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A COVID-19 mortality prediction model for Korean patients using nationwide Korean disease control and prevention agency database

Title
A COVID-19 mortality prediction model for Korean patients using nationwide Korean disease control and prevention agency database
Authors
Jee Y.Kim Y.-J.Oh J.Ha E.-H.Jo I.
Ewha Authors
하은희김영주조인호김이준
SCOPUS Author ID
하은희scopus; 김영주scopus; 조인호scopusscopus; 김이준scopusscopus
Issue Date
2022
Journal Title
Scientific Reports
ISSN
2045-2322JCR Link
Citation
Scientific Reports vol. 12, no. 1
Publisher
Nature Research
Indexed
SCIE; SCOPUS WOS scopus
Document Type
Article
Abstract
The experience of the early nationwide COVID-19 pandemic in South Korea led to an early shortage of medical resources. For efficient resource allocation, accurate prediction of the prognosis or mortality of confirmed patients is essential. Therefore, the aim of this study was to develop an accurate model for predicting COVID-19 mortality using epidemiolocal and clinical variables and for identifying a high-risk group of confirmed patients. Clinical and epidemiolocal variables of 4049 patients with confirmed COVID-19 between January 20, 2020 and April 30, 2020 collected by the Korean Disease Control and Prevention Agency were used. Among the 4049 total confirmed patients, 223 patients died, while 3826 patients were released from isolation. Patients who had the following risk factors showed significantly higher risk scores: age over 60 years, male sex, difficulty breathing, diabetes, cancer, dementia, change of consciousness, and hospitalization in the intensive care unit. High accuracy was shown for both the development set (n = 2467) and the validation set (n = 1582), with AUCs of 0.96 and 0.97, respectively. The prediction model developed in this study based on clinical features and epidemiological factors could be used for screening high-risk groups of patients and for evidence-based allocation of medical resources. © 2022, The Author(s).
DOI
10.1038/s41598-022-07051-4
Appears in Collections:
의과대학 > 의학과 > Journal papers
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