen in the distribution of findings between the non-haemorrhagic, subarachnoid haemorrhage and intracerebral haemorrhage groups. In patients with a history of epileptic seizures abnormality of the EEG was more frequent (p < 0.05) than in those with no epileptic seizures. Parietal and temporal AVMs combined had a higher frequency (p < 0.001) of local EEG abnormalities than in those patients in whom the AVM was occipital, central or in the posterior fossa. EEG as a screening method for intracranial AVM is noted to reveal only 62% of those AVMs found by brain scanning. On the other hand, half of the patients in whom scanning failed (due to small size or temporal location of the AVM) the EEG showed a local abnormality.     

Diurnal and sleep/wake patterns of epileptic spasms in different age groups

Purpose: Epileptic spasms are seizures that occur predominantly in children and are characterized by clusters of brief axial movements. Epileptic spasms may occur in the context of a variety of syndromes. Previous research has found that epileptic spasms occur in a sleep/wake and diurnal rhythm. The purpose of this study was to identify these patterns in different age groups. Methods: Charts of 2,021 patients with epilepsy undergoing video–electroencephalography (EEG) monitoring over a 10‐year period were reviewed for presence of epileptic spasms and analyzed for their occurrence during the day (6 a.m. to 6 p.m.) or night, out of wake or sleep, and in 3‐h time‐blocks throughout the day. Exact epileptic spasm time, EEG localization, and the presence or absence of magnetic resonance imaging lesion were also recorded. Patients were separated into two age groups: A ages 3 and under, and over age 3. Statistical analysis of seizure occurrence in time bins was carried out using binomial calculations. p‐Values <0.05 were taken as significant. Using exact seizure times, a generalized linear mixed model of the Poisson‐family with a square root link function was used to calculate mean seizure times. Age, as a binary variable, and time, as a categorical variable, was treated as fixed effect predictors, and individual effects were modeled as random effects. For comparison between the two age groups, over age 3 and under age 3, seizure times were transformed into circular variables. A circular analysis of variance test was used to assess for the difference in mean seizure time, assuming a von Mises distribution of the circle. Key Findings: We analyzed 219 clusters of epileptic spasms in 51 patients (15 girls; mean age 2.15 ± 2.22 years). Forty‐two patients younger than 3 years of age had 163 seizures and nine patients older than 3 years had 56 seizures. Epileptic spasms occurred predominantly during wakefulness (p < 0.001) and during daytime (p < 0.001). Epileptic spasms occurred most frequently between 9 a.m. and noon (p < 0.05) and between 3 p.m. and 6 p.m. (p < 0.001). Patients without magnetic resonance imaging lesions had most seizures between 9 a.m. and noon (p < 0.01) and 3 p.m. and 6 p.m. (p < 0.001). Thirty‐seven patients had 157 epileptic spasms (71.2%) with generalized EEG patterns and 14 patients had 62 epileptic spasms (28.8%) with focal EEG patterns. Generalized EEG seizures occurred more frequently than focal EEG seizures (p < 0.001). Following age stratification, patients younger than 3 years had most epileptic spasms between 9 a.m. and noon (p < 0.05) and 3 p.m. and –6 p.m. (p < 0.01) and patients older than 3 years had most epileptic spasms between 6 a.m. and –9 a.m. (p < 0.05) and a second peak between 3 p.m. and 6 p.m., although the difference was not statistically significant due to insufficient numbers. Using continuous time analysis, the mean seizure time in the under age 3 and the over age 3 groups was 2:24 p.m. and 11:40 a.m. Using a circular analysis of variance test, the difference between mean seizure times in these groups was found to be statistically significant (p = 0.038). Significance: Epileptic spasms occur more frequently in the waking state and daytime. Younger patients have epileptic spasms mostly between 9 a.m. and noon and 3 p.m. and –6 p.m., and older patients have epileptic spasms mostly between 6 a.m. and 9 a.m. These findings emphasize age‐related changes in epileptic spasm pathophysiology or potentially evolution of disease with age.     

"Convulsive" nonepileptic seizures have a characteristic pattern of rhythmic artifact distinguishing them from convulsive epileptic seizures

PURPOSE: Approximately 30% of patients admitted for video-EEG monitoring have psychogenic nonepileptic seizures (PNES). Differentiation of "convulsive" PNES from convulsive seizures can be difficult. The EEG often displays rhythmic movement artifact that may resemble seizure activity and confound the interpretation. We sought to determine whether time-frequency mapping of the rhythmic EEG artifact during "convulsive" PNES reveals a pattern that differs from that of epileptic seizures. METHODS: EEGs from 15 consecutive patients with "convulsive" PNESs were studied with time-frequency mapping by using NEUROSCAN and compared with 15 patients with convulsive epileptic seizures. Fast Fourier transforms (FFTs) were performed to determine the dominant frequency for 1- to 2-s windows every 2 s through the seizures. RESULTS: The dominant frequency remained stable within a narrow range for the duration of the PNES, whereas in the epileptic seizures, it evolved through a wide range. The coefficient of variation of the frequency during the seizures was considerably less for patients without epilepsy (median, 15.0%; range, 7.2-23.7% vs. median, 58.0%; range, 34.8-92.1%; p < 0.001). The median frequency did not differ significantly between groups (4.2 vs. 4.6 Hz; p = 0.290). CONCLUSIONS: "Convulsive" PNES display a characteristic pattern on time-frequency mapping of the EEG artifact, with a stable, nonevolving frequency that is different from the evolving pattern seen during an epileptic seizure.     

Seizure frequency and bioelectric brain activity in epileptic patients in stable and unstable atmospheric pressure and temperature in different seasons of the year--a preliminary report

Background and purposeAn epileptic seizure is a sum of exogenous and endogenous factors affecting an epileptic focus. The aim of the study was to examine the influence of changes in atmospheric pressure and temperature on the increase in the frequency of seizures and changes in EEG in epileptic patients.Material and methodsThe study included 30 epileptic patients (aged 19–54) reporting the influence of changes in weather conditions on the increase in the frequency of seizures for at least 2 years. EEG was performed twice each season at the time of stable and unstable weather conditions.ResultsIn stable and unstable weather conditions, epileptic changes in EEG were most often found in winter (in 43.3% and 63.3% of patients, respectively). Unstable weather conditions increased the proportion of patients with epileptic changes in EEG also in the other seasons. Unstable weather conditions caused an increase in the frequency of seizures in 40% of patients in spring, 43.3% in autumn, 40% in winter and in approximately 7% in summer.ConclusionsIn spring, autumn and winter, unstable weather conditions cause an increase in the frequency of seizures in almost half of the epileptic patients but only in 7% in summer. The increase in frequency of seizures in unstable weather conditions did not correspond in all patients with increase of changes in EEG. The higher proportion of epileptic patients with changes in EEG in unstable weather conditions in all seasons suggests an impact of these conditions on subclinical seizure discharges in this period.     

Comparison of heart rate variability parameters during complex partial seizures and psychogenic nonepileptic seizures

Purpose: Psychogenic nonepileptic seizures (PNES) superficially resemble epileptic seizures. Little is known about ictal autonomic nervous system (ANS) activity changes in epilepsy and PNES. This study compares ictal heart rate variability (HRV) parameters as a reflection of ANS tone in epileptic seizures and PNES, and explores differences between interictal and ictal ANS tone in both patient groups. Methods: Ictal HRV parameters were extracted from single‐lead electrocardiography (ECG) data collected during video–electroencephalography (EEG) recordings of 26 patients with medically refractory temporal lobe epilepsy and 24 age‐ and sex‐matched patients with PNES. One seizure per patient in a resting, wake, supine state was analyzed. Interictal ECG data were available for comparison from 14 patients in both groups. HRV parameters in time and frequency domains were analyzed (low frequency [LF], high frequency [HF], standard deviation of all consecutive normal R wave intervals [SDNN], square root of the mean of the sum of the squares of differences between adjacent normal R wave intervals [RMSSD]). CVI (cardiovagal index), CSI (cardiosympathetic index), and ApEn (approximate entropy) were calculated from Lorenz plots. Key Findings: There were significant differences between ictal HRV measures during epileptic and nonepileptic seizures in the time and frequency domains. CSI (p < 0.001) was higher in epileptic seizures. Time interval between two consecutive R waves in the ECG (RR interval) (p = 0.002), LF (p = 0.02), HF (p = 0.003), and RMSSD (p = 0.003) were significantly lower during epileptic seizures. Binary logistic regression yielded a significant model based on the differences in CSI classifying 88% of patients with epilepsy and 73% of patients with PNES correctly. The comparison between resting and ictal states in both seizure disorders revealed significant differences in RR interval (epilepsy p < 0.001, PNES p = 0.01), CSI (epilepsy p < 0.001, PNES p = 0.02), HF (epilepsy p = 0.002, PNES p = 0.03), and RMSSD (epilepsy p = 0.004, PNES p = 0.04). In patients with epilepsy there were also significant differences in ictal versus interictal mean values of ApEn (p = 0.03) and LF (p = 0.04). Although CSI was significantly higher, the other parameters were lower during the seizures. Stepwise binary regression in the 14 patients with epilepsy produced a significant model differentiating resting state from seizures in 100% of cases. The same statistical approach did not yield a significant model in the PNES group. Significance: Our results show greater ANS activation in epileptic seizures than in PNES. The biggest ictal HRV changes associated with epileptic seizures (CSI, HF, and RMSSD) reflect high sympathetic system activation and reduced vagal tone. The reduced ApEn also reflects a high sympathetic tone. The observed ictal alterations of HRV patterns may be a more specific marker of epileptic seizures than heart rate changes alone. These altered HRV patterns could be used to detect seizures and also to differentiate epileptic seizures from PNES. Larger studies are justified with intergroup and intragroup comparisons between ictal and resting states.     

Long-term EEG monitoring in epilepsy diagnosis

EEG long-term monitorings were carried out in 149 patients using a portable 4-channel miniature recorder system. In most cases EEG was recorded for 48 hours. In addition to preceding routine EEG controls, long-term EEG monitoring disclosed epileptic phenomena in 32.7% of patients suspected for epileptic seizures from their history. This gain of information was based mainly on the detection of abnormal potentials or epileptic seizures appearing during sleep. Using EEG long-term recording numerous EEG routine controls could be replaced which otherwise are often necessary for ensuring the diagnosis of epilepsy. If the patient's history, however, gives only poor reason to believe epileptic seizures, positive findings in EEG long-term monitorings are unlikely. Consequently, careful evaluation of the patient's history is crucial for the indication of this laborious examination. As the limited number of recorder channels may cause false negative results, normal findings should be utilized with caution. Only the sum of all clinical and neurophysiological data should be used for exclusion of suspected epilepsy. The second, even more important application of EEG long-term recordings is the special examination of patients with known epilepsy, such as studies of the circadian profiles of epileptic excitability, documentation of seizure frequency, and electrographic analysis of the course of seizure. Therapy control of epileptic patients can be improved by such informations. In view of the large amount of data which results from long-term recordings, computer assisted methods supporting the visual analysis are necessary. In this regard the continuous spectral analysis of the EEG long-term recordings proved to be highly useful.     

Daytime Sleep Tendency Before and After Discontinuation of Antiepileptic Drugs in Preadolescent Children with Epilepsy

In 9 preadolescent children treated for epilepsy who had been free from seizures long enough for treatment to be discontinued, daytime vigilance was studied before and after discontinuation of antiepileptic drugs (AEDs). Comparisons were made with healthy controls. Multiple sleep latency test (MSLT), EEG, and a questionnaire were used. As part of the analysis of the MSLT, a new measure, the daily average sleep tendency (DAST), was constructed to overcome the problems with data censoring of the classic MSLT analysis. The patients had significantly (p less than 0.001) higher daytime sleep tendency, even after drug discontinuation, than controls, a result that could neither be attributed to AED treatment nor to recent epileptic seizures or complicated epilepsy.     

The prevalence of seizures in comatose children in the pediatric intensive care unit: A prospective video‐EEG study

Purpose: Studies in adult and neonatal intensive care units (ICUs) report a high prevalence of epileptic seizures in comatose patients. The prevalence of seizures in pediatric ICUs is variably reported in a few retrospective studies using different electroencephalography (EEG) methods. We aimed to determine prospectively the prevalence of epileptic seizures (clinical and subclinical) in comatose children in the pediatric ICU using continuous video‐EEG (v‐EEG) monitoring. Methods: We performed v‐EEG in consecutive children aged 2 months to 17 years admitted to the pediatric ICU with sustained depressed consciousness over a period of 15 months. Results: We monitored 100 comatose children, 69% within 24 h of ICU admission. Median length of ICU stay was 5 days. Median duration of v‐EEG was 20 h. Epileptic seizures were identified in only seven patients, of whom six had a history of epilepsy with witnessed seizures immediately prior to v‐EEG. All epileptic seizures were recorded in the first 3 h of v‐EEG. Seizures were suspected by ICU staff in 18 monitored patients, only four of whom had confirmed epileptic seizures. Discussion: The lower prevalence of epileptic seizures and the shorter length of ICU stay in children compared to adults and neonates suggest a different spectrum of disease and neurologic response. Short‐duration v‐EEG in patients with a history of prior seizures, epilepsy, or clinical events suspected to be seizures seems more appropriate than routine v‐EEG in all comatose children in the pediatric ICU.     

Alcoholism and Epilepsy

There is a scarcity of population-based epidemiological investigations concerning the prevalence of epilepsy among alcoholics, and of alcoholism among epileptic patients. Available data seem to suggest that the prevalence of epilepsy among alcoholics is at least triple that in the general population, and that alcoholism may be more prevalent among epileptic patients than in the general population. The term "alcoholic epilepsy" has been used with varying definitions in different investigations. It is suggested that a uniform definition be adopted so as to minimize confusion when comparing data from different laboratories. Although there is general agreement that excessive alcohol intake can increase the frequency of seizures in epileptic patients, limited available data suggest that light to moderate social alcohol drinking may not affect seizure frequency. However, epileptic patients should be warned about the possible adverse effects of alcohol, especially those who have refractory forms of epilepsy. Except for a few anomalous cases, evidence for the direct seizure-provoking effect of alcohol is not strong. This is because it is difficult to pinpoint alcohol as the only etiology; more likely, alcohol is only one factor among others (e.g., head trauma, cerebral infarct, alcohol withdrawal, and metabolic effects of alcohol) in provoking seizures. Because seizures are a symptom and not a disease, it is often difficult to distinguish epileptic seizures from alcohol-withdrawal seizures. Patients with only the latter kind of seizures should not need chronic antiepileptic medication.     

Epileptic and nonepileptic features in patients with early onset epileptic encephalopathy and STXBP1 mutations

Purpose: STXBP1 (MUNC18‐1) mutations have been associated with various types of epilepsies, mostly beginning early in life. To refine the phenotype associated with STXBP1 aberrations in early onset epileptic syndromes, we studied this gene in a cohort of patients with early onset epileptic encephalopathy. Methods: STXBP1 was screened in a multicenter cohort of 52 patients with early onset epilepsy (first seizure observed before the age of 3 months), no cortical malformation on brain magnetic resonance imaging (MRI), and negative metabolic screening. Three groups of patients could be distinguished in this cohort: (1) Ohtahara syndromes (n = 38); (2) early myoclonic encephalopathies (n = 7); and (3) early onset epileptic encephalopathies that did not match any familiar syndrome (n = 7). None of the patients displayed any cortical malformation on brain MRI and all were screened through multiple video–electroencephalography (EEG) recordings for a time period spanning from birth to their sixth postnatal month. Subsequently, patients had standard EEG or video‐EEG recordings. Key Findings: We found five novel STXBP1 mutations in patients for whom video‐EEG recordings could be sampled from the beginning of the disease. All patients with a mutation displayed Ohtahara syndrome, since most early seizures could be classified as epileptic spasms and since the silent EEG periods were on average shorter than bursts. However, each patient in addition displayed a particular clinical and EEG feature: In two patients, early seizures were clonic, with very early EEG studies exhibiting relatively low amplitude bursts of activity before progressing into a typical suppression‐burst pattern, whereas the three other patients displayed epileptic spasms associated with typical suppression‐burst patterns starting from the early recordings. Epilepsy dramatically improved after 6 months and finally disappeared before the end of the first year of life for four patients; the remaining one patient had few seizures until 18 months of age. In parallel, EEG paroxysmal abnormalities disappeared in three patients and decreased in two, giving place to continuous activity with fast rhythms. Each patient displayed frequent nonepileptic movement disorders that could easily be mistaken for epileptic seizures. These movements could be observed as early as the neonatal period and, unlike seizures, persisted during all the follow‐up period. Significance: We confirm that STXBP1 is a major gene to screen in cases of Ohtahara syndrome, since it is mutated in >10% of the Ohtahara patients within our cohort. This gene should particularly be tested in the case of a surprising evolution of the patient condition if epileptic seizures and EEG paroxysmal activity disappear and are replaced by fast rhythms after the end of the first postnatal year.     

Cerebral seizures, alcoholism, and deliria (author's transl)]

The occurrence of cerebral seizures in alcoholics was investigated in case histories of 84 delirious and nondelirious male patients. Eighteen patients had seizures before they became alcoholics; the frequency of the seizures increased during abuse. Twelve had no deliria at all up to the moment of this investigation; in 66 of the patients the occurrence of seizures was assumed to be caused by alcohol abuse alone. Seventy-one patients had seizures irrespective of deliria and nearly 40% of them had no deliria at all. In 21% we observed only deliria with seizures; in 16% only deliria without seizures; and 24% had deliria both with and without seizures. The remaining 13 patients of 84 had only deliria complicated by cerebral seizures; only 3 had deliria without seizures. The seizures occurred as grand mal in 94% of the alcoholics, in all patients with genuine epilepsy, and in 60% of the patients with post-traumatic epilepsy.     

Sleep EEG with or without sleep deprivation? Does sleep deprivation activate more epileptic activity in patients suffering from different types of epilepsy?

A sleep EEG of 190 patients without sleep deprivation was recorded, followed by a sleep EEG after 24 h of sleep deprivation on the next day. The patients suffered from various types of epilepsy, in their routine EEGs no epileptic discharges were seen. Both sleep EEGs were recorded under the same antiepileptic drugs. A waking EEG was recorded immediately before each sleep EEG. The activation rates of epileptic activity in 52.6% (without sleep deprivation) and 53.2% (with sleep deprivation) of the patients showed no significant differences. Also on classifying the epileptic discharges no real difference was found between the 2 methods (generalized: 29.5 vs. 29.5%, generalized with lateral emphasis: 11.1 vs. 9.5%, focal: 12.1 vs. 14.2%). Only in the waking EEG, recorded immediately before the sleep EEG after sleep deprivation, a few more patients showed epileptic discharges (33.6 vs. 27.4%). Without there being any significant differences between the 2 methods there were some different results in comparing the EEG with the clinical findings: significantly more epileptic activity was shown in patients who had their first seizure before the age of 20 (55.6 and 55.6% vs. 26.3 and 31.6%), amongst females (59.8 and 61.9% vs. 45.2 and 44.1%), in awakening grand mal (= primary generalized tonic-clonic seizures, 76.5 and 70%) and in absences (69 and 72.4%). The higher activation rates in young subjects, in patients with a family history of seizures, with pathological neurological findings, mental retardation and delayed psychomotoric development in early childhood, were not statistically significant.(ABSTRACT TRUNCATED AT 250 WORDS)     

Electroclinical features of epilepsy in patients with juvenile type dentatorubral-pallidoluysian atrophy

Purpose: To clarify the electroclinical characteristics of epileptic seizures in patients with juvenile type dentatorubral‐pallidoluysian atrophy (DRPLA). Methods: Seventeen patients with juvenile type DRPLA confirmed by genetic analysis were studied retrospectively. The clinical records of all 17  patients and the ictal video electroencephalography (EEG) recordings from 12 of the 17 patients were reviewed. Results: Electroclinical studies in 12 patients identified 11 habitual seizures in 6 patients as partial seizures on ictal video EEG recordings. Clinical manifestations composed mainly of versions of the head and loss of consciousness. These partial seizures were persistently recorded throughout the clinical course. Brief generalized seizures (atypical absence and myoclonic seizure) were observed in 6 of 12 patients at the early stage. In contrast, generalized tonic–clonic seizures (GTCS) were recorded in four advanced stage patients who were almost bedridden. Semiological studies in 17 patients showed that the prevalence of partial seizures was significantly higher in patients with younger epilepsy onset (below 10 years of age; χ² test, p < 0.05) and that the age of epilepsy onset was significantly lower in patients with partial seizures than in those without partial seizures (Mann‐Whitney U test, p = 0.02). However, the number of CAG repeats and age at clinical onset were not significantly different between two groups. Discussion: Partial seizure is one of the common epileptic features in juvenile type DRPLA, especially in patients with younger epilepsy onset. Seizure types may be affected in an age‐dependent manner and change evolutionally during progression of the clinical stage.     

Subclinical epileptiform activity accelerates the progression of Alzheimer’s disease: A long-term EEG study

ObjectiveWhile many studies suggest that patients with Alzheimer’s disease have a higher chance for developing epileptic seizures, only a few studies are available examining independent epileptic discharges. The major aims of our study was to determine the prevalence of subclinical epileptiform activity (SEA) in AD compared to healthy elderly controls with the hypothesis that SEA is more frequent in AD than in cognitively normal individuals. Another aim was to analyze the effect of baseline SEA captured with electroencephalography on the progression of the disease with longitudinal cognitive testing.MethodsWe investigated 52 Alzheimer patients with no history of epileptic seizures and 20 healthy individuals. All participants underwent a 24-hour electroencephalography, neurology, neuroimaging and neuropsychology examination. Two independent raters analyzed visually the electroencephalograms and both raters were blind to the diagnoses. Thirty-eight Alzheimer patients were enrolled in a 3-year long prospective follow-up study with yearly repeated cognitive evaluation.ResultsSubclinical epileptiform discharges were recorded significantly (p:0.018) more frequently in Alzheimer patients (54%) than in healthy elderly (25%). Epileptiform discharges were associated with lower performance scores in memory. Alzheimer patients with spikes showed 1.5-times faster decline in global cognitive scores than patients without (p < 0.001). The decline in cognitive performance scores showed a significant positive correlation with spike frequency (r:+0.664; p < 0.001).ConclusionsSubclinical epileptiform activity occurs in half of Alzheimer patients who have never suffered epileptic seizures. Alzheimer patients with subclinical epileptiform activity showed accelerated cognitive decline with a strong relation to the frequency and spatial distribution (left temporal) of spikes.SignificanceOur findings suggest the prominent role of epileptiform discharges in the pathomechanism of Alzheimer's disease which might serve as potential therapeutic target.     

Approximate entropy of the electroencephalogram in healthy awake subjects and absence epilepsy patients.

The approximate entropy (ApEn) of signals in the electroencephalogram (EEG) was evaluated in 8 healthy volunteers and in 10 patients with absence epilepsy, both during seizure-free and seizure intervals. We estimated the nonlinearity of each 3-sec EEG segment using surrogate data methods. The mean (+/- SD) ApEn in EEG was 0.83 +/- 0.22 in healthy subjects awake with eyes closed. It was significantly lower during epileptic seizures (0.48 +/- 0.05) than during seizure-free intervals (0.80 +/- 0.13) (P < 0.001). Nonlinearity was clearly detected in EEG signals from epileptic patients during seizures but not during seizure-free intervals or in EEG signals from healthy subjects. The ApEn of EEG signals estimated over consecutive intervals could serve to determine pathological brain activity such as that occurring during absence epilepsy.     

Epilepsy and EEG paroxysmal abnormalities in autism spectrum disorders

The occurrence of epilepsy in autism is variable; nevertheless, EEG paroxysmal abnormalities (PA) are frequently recorded in patients with autism, although the influence of epilepsy and/or EEG PA on the autistic regression has not been clarified yet. We examine a large sample of 345 inpatients with autism, divided into three groups: (1) patients without epilepsy and EEG PA; (2) patients with EEG PA but no seizures; (3) patients with epilepsy including febrile convulsions. The prevalence of epilepsy (24.9%) and EEG PA (45.5%) was higher than that reported in the general population. The significant differences among the three groups concerned autistic regression (comparison between groups 1 and 2, p < 0.05; comparison between groups 1 and 3, p < 0.01), cerebral lesions (comparison between groups 1 and 2, p < 0.05; between groups 1 and 3, p < 0.001), and symptomatic autism (comparison between groups 1 and 2 as much as comparison between groups 1 and 3, p < 0.001), which were prevalent in groups 2 and 3; while severe/profound mental retardation was more frequent in group 3 compared to group 1 (p < 0.01). Focal epilepsy (43.0%) and febrile convulsions (33.7%) were frequent in the third group with epilepsy. EEG PA were mainly localized in temporal and central areas (31.4%). Only 2.6% of patients had subcontinuous/continuous EEG PA during sleep. Seizures and EEG PA were not related to autistic regression. EEG PA occurred mainly in childhood, while epilepsy tended to occur (p < 0.001) as age increased. The age at onset of seizures had two peaks: between 0 and 5 and between 10 and 15 years with no difference between idiopathic and symptomatic cases. In 58.5% of subjects aged ?20 years, epilepsy including febrile seizures occurred at some point of their lives, while cases with only EEG PA were less frequent (9.7%). The relationship among autism, EEG PA and epilepsy should be clarified and investigated. In autism, seizures and EEG PA could represent an epiphenomenon of a cerebral dysfunction independent of apparent lesions.