Epilepsy and Variables. Department of Neurology, Hospital de Clínicas from 2016 to 2018

González, Silvia Adriana; Galeano, Martha Sady; Morel, Maida; Díaz, Luis Fernando; González, Romina

doi:10.18004/anales/2019.052.03.47-052

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…Focal seizures are the predominant type worldwide, constituting up to two-thirds of epilepsies cases ( 24 ). According to our study, González et al ( 23 ) observed that 63.34% of patients with epilepsy presented with focal seizures. In contrast, the Argentine study has shown that seizures were generalized in 37 (58.0%) and focal in 24 (38.0%) patients with epilepsy ( 21 ).…”

Section: Discussionsupporting

confidence: 55%

“…In the Argentine study, the prevalence rate of epilepsy was 5.3/1,000 for male patients and 7.1/1,000 for female patients ( 21 ). González et al ( 23 ) have analyzed patients with epilepsy in Paraguay found 51.9% of male patients. Moreover, a review study considering North, Central, and South America, Europe, and Asia, between 1985 and 2007 ( 24 ) has found a higher prevalence rate of epilepsy in men than in women.…”

Section: Discussionmentioning

confidence: 99%

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Epidemiologic Profile of Patients With Epilepsy in a Region of Southeast Brazil: Data From a Referral Center

et al. 2022

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IntroductionEpilepsy affects about 50 million people worldwide, 80% of whom live in low- and middle-income countries. In Brazil, epidemiological studies are outdated and restricted to specific regions, mostly due to the continental size of country.ObjectiveWe aimed to present the first evidence-based study on the epidemiological aspects of individuals with epilepsy, mapping the characteristics of this disease in a referral center in a region of Southeast Brazil.MethodsA retrospective study was carried out from January 2010 to March 2021. Patients were selected according to the International League Against Epilepsy Criteria.ResultsFrom a total of 618 selected patients, 317 (51.3%) were men and 301 (48.7%) were women with an average age of 34.03 ± 20.66 years. The average age at the first seizure was 15.16 ± 17.61 years. The prevalence ratio was 1.30 cases/1,000 habitants. Childhood febrile seizure was present in 44 patients (7.9%) and family history of epilepsy in 231 (37.4%) patients. The predominant type of seizure was focal in 401 (64.9%) patients. The most frequent etiologies were structural in 254 (41.1%) patients and unknown in 238 (38.5%) patients. Most of the patients' treatments were based on anti-seizure drugs in monotherapy [389 (62.9%)] with 398 (64.4%) drug-responsive patients.ConclusionsOur epilepsy prevalence rate was lower than other studies in the Southeast Region of Brazil. In addition, the structural epilepsy type was predominant in our study compared with unknown causes, which is more frequent in other Brazilian regions and worldwide studies. The differences may be attributed to our region, which presents a high prevalence of neuroinfection, specially neurocysticercosis, and a referral center for traumatic brain injury. Moreover, the contrasting results reinforce the need for an adequate epidemiological assessment of epilepsy incidence in a region of Southeast Brazil.

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Section: Discussionsupporting

confidence: 55%

Section: Discussionmentioning

confidence: 99%

Epidemiologic Profile of Patients With Epilepsy in a Region of Southeast Brazil: Data From a Referral Center

et al. 2022

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Epileptic Seizure Prediction Using Attention Augmented Convolutional Network

Liu,

Dong,

Bian

et al. 2023

Int. J. Neur. Syst.

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Early seizure prediction is crucial for epilepsy patients to reduce accidental injuries and improve their quality of life. Identifying pre-ictal EEG from the inter-ictal state is particularly challenging due to their nonictal nature and remarkable similarities. In this study, a novel epileptic seizure prediction method is proposed based on multi-head attention (MHA) augmented convolutional neural network (CNN) to address the issue of CNN’s limit of capturing global information of input signals. First, data enhancement is performed on original EEG recordings to balance the pre-ictal and inter-ictal EEG data, and the EEG recordings are sliced into 6-second-long EEG segments. Subsequently, EEG time-frequency distribution is obtained using Stockwell transform (ST), and the attention augmented convolutional network is employed for feature extraction and classification. Finally, post-processing is utilized to reduce the false prediction rate (FPR). The CHB-MIT EEG database was used to evaluate the system. The validation results showed a segment-based sensitivity of 98.24% and an event-based sensitivity of 94.78% with a FPR of 0.05/h were yielded, respectively. The satisfying results of the proposed method demonstrate its possible potential for clinical applications.

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Epilepsy and Variables. Department of Neurology, Hospital de Clínicas from 2016 to 2018

Cited by 2 publications

References 3 publications

Epidemiologic Profile of Patients With Epilepsy in a Region of Southeast Brazil: Data From a Referral Center

Epidemiologic Profile of Patients With Epilepsy in a Region of Southeast Brazil: Data From a Referral Center

Epileptic Seizure Prediction Using Attention Augmented Convolutional Network

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