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Multidimensional Early Prediction Score for Drug-Resistant Epilepsy

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Author(s)
Kyung Wook KangYong Won ChoSang Kun LeeKi-Young JungJi Hyun KimDong Wook KimSang-Ahm LeeSeung Bong HongIn-Seop NaSo-Hyun LeeWon-Ki Ba다Seok-Yong ChoiMyeong-Kyu Kim
Keimyung Author(s)
Baek, Won Ki
Department
Dept. of Microbiology (미생물학)
Journal Title
J Clin Neurol
Issued Date
2022
Volume
18
Issue
5
Keyword
epilepsydrug resistant epilepsygenome-wide association studygenetic predictor
Abstract
Background and Purpose:
Achieving favorable postoperative outcomes in patients with drug-resistant epilepsy (DRE) requires early referrals for preoperative examinations. The purpose of this study was to investigate the possibility of a user-friendly early DRE prediction model that is easy for nonexperts to utilize.

Methods:
A two-step genotype analysis was performed, by applying 1) whole-exome sequencing (WES) to the initial test set (n=243) and 2) target sequencing to the validation set (n=311). Based on a multicenter case–control study design using the WES data set, 11 genetic and 2 clinical predictors were selected to develop the DRE risk prediction model. The early prediction scores for DRE (EPS-DRE) was calculated for each group of the selected genetic predictors (EPS-DREgen), clinical predictors (EPS-DREcln), and two types of predictor mix (EPS-DREmix) in both the initial test set and the validation set.

Results:
The multidimensional EPS-DREmix of the predictor mix group provided a better match to the outcome data than did the unidimensional EPS-DREgen or EPS-DREcln. Unlike previous studies, the EPS-DREmix model was developed using only 11 genetic and 2 clinical predictors, but it exhibited good discrimination ability in distinguishing DRE from drug-responsive epilepsy. These results were verified using an unrelated validation set.

Conclusions:
Our results suggest that EPS-DREmix has good performance in early DRE prediction and is a user-friendly tool that is easy to apply in real clinical trials, especially by nonexperts who do not have detailed knowledge or equipment for assessing DRE. Further studies are needed to improve the performance of the EPS-DREmix model.
Keimyung Author(s)(Kor)
백원기
Publisher
School of Medicine (의과대학)
Type
Article
ISSN
2005-5013
Source
https://thejcn.com/DOIx.php?id=10.3988/jcn.2022.18.5.553
DOI
10.3988/jcn.2022.18.5.553
URI
https://kumel.medlib.dsmc.or.kr/handle/2015.oak/44463
Appears in Collections:
1. School of Medicine (의과대학) > Dept. of Microbiology (미생물학)
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