The adolescent or adult with generalized tonic-clonic seizures

Aims: This study was undertaken to determine the prevalence of active epilepsy, assess the sociodemographic profile, and psychological aspects of epilepsy in the Jaipur district of Rajasthan, India. Methods: We conducted a community-based, cross-sectional observational study covering both rural (n = 165,660) and urban (n = 179,142) populations of Jaipur district using a house-to-house survey. An adapted, pre-designed World Health Organization screening questionnaire was used to identify the cases. Those confirmed by neurologists as true seizures were included in the study. Cases were classified as per the International League against Epilepsy recommendation. Global Mental Health Assessment Tool electronic questionnaire was used to analyze psychological aspects of cases. The caregivers of the patients participated in the knowledge, attitude, and practice (KAP) survey. Results: A total of 380 patients (258 men, 122 women) were identified with active epilepsy. The estimated prevalence of active epilepsy was 1.1/1,000 population and 71% of cases belonged to low socioeconomic classes. Primary treatment gap was documented in 18.8% of cases in our study, 38% of cases were non-compliant to treatment with poorer compliance in those on pol-therapy, 76% had some psychiatric disorder, anxiety and depression being the commonest, and positive family history of epilepsy was found in 4.7%. KAP survey revealed that only 15% of the respondents believed that epilepsy is non-curable, 74% denied its infectious nature, 26% believed that epilepsy occurs due to past sins, and 81% said that they would not marry persons with epilepsy. Conclusion: A relatively low prevalence (1.1/1,000) of active epilepsy and a smaller primary treatment gap (18.8%) was found in our study population. Almost three-fourth of cases had an associated psychological problem, Though caregivers were aware of the nature of disease, majority would not prefer to marry a person suffering from epilepsy.

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“…Indian studies have reported generalized seizures as the common seizure type [32, 33], our study too revealed similar finding (75%).…”

Section: Discussionsupporting

confidence: 80%

Prevalence, Demographic Profile, and Psychological Aspects of Epilepsy in North-Western India: A Community-Based Observational Study

et al. 2018

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“…Given that it is a medical emergency, determining the etiology is quite important in the management and prevention of seizures. As seizure etiologies are different in developed and developing countries, the common cause of ASS in developing countries is neuroinfections like neurocysticercosis, tuberculosis, and malaria, which are uncommon in developed countries [ 2 ]. It also varies with geographic location and is influenced by some endemic diseases which are prevalent in that particular region.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Acute Symptomatic Seizures and Etiological Factors in a Tertiary Care Hospital From a Developing Country

Vemulapalli¹,

Betdur²,

Harikrishna³

et al. 2022

Cureus

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Introduction: The etiologies of acute symptomatic seizures (ASS) differ across the globe. We aimed to evaluate the etiological spectrum of acute seizures and to observe the pattern of seizure types among study participants.Methodology: We conducted this prospective study from 2016 to 18. We included all patients aged 20 years or older, presenting with ASS. We excluded those with pseudoseizures. We performed appropriate descriptive analyses to describe the demographic details, etiology of ASS, and pattern of ASS.Results: One hundred and thirty-eight patients were enrolled, constituting about 0.8% of total hospital admissions. The mean age at presentation was 44.33 ± 17.73 years. The most common etiologies for ASS were cerebrovascular accidents (CVA -32.6%), neuroinfections (26.8%), metabolic derangements (13%), alcohol withdrawal (10.9%), and intracranial tumors (4.3%). 71% of the patients presented with only a single episode of ASS. The predominant type of seizure was generalized tonic-clonic seizures, seen in 70.2% of all patients, followed by focal with the bilateral tonic-clonic type (15.9%) and focal seizures (10.1%). New-onset seizures presenting as status epilepticus were observed in 3.6%.Discussion: CVA and neuroinfections were the most common causes of ASS in our study, highlighting the need for community awareness of these conditions and the need to seek rapid care. The majority of our patients had only a single episode of seizures, with generalized seizures being the most common type, followed by focal onset seizures.

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“…The EEG is a powerful and important tool for the diagnosis and classification of seizure and epilepsy [ 2 , 3 ]. Interictal epileptic EEG is essential for the diagnosis of epilepsy, as epileptic EEG features may be obscured by artifacts [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Automatic Recognition of High-Density Epileptic EEG Using Support Vector Machine and Gradient-Boosting Decision Tree

Liu

et al. 2022

Brain Sciences

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Background: Epilepsy (Ep) is a chronic neural disease. The diagnosis of epilepsy depends on detailed seizure history and scalp electroencephalogram (EEG) examinations. The automatic recognition of epileptic EEG is an artificial intelligence application developed from machine learning (ML). Purpose: This study compares the classification effects of two kinds of classifiers by controlling the EEG data source and characteristic values. Method: All EEG data were collected by GSN HydroCel 256 leads and high-density EEG from Xiangya Third Hospital. This study used time-domain features (mean, kurtosis and skewness processed by empirical mode decomposition (EMD) and three IMFs), a frequency-domain feature (power spectrum density, PSD) and a non-linear feature (Shannon entropy). Support vector machine (SVM) and gradient-boosting decision tree (GBDT) classifiers were used to recognize epileptic EEG. Result: The result of the SVM classifier showed an accuracy of 72.00%, precision of 73.98%, and an F1_score of 82.28%. Meanwhile, the result of the GBDT classifier showed a sensitivity of 98.57%, precision of 89.13%, F1_score of 93.40%, and an AUC of 0.9119. Conclusion: The comparison of GBDT and SVM by controlling the variables of the feature values and parameters of a classifier is presented. GBDT obtained the better classification accuracy (90.00%) and F1_score (93.40%).

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The adolescent or adult with generalized tonic-clonic seizures

Cited by 11 publications

References 55 publications

Prevalence, Demographic Profile, and Psychological Aspects of Epilepsy in North-Western India: A Community-Based Observational Study

Prevalence, Demographic Profile, and Psychological Aspects of Epilepsy in North-Western India: A Community-Based Observational Study

Evaluation of Acute Symptomatic Seizures and Etiological Factors in a Tertiary Care Hospital From a Developing Country

Automatic Recognition of High-Density Epileptic EEG Using Support Vector Machine and Gradient-Boosting Decision Tree

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