Feasibility, tolerability and efficacy of the ketogenic diet in children with drug-resistant epilepsy in Vietnam.

OBJECTIVES: According to the WHO, more than 50 million people have epilepsy. Among them, nearly 80% of patients with epilepsy live in developing countries and 75% of them do not have access to treatment. The ketogenic diet (KD) has been shown as an effective alternative for patients with drug-resistant epilepsy. Although it has been studied in Asia, no such studies have been conducted in Vietnam. The purpose of this study was to verify the feasibility and tolerability of KD in children with refractory epilepsies in Vietnam. METHODS: Children with drug-resistant epilepsy followed at Children's Hospital, Vietnam treated by KD were included in a prospective study from June 2019 to October 2021. Side-effects, retention rate, number, and duration of seizures were recorded after 1, 3, 6, 9 and 12 months of KD. Patients were considered as respondents when a 50% seizure frequency was reached. Tolerance and acceptability of the KD were closely monitored. RESULTS: Forty-six children were included but KD was contraindicated for one patient. Due to the COVID pandemic, we had to rely on internet exchanges to stay in touch with families. Meals had to be adapted to Vietnamese culinary habits. The retention rate decreased from 82.2% at 1 month to 40% at 12 months of follow-up. The incidence of side effects was 44.4% and occurred mainly during the first month. Fifteen patients out of 45 were considered as responders after 12 months. SIGNIFICANCE: Our study was the first attempt to introduce KD in Vietnam. It demonstrated that this diet was feasible and well tolerated. The KD diet resulted in significant improvement for 30% of our patients with drug-resistant epilepsy. This percentage is lower than in some studies but warrants the use of KD as a valuable alternative in a country where many patients lack access to recent treatments.

Determining ICU EEG periodic patterns and why it matters.

Historically, periodic EEG patterns were described as any pattern with stereotyped paroxysmal complexes occurring at regular intervals, i.e., the period (T). T is the sum of the duration of the waveform (t1) and, eventually, the duration of the interval between two consecutive waves (t2). The American Clinical Neurophysiology Society introduced the concept of a clearly discernible inter-discharge interval between consecutive waveforms (i.e., t2). As this definition was not applied to what have previously been termed triphasic waves and in some cases of lateralized periodic discharges, we propose reconsideration of terminology that includes historical use of definitions. This will allow the development and usage of the concept for periodic EEG patterns as any runs of stereotyped paroxysmal waveforms separated by nearly identical intervals and prolonged repetitive complexes on the EEG. Prolonged expression means EEG is recorded for a sufficient period of time to prove that the pattern is repetitive, thus resulting in a monomorphic/monotonous pattern. More important than the inter-discharge interval (t2), periodic EEG patterns occur at time regular intervals (T). As a result, periodic EEG activity should be considered along a continuum and not the opposite of rhythmic EEG activity where no interval activity exists between consecutive waveforms.

Epilepsy surgery program in a resource-limited setting in Vietnam: A multicentered collaborative model.

OBJECTIVE: Although epilepsy surgery is more effective than medical therapy for drug-resistant patients, it is underutilized in both high-income and low- and middle-income countries. In light of our efforts to establish an epilepsy surgery program in a resource-limited setting, this study aimed to determine the outcome of the epilepsy surgery program in Ho Chi Minh City (HCMC), Vietnam. METHODS: In 2018, we developed the HCMC epilepsy core multidisciplinary team with members from various hospitals and centers. The team typically included neurologists, neurosurgeons, neuropsychologists, psychiatrists, and nursing specialists. Presurgical evaluations were performed for patients with drug-resistant epilepsy, fulfilling the ILAE criteria, with an epileptogenic lesion (mesial temporal sclerosis, low-grade gliomas, or focal cortical dysplasia). All epilepsy surgeries were performed in two epilepsy surgery centers in HCMC between 2018 and 2021. The patients were followed up for at least 12 months. RESULTS: Fifty-two patients with drug-resistant epilepsy underwent presurgical evaluation, of which 35 underwent surgery. Among the 52 patients, 20 (38.5%) underwent surgery after showing concordance among the results of standard presurgical assessments such as semiology, scalp interictal or ictal electroencephalography, and brain imaging. Among the 26 people with epilepsy who required more advanced evaluations, 15 underwent surgery with intraoperative electrocorticography to delineate the optimal resection borders. The outcomes of Engel Class I and Class II were achieved in 29/35 (82.8%) and 6/35 (17.2%) patients, respectively. SIGNIFICANCE: The epilepsy surgery program with a multicentered collaborative model in a resource-limited setting showed favorable outcomes in HCMC, Vietnam.

Lateralized Periodic Discharges: Which patterns are interictal, ictal, or peri-ictal?

There is an ongoing debate if Lateralized Periodic Discharges (LPDs) represent an interictal pattern reflecting non-specific but irritative brain injury, or conversely, is an ictal pattern. The challenge is: how to correctly manage these patients? Between this apparent dichotomous distinction, there is a pattern lying along the interictal-ictal continuum (IIC) that we may call "peri-ictal". Peri-ictal means that LPDs are temporally associated with epileptic seizures (although not necessarily in the same recording). Their recognition should lead to careful EEG monitoring and longer periods of video-EEG to detect seizure activity (clinical and/or subclinical seizures). In order to distinguish which kind of LPDs should be considered as representing interictal/irritative brain injury versus ictal/peri-ictal LPDs, a set of criteria, with both clinical/neuroimaging and EEG, is proposed. Among them, the dichotomy LPDs-proper versus LPDs-plus should be retained. Spiky or sharp LPDs followed by associated slow after-waves or periods of flattening giving rise to a triphasic morphology should be included in the definition of LPDs-plus. We propose defining a particular subtype of LPDs-plus that we call "LPDs-max". The LPDs-max pattern corresponds to an ictal pattern, and therefore, a focal non-convulsive status epilepticus, sometimes associated with subtle motor signs and epileptic seizures. LPDs-max include periodic polyspike-wave activity and/or focal burst-suppression-like patterns. LPDs-max have a posterior predominance over the temporo-parieto-occipital regions and are refractory to antiseizure drugs. Interpretations of EEGs in critically ill patients require a global clinical approach, not limited to the EEG patterns. The clinical context and results of neuroimaging play key roles.

Closed-loop insulin delivery in adults with type 1 diabetes in real-life conditions: a 12-week multicentre, open-label randomised controlled crossover trial.

BACKGROUND: Closed-loop insulin delivery systems are expected to become a standard treatment for patients with type 1 diabetes. We aimed to assess whether the Diabeloop Generation 1 (DBLG1) hybrid closed-loop artificial pancreas system improved glucose control compared with sensor-assisted pump therapy. METHODS: In this multicentre, open-label, randomised, crossover trial, we recruited adults (aged ≥18 years) with at least a 2 year history of type 1 diabetes, who had been treated with external insulin pump therapy for at least 6 months, had glycated haemoglobin (HbA1c) of 10% or less (86 mmol/mol), and preserved hypoglycaemia awareness. After a 2-week run-in period, patients were randomly assigned (1:1) with a web-based system in randomly permuted blocks of two, to receive insulin via the hybrid closed-loop system (DBLG1; using a machine-learning-based algorithm) or sensor-assisted pump therapy over 12 weeks of free living, followed by an 8-week washout period and then the other intervention for 12 weeks. The primary outcome was the proportion of time that the sensor glucose concentration was within the target range (3·9-10·0 mmol/L) during the 12 week study period. Efficacy analyses were done in the modified intention-to-treat population, which included all randomly assigned patients who completed both 12 week treatment periods. Safety analyses were done in all patients who were exposed to either of the two treatments at least once during the study. This trial is registered with ClinicalTrials.gov, number NCT02987556. FINDINGS: Between March 3, 2017, and June 19, 2017, 71 patients were screened, and 68 eligible patients were randomly assigned to the DBLG1 group (n=33) or the sensor-assisted pump therapy group (n=35), of whom five dropped out in the washout period (n=1 pregnancy; n=4 withdrew consent). 63 patients completed both 12 week treatment periods and were included in the modified intention-to-treat analysis. The proportion of time that the glucose concentration was within the target range was significantly higher in the DBLG1 group (68·5% [SD 9·4] than the sensor-assisted pump group (59·4% [10·2]; mean difference 9·2% [95% CI 6·4 to 11·9]; p<0·0001). Five severe hypoglycaemic episodes occurred in the DBLG1 group and three episodes occurred in the sensor-assisted pump therapy group, which were associated with hardware malfunctions or human error. INTERPRETATION: The DBLG1 system improves glucose control compared with sensor-assisted insulin pumps. This finding supports the use of closed-loop technology combined with appropriate health care organisation in adults with type 1 diabetes. FUNDING: French Innovation Fund, Diabeloop.

Contact, high-resolution spatial diffuse reflectance imaging system for skin condition diagnosis.

Spatially resolved diffuse reflectance spectroscopy (srDRS) is a well-established technique for noninvasive, in vivo characterization of tissue optical properties toward diagnostic applications. srDRS has a potential for depth-resolved analysis of tissue, which is desired in various clinical situations. However, current fiber-based and photodiode-based systems have difficulties achieving this goal due to challenges in sampling the reflectance with a high enough resolution. We introduce a compact, low-cost architecture for srDRS based on the use of a multipixel imaging sensor and light-emitting diodes to achieve lensless diffuse reflectance imaging in contact with the tissue with high spatial resolution. For proof-of-concept, a prototype device, involving a commercially available complementary metal-oxide semiconductor coupled with a fiber-optic plate, was fabricated. Diffuse reflectance profiles were acquired at 645 nm at source-to-detector separations ranging from 480 µm to 4 mm with a resolution of 16.7 µm. Absorption coefficients (µa) and reduced scattering coefficients (µs') of homogeneous tissue-mimicking phantoms were measured with 4.2 ± 3.5 % and 7.0 ± 4.6 % error, respectively. The results obtained confirm the potential of our approach for quantitative characterization of tissue optical properties in contact imaging modality. This study is a first step toward the development of low-cost, wearable devices for skin condition diagnosis in vivo.

Design and development of an impedimetric-based system for the remote monitoring of home-based dialysis patients.

A key clinical challenge is to determine the desired 'dry weight' of a patient in order to terminate the dialysis procedure at the optimal moment and thus avoid the effects of over- and under-hydration. It has been found that the effects of haemodialysis on patients can be conveniently monitored using whole-body bioimpedance measurements. The identified need of assessing the hydrational status of patients undergoing haemodialysis at home gave rise to the present Dialydom (DIALYse à DOMicile) project. The aim of the project is to develop a convenient miniaturised impedance monitoring device for localised measurements (on the calf) in order to estimate an impedimetric hydrational index of the home-based patient, and to transmit this and other parameters to a remote clinical site. Many challenges must be overcome to develop a robust and valid home-based device. Some of these are presented in the paper.

Automatic identification of physical activity types and sedentary behaviors from triaxial accelerometer: laboratory-based calibrations are not enough.

"Objective" methods to monitor physical activity and sedentary patterns in free-living conditions are necessary to further our understanding of their impacts on health. In recent years, many software solutions capable of automatically identifying activity types from portable accelerometry data have been developed, with promising results in controlled conditions, but virtually no reports on field tests. An automatic classification algorithm initially developed using laboratory-acquired data (59 subjects engaging in a set of 24 standardized activities) to discriminate between 8 activity classes (lying, slouching, sitting, standing, walking, running, and cycling) was applied to data collected in the field. Twenty volunteers equipped with a hip-worn triaxial accelerometer performed at their own pace an activity set that included, among others, activities such as walking the streets, running, cycling, and taking the bus. Performances of the laboratory-calibrated classification algorithm were compared with those of an alternative version of the same model including field-collected data in the learning set. Despite good results in laboratory conditions, the performances of the laboratory-calibrated algorithm (assessed by confusion matrices) decreased for several activities when applied to free-living data. Recalibrating the algorithm with data closer to real-life conditions and from an independent group of subjects proved useful, especially for the detection of sedentary behaviors while in transports, thereby improving the detection of overall sitting (sensitivity: laboratory model = 24.9%; recalibrated model = 95.7%). Automatic identification methods should be developed using data acquired in free-living conditions rather than data from standardized laboratory activity sets only, and their limits carefully tested before they are used in field studies.

A comparison of ERP spatial filtering methods for optimal mental workload estimation.

Mental workload estimation is of crucial interest for user adaptive interfaces and neuroergonomics. Its estimation can be performed using event-related potentials (ERPs) extracted from electroencephalographic recordings (EEG). Several ERP spatial filtering methods have been designed to enhance relevant EEG activity for active brain-computer interfaces. However, to our knowledge, they have not yet been used and compared for mental state monitoring purposes. This paper presents a thorough comparison of three ERP spatial filtering methods: principal component analysis (PCA), canonical correlation analysis (CCA) and the xDAWN algorithm. Those methods are compared in their performance to allow for an accurate classification of mental workload when applied in an otherwise similar processing chain. The data of 20 healthy participants that performed a memory task for 10 minutes each was used for classification. Two levels of mental workload were considered depending on the number of digits participants had to memorize (2/6). The highest performances were obtained using the CCA filtering and the xDAWN algorithm respectively with 98% and 97% of correct classification. Their performances were significantly higher than that obtained using the PCA filtering (88%).

First-ever population-based study on status epilepticus in French Island of La Reunion (France) - incidence and fatality.

PURPOSE: We aimed to determine the incidence and case-fatality of first-ever status epilepticus (SE) among the general population living in La Reunion Island, a French overseas territory in the Indian Ocean near Madagascar. METHODS: We recruited cases (1st July 2004-30th June 2005) in a population-based manner using neurology, neurosurgery, electroencephalogram, emergency, paediatric and neuroradiology services; emergency medical aid service; emergency and admission service of private and public clinics; neurologists (public and private); private paediatricians and practitioners of various rural hospitals. All cases had an electroencephalogram (EEG) and were assessed by an epileptologist. Standard definition and classification schemes were used. Those with known epilepsy were not part of this analysis. RESULTS: Sixty-five cases (males: n=41, 63.1%) had epileptologist-confirmed SE, with 38.5% (n=25) being >60 years of age. Global incidence rate was 8.52/100 000 (95% confidence interval 6.5-10.5). A bimodal age distribution with high frequency and incidence among young (<10 years age) (frequency: 12.3%; incidence 6.6/100,000) and aged (>60 years) (frequency: 40.0%; incidence 35.0/100,000) was observed. We found that 60%, 32.3%, 6.7% had convulsive, partial and non-convulsive SE respectively (1% remained unclassified). Of the cases identified, 44.6%, 38.5%, 16.9% had unprovoked, provoked or cryptogenic seizures respectively. The most important aetiological factors identified included: stroke (27.7%), alcoholism/toxicity (18.5%), cryptogenic (16.9%), infections (10.8%). Mortality was 18.5%. CONCLUSION: The incidence of SE incidence in La Reunion Island was lower than that described elsewhere. The status type was found to be dependent on aetiology and age. The study confirms that SE is more frequent in men and in older adults and is associated with significant short-term case mortality.

Improving activity recognition using temporal coherence.

Assessment of daily physical activity using data from wearable sensors has recently become a prominent research area in the biomedical engineering field and a substantial application for pattern recognition. In this paper, we present an accelerometer-based activity recognition scheme on the basis of a hierarchical structured classifier. A first step consists of distinguishing static activities from dynamic ones in order to extract relevant features for each activity type. Next, a separate classifier is applied to detect more specific activities of the same type. On top of our activity recognition system, we introduce a novel approach to take into account the temporal coherence of activities. Inter-activity transition information is modeled by a directed graph Markov chain. Confidence measures in activity classes are then evaluated from conventional classifier's outputs and coupled with the graph to reinforce activity estimation. Accurate results and significant improvement of activity detection are obtained when applying our system for the recognition of 9 activities for 48 subjects.

Estimation of physical activity monitored during the day-to-day life by an autonomous wearable device (SVELTE project).

Physical activity (PA) and the energy expenditure it generates (PAEE) are increasingly shown to have impacts on everybody's health (e.g. development of chronic diseases) and to be key factors in maintaining the physical autonomy of elderlies. The SVELTE project objective was to develop an autonomous actimeter, easily wearable and with several days of autonomy, which could record a subject's physical activity during his/her daily life and estimate the associated energy expenditure. A few prototypes and dedicated algorithms were developed based on laboratory experiments. The identification of physical activity patterns algorithm shows good performances (79% of correct identification), based on a trial in semi-free-living conditions. The assessment of the PAEE computation algorithm is under validation based on a clinical trial.

Newly-diagnosed epileptic seizures in three populations: Geneva (EPIGEN), Martinique (EPIMART), and the Reunion Island (EPIREUN).

AIM: The objective was to analyse and discuss data from three studies of newly-diagnosed epileptic seizures (provoked and unprovoked) conducted in Geneva, Martinique, and the Reunion Island, in which the same methodology was used. METHODS: We extracted data from three studies in which the incidence of seizures was estimated and aetiologies identified. Data was extracted and analysed using STATA. Group comparison was performed firstly for each study as a single group, and secondly by considering Martinique and the Reunion Island as an overseas group, in comparison with Geneva, considered as a mainland group. Uncorrected χ(2)was used and statistical significance (two-sided, p=0.05) was determined for each aetiology per cohort. RESULTSThe incidence of newly-diagnosed epileptic seizures per 100,000 was 71.0, 80.6, and 100.4 in Geneva, Martinique, and the Reunion Island, respectively. A bimodal distribution and predominance of generalised seizures was noted. The male to female ratio was higher in Martinique (∼2.0) than other populations (∼1.5). Status epilepticus was noted in Geneva and more so in the Reunion Island. The incidence of provoked seizures per 100,000 was 25.2, 16.4, and 17.7, and for unprovoked seizures was 45.6, 64.1, and 81.2 in Geneva, Martinique, and the Reunion Island, respectively. There was a greater risk of provoked seizures in Geneva relative to the overseas group, which was due to tumours, use of toxic substances, and drug abuse. The risk of unprovoked seizures in Geneva was due to trauma and infections. In Martinique, alcoholism and HIV were foremost factors for provoked and unprovoked seizures, and stroke was an important aetiology in both Martinique (provoked seizures) and the Reunion Island (unprovoked seizures). CONCLUSION: The risk of provoked seizures was greatest in Geneva and risk of unprovoked seizures was greatest in the Reunion Island. Toxic substances, alcohol, infection, and trauma constituted major factors for epileptic seizures in Geneva, while alcoholism, HIV, and stroke were major factors in the overseas group. Relative eradication of tropical infections has paved a way for the emergence of non-communicable aetiologies (stroke, alcoholism). Males from Martinique demonstrated the greatest risk of epileptic seizures, signifying the importance of alcoholism, HIV, etc. Three steps should follow: follow-up studies (mortality), strong mechanisms for prevention (or control) of risk factors, guidelines on whether to treat or not.

Newly diagnosed epileptic seizures: focus on an elderly population on the French island of Réunion in the Southern Indian Ocean.

PURPOSE: To describe seizure types and risk factors among elderly people with newly diagnosed epileptic seizures living on La Réunion, a French Island in the Southern Indian Ocean. METHODS: We describe an elderly population with newly diagnosed epileptic seizures using data from the EPIREUN study conducted between July 1, 2004 and June 30, 2005. The methodology is described in detail in the EPIREUN study report (Mignard et al., 2009). KEY FINDINGS: There were 153 single unprovoked seizures (84.1%); their incidence was 278.1 [95% confidence interval (CI) 237.4-325.9] per 100,000. The incidence of newly diagnosed epilepsy was 125.4 (95% CI, 99.1-158.8) per 100,000. Twenty-eight acute symptomatic seizures occurred (15.4%); the incidence was 50.9 (95% CI 35.1-73.7) per 100,000. The annual incidence of newly diagnosed epileptic seizure in the elderly was 330.8 (95% CI 286.1-382.6) per 100,000: 403.0 (95% CI 328.5-494.3) per 100,000 in men and 279.6 (95% CI, 227.4-343.8) per 100,000 in women. Sex had a significant (p = 0.014) effect on incidence: elderly men had a risk ratio of 1.44 compared to women of developing a newly diagnosed epileptic seizure. The etiology of single unprovoked seizure was as follows: stroke, 77 cases (50.3%); cryptogenic, 36 (23.5%); alcoholism, 10 (6.6%); a combination of several causes such as polypathology, 9 (5.9%); degenerative disease, 6 (4.0%); HIV infection, 2 (2.0%), and undetermined causes (2.7%). Most patients (170; 93.4%) were hospitalized, and 110 (60.8%) were treated. Among patients treated, 49 (44.5%) were given sodium valproate, 25 (22.7%) benzodiazepines, 12 (10.9%) phenytoin, 9 (8.2%) lamotrigine, 8 (7.3%) Trileptal, and 7 (6.4%) gabapentin. SIGNIFICANCE: Our findings show that the incidences of newly diagnosed epileptic seizures and newly diagnosed epilepsy were high in the elderly population of La Réunion. These incidences were significantly higher in men than in women. These results may be attributable to the high incidence of cerebrovascular diseases and comorbidities in this population.

A Bayesian approach for epileptic seizures detection with 3D accelerometers sensors.

In this paper, an algorithm able to detect epilepsy seizure based on 3D accelerometers and with patient adaptation is presented. This algorithm is based on a Bayesian approach using hidden Markov models for statistical modelling of moves signals. A particular focus is set on the learning procedure and in particular on its initialisation to ensure a good learning and to avoid numerical instability. Numerical simulations show that, without inhibition of the detection algorithm when the person is standing up, the algorithm is able to detect close to 90% of seizures when false alarms are 25% of alarms.

A graph based algorithm for postures estimation based on accelerometers data.

An algorithm is presented in this paper to estimate the activity of a person at each time index through a Bayesian approach. It does not require any pre-processing to identify single activity parts in the signal but can generate some instability in the estimated sequences of activities due to its nature. To circumvent this issue, the decision is enforced with a graph setting constraints between the different activities to be detected. As the method is based on a Bayesian approach, training can be used to adapt the algorithm to each person. If so, the algorithm shows very good performance.

Detection system of motor epileptic seizures through motion analysis with 3D accelerometers.

A system of epilepsy seizure detection in real life conditions and based on inertial sensors is presented in this paper with a focus on the signal processing to recognize seizure moves. This system is based on several models of signals, one corresponding to general movements, and two others describing seizures moves. The detection algorithm evaluates for a given time window which model fits the best with the observed signals and trigger an alarm if this model is a seizure model. The signal processing algorithm is based on hidden Markov models.

A survey of public knowledge, attitudes, and practices with respect to epilepsy in Badissa village, centre region of Cameroon.

OBJECTIVE: The aim of this study was to assess knowledge, attitudes, and practices (KAP) with respect to epilepsy in Badissa, as part of a series of studies mandated by the Cameroon Ministry of Public Health. METHOD: We interviewed 164 subjects face-to-face during a door-to-door survey. RESULTS: All of the subjects had heard about epilepsy; 98.8% knew at least one patient with epilepsy, and 97.6% had seen at least one epileptic seizure. With respect to attitudes, 16% and 32% would respectively prevent their children from associating with and marrying, people with epilepsy; 55.5% would offer people with epilepsy equal employment. The independent determinants of attitudes were the belief that epilepsy is a form of insanity (P=0.004) or is caused by a mental illness (P=0.003), having read about epilepsy (P=0.018), and being married (P=0.007). CONCLUSIONS: Our study demonstrates a high level of awareness and fairly good knowledge of epilepsy, a lower level of misconceptions, and better attitudes, in the study area confirming our hypothesis of a regional variation in these characteristics. This model of care may be useful in scaling up the epilepsy education program in Cameroon.

Incidence of newly diagnosed epileptic seizures in a French South Indian Ocean Island, La Réunion (EPIREUN).

PURPOSE: To assess the incidence of newly diagnosed epileptic seizures in the population of La Réunion. METHODS: From July 1, 2004 to June 30, 2005, we conducted a prospective, observational, and multicenter epidemiologic study to identify patients with newly diagnosed epileptic seizures. Febrile and neonatal seizures were excluded. RESULTS: Seven hundred sixty-six patients were included. The standardized (2000 U.S. population) incidence rate of all suspected cases of newly diagnosed (provoked and unprovoked) epileptic seizures was 115.4/100.000 person-years [95% confidence interval (CI) 106.7-124.0]. We observed a bimodal distribution: The crude incidence was 99.5/100,000 in the group aged 0-14 years and 330.8/100,000 in those older than 65 years. One hundred thirty-five cases were classified as provoked seizures (17.6%; incidence 17.7/100,000). Alcohol consumption, cranial trauma, and cerebrovascular disease were the most frequent causes (27.4%, 11.1%, and 10.4%, respectively). Six hundred twenty cases were classified as unprovoked seizures (single and recurrent) (80.9%; incidence, 81.2/100,000). Two hundred sixty cases of seizures were due to stable neurologic conditions (incidence, 34.1/100,000) and the most common causes were cerebrovascular disease (46.2%), alcoholism (20.4%), and cranial trauma (5.4%). Evolutive neurologic conditions contributed to 23 cases (incidence, 3.0/100,000). Lastly, unprovoked seizures with unknown etiology were 337 (incidence, 44.2/100,000). CONCLUSIONS: The global incidence rate of newly diagnosed epileptic seizures in La Réunion was clearly higher than those observed in industrialized countries and similar to those observed in developing countries. The major risk factors were represented by cerebrovascular disease, alcohol consumption, and cranial trauma. Surprisingly, there were few infections.