Version 1
: Received: 27 August 2024 / Approved: 27 August 2024 / Online: 27 August 2024 (18:35:19 CEST)
How to cite:
Park, K.-I.; Hwang, S.; Son, H.; Moon, J.; Lee, S.-T.; Jung, K.-H.; Jung, K.-Y.; Chu, K.; Lee, S. K. Prognostication in Epilepsy with Integrated Analysis of Blood Parameters and Clinical Data. Preprints2024, 2024081948. https://doi.org/10.20944/preprints202408.1948.v1
Park, K.-I.; Hwang, S.; Son, H.; Moon, J.; Lee, S.-T.; Jung, K.-H.; Jung, K.-Y.; Chu, K.; Lee, S. K. Prognostication in Epilepsy with Integrated Analysis of Blood Parameters and Clinical Data. Preprints 2024, 2024081948. https://doi.org/10.20944/preprints202408.1948.v1
Park, K.-I.; Hwang, S.; Son, H.; Moon, J.; Lee, S.-T.; Jung, K.-H.; Jung, K.-Y.; Chu, K.; Lee, S. K. Prognostication in Epilepsy with Integrated Analysis of Blood Parameters and Clinical Data. Preprints2024, 2024081948. https://doi.org/10.20944/preprints202408.1948.v1
APA Style
Park, K. I., Hwang, S., Son, H., Moon, J., Lee, S. T., Jung, K. H., Jung, K. Y., Chu, K., & Lee, S. K. (2024). Prognostication in Epilepsy with Integrated Analysis of Blood Parameters and Clinical Data. Preprints. https://doi.org/10.20944/preprints202408.1948.v1
Chicago/Turabian Style
Park, K., Kon Chu and Sang Kun Lee. 2024 "Prognostication in Epilepsy with Integrated Analysis of Blood Parameters and Clinical Data" Preprints. https://doi.org/10.20944/preprints202408.1948.v1
Abstract
Background/Objectives: Determining the outcome of epilepsy is crucial for making proactive and timely treatment decisions, as well as for counseling patients. Recent research efforts have focused on using various imaging techniques and EEG for prognostication; however, there is insufficient evidence regarding the role of blood parameters. Our study aimed to investigate the additional prognostic value of routine blood parameters in predicting epilepsy outcomes. Methods: We analyzed data from 1,782 patients who underwent routine blood tests within 90 days of their first visit and had a minimum follow-up duration of three years. The etiological types were structural (35.1%), genetic (14.2%), immune (4.7%), infectious (2.9%), and unknown (42.6%). The outcome was defined as the presence of seizures in the last year. Results: Initially, a multivariate analysis was conducted based on clinical variables, MRI, and EEG data. This analysis revealed that sex, age of onset, epileptiform discharge, structural etiology, and the number of antiseizure medications were related to the outcome, with an area under curve (AUC) of 0.708. Among the blood parameters, fibrinogen, bilirubin, uric acid, and aPTT were significant, with AUCs of 0.602, 0.597, 0.455, and 0.549, respectively. Including these blood parameters in the analysis slightly improved the AUC to 0.713. Conclusions: Some blood parameters were found to be related to the final outcome, potentially paving the way to understanding the mechanisms of epileptogenesis and drug resistance.
Keywords
epilepsy; outcome; prediction; blood
Subject
Biology and Life Sciences, Neuroscience and Neurology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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