Risk Factors of Epilepsy Seizure


Santi Wulan Purnami1), Lianna Dwi Rahmawati 2), Wardah Rahmatul Islamiyah3), Diah Puspito Wulandari4), Anda Iviana Juniani5)

 

1,2)Department of Statistics, Faculty of Mathematics, Computing, and Data Sciences Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

3)Department of Neurology, Faculty of Medicine, University of Airlangga, Surabaya, Indonesia

4)Department of Computer Engineering, Faculty of Electrical Technology Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia

5)Department of Marine Engineering, Shipbuilding Institute of Polytechnic Surabaya, Indonesia

 

ABSTRACT 

Background: Seizure of epilepsy can be defined as a sudden and fleeting modification of brain function that comes from a group of brain cells. Various things can trigger seizures, such as lack of sleep, stress, alcohol consumption, and stimulation such as television light or disco light. This study aimed to determine the risk of epilepsy seizure.

Subjects and Method: This was a cross sectional study conducted in East Java in March 2019. A total of 51 patients with epilepsy were selected for this study. The dependent variable was seizures. The independent variables were age of the epilepsy patient, age diagnosed with epilepsy, history of fever with seizures, and seizure trigger factors. The data were obtained from survey of people with epilepsy (ODE) community in March 2019. The data was analyzed by a binary logistic regression and naïve Bayes method.

Results: The risk of seizure of epilepsy increased with age (OR=0.89; 90% CI=-0.19 to -0.02; p=0.041), age at diagnosis, (OR=1.12; 90% CI=0.01 to 0.21; p=0.056), history of fever with seizure (OR=6.88; 90% CI=0.303 to 3.55; p=0.051), and seizure trigger factor (OR=12.52; 90% CI=0.94 to 4.11; p=0.091). The prediction results of seizure events using the binary logistic regression had higher predictive accuracy (75%) than naïve Bayes method (66.67%).

Concluson: The risk of seizure of epilepsy increases with age, age at diagnosis, history of fever with seizures, and seizure trigger factor. The prediction results of seizure events using the binary logistic regression have higher predictive accuracy than naïve bayes method.

Keywords: risk factor, seizures, epilepsy, naïve Bayes

Correspondence: Santi Wulan Purnami. Department of Statistics, Faculty of Mathematics, Computing, and Data Sciences, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia. Email: santiwulan08@gmail.com. Mobile: 0812324158275.

DOI: https://doi.org/10.26911/the6thicph.05.27

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