Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices
Distinguishing syncope from epileptic seizures in patients with sudden loss of consciousness is important. Various blood tests have been used to indicate epileptic seizures in patients with impaired consciousness. This retrospective study aimed to predict the diagnosis of epilepsy in patients with t...
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MDPI AG
2023-06-01
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| Series: | Journal of Clinical Medicine |
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| Online Access: | https://www.mdpi.com/2077-0383/12/12/4031 |
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| author | Sun Jin Jin Taesic Lee Hyun Eui Moon Eun Seok Park Sue Hyun Lee Young Il Roh Dong Min Seo Won-Joo Kim Heewon Hwang |
| author_facet | Sun Jin Jin Taesic Lee Hyun Eui Moon Eun Seok Park Sue Hyun Lee Young Il Roh Dong Min Seo Won-Joo Kim Heewon Hwang |
| author_sort | Sun Jin Jin |
| collection | DOAJ |
| description | Distinguishing syncope from epileptic seizures in patients with sudden loss of consciousness is important. Various blood tests have been used to indicate epileptic seizures in patients with impaired consciousness. This retrospective study aimed to predict the diagnosis of epilepsy in patients with transient loss of consciousness using the initial blood test results. A seizure classification model was constructed using logistic regression, and predictors were selected from a cohort of 260 patients using domain knowledge and statistical methods. The study defined the diagnosis of seizures and syncope based on the consistency of the diagnosis made by an emergency medicine specialist at the first visit to the emergency room and the diagnosis made by an epileptologist or cardiologist at the first outpatient visit using the International Classification of Diseases 10th revision (ICD-10) code. Univariate analysis showed higher levels of white blood cells, red blood cells, hemoglobin, hematocrit, delta neutrophil index, creatinine kinase, and ammonia levels in the seizure group. The ammonia level had the highest correlation with the diagnosis of epileptic seizures in the prediction model. Therefore, it is recommended to be included in the first examination at the emergency room. |
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| institution | Directory Open Access Journal |
| issn | 2077-0383 |
| language | English |
| last_indexed | 2024-03-11T02:18:14Z |
| publishDate | 2023-06-01 |
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| series | Journal of Clinical Medicine |
| spelling | doaj.art-48490e93f1214cf9a18b9716dfc9f5a82023-11-18T11:00:00ZengMDPI AGJournal of Clinical Medicine2077-03832023-06-011212403110.3390/jcm12124031Classification Model for Epileptic Seizure Using Simple Postictal Laboratory IndicesSun Jin Jin0Taesic Lee1Hyun Eui Moon2Eun Seok Park3Sue Hyun Lee4Young Il Roh5Dong Min Seo6Won-Joo Kim7Heewon Hwang8Department of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDivision of Data Mining and Computational Biology, Institute of Global Health Care and Development, Wonju 26426, Republic of KoreaDepartment of Family Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Medical Information, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDepartment of Neurology, Gangnam Severance Christian Hospital, Yonsei University College of Medicine, Seoul 06273, Republic of KoreaDepartment of Neurology, Wonju Severance Christian Hospital, Yonsei University Wonju College of Medicine, Wonju 26426, Republic of KoreaDistinguishing syncope from epileptic seizures in patients with sudden loss of consciousness is important. Various blood tests have been used to indicate epileptic seizures in patients with impaired consciousness. This retrospective study aimed to predict the diagnosis of epilepsy in patients with transient loss of consciousness using the initial blood test results. A seizure classification model was constructed using logistic regression, and predictors were selected from a cohort of 260 patients using domain knowledge and statistical methods. The study defined the diagnosis of seizures and syncope based on the consistency of the diagnosis made by an emergency medicine specialist at the first visit to the emergency room and the diagnosis made by an epileptologist or cardiologist at the first outpatient visit using the International Classification of Diseases 10th revision (ICD-10) code. Univariate analysis showed higher levels of white blood cells, red blood cells, hemoglobin, hematocrit, delta neutrophil index, creatinine kinase, and ammonia levels in the seizure group. The ammonia level had the highest correlation with the diagnosis of epileptic seizures in the prediction model. Therefore, it is recommended to be included in the first examination at the emergency room.https://www.mdpi.com/2077-0383/12/12/4031seizuresyncopeserumammoniabayes approach |
| spellingShingle | Sun Jin Jin Taesic Lee Hyun Eui Moon Eun Seok Park Sue Hyun Lee Young Il Roh Dong Min Seo Won-Joo Kim Heewon Hwang Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices Journal of Clinical Medicine seizure syncope serum ammonia bayes approach |
| title | Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices |
| title_full | Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices |
| title_fullStr | Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices |
| title_full_unstemmed | Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices |
| title_short | Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices |
| title_sort | classification model for epileptic seizure using simple postictal laboratory indices |
| topic | seizure syncope serum ammonia bayes approach |
| url | https://www.mdpi.com/2077-0383/12/12/4031 |
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