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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10298879/ https://www.ncbi.nlm.nih.gov/pubmed/37373723 http://dx.doi.org/10.3390/jcm12124031 |
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author | Jin, Sun Jin Lee, Taesic Moon, Hyun Eui Park, Eun Seok Lee, Sue Hyun Roh, Young Il Seo, Dong Min Kim, Won-Joo Hwang, Heewon |
author_facet | Jin, Sun Jin Lee, Taesic Moon, Hyun Eui Park, Eun Seok Lee, Sue Hyun Roh, Young Il Seo, Dong Min Kim, Won-Joo Hwang, Heewon |
author_sort | Jin, Sun Jin |
collection | PubMed |
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. |
format | Online Article Text |
id | pubmed-10298879 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102988792023-06-28 Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices Jin, Sun Jin Lee, Taesic Moon, Hyun Eui Park, Eun Seok Lee, Sue Hyun Roh, Young Il Seo, Dong Min Kim, Won-Joo Hwang, Heewon J Clin Med Article 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. MDPI 2023-06-13 /pmc/articles/PMC10298879/ /pubmed/37373723 http://dx.doi.org/10.3390/jcm12124031 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jin, Sun Jin Lee, Taesic Moon, Hyun Eui Park, Eun Seok Lee, Sue Hyun Roh, Young Il Seo, Dong Min Kim, Won-Joo Hwang, Heewon Classification Model for Epileptic Seizure Using Simple Postictal Laboratory Indices |
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 | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10298879/ https://www.ncbi.nlm.nih.gov/pubmed/37373723 http://dx.doi.org/10.3390/jcm12124031 |
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