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Prognosis Score System to Predict Survival for COVID-19 Cases: a Korean Nationwide Cohort Study.
- Source :
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Journal of medical Internet research [J Med Internet Res] 2021 Feb 22; Vol. 23 (2), pp. e26257. Date of Electronic Publication: 2021 Feb 22. - Publication Year :
- 2021
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Abstract
- Background: As the COVID-19 pandemic continues, an initial risk-adapted allocation is crucial for managing medical resources and providing intensive care.<br />Objective: In this study, we aimed to identify factors that predict the overall survival rate for COVID-19 cases and develop a COVID-19 prognosis score (COPS) system based on these factors. In addition, disease severity and the length of hospital stay for patients with COVID-19 were analyzed.<br />Methods: We retrospectively analyzed a nationwide cohort of laboratory-confirmed COVID-19 cases between January and April 2020 in Korea. The cohort was split randomly into a development cohort and a validation cohort with a 2:1 ratio. In the development cohort (n=3729), we tried to identify factors associated with overall survival and develop a scoring system to predict the overall survival rate by using parameters identified by the Cox proportional hazard regression model with bootstrapping methods. In the validation cohort (n=1865), we evaluated the prediction accuracy using the area under the receiver operating characteristic curve. The score of each variable in the COPS system was rounded off following the log-scaled conversion of the adjusted hazard ratio.<br />Results: Among the 5594 patients included in this analysis, 234 (4.2%) died after receiving a COVID-19 diagnosis. In the development cohort, six parameters were significantly related to poor overall survival: older age, dementia, chronic renal failure, dyspnea, mental disturbance, and absolute lymphocyte count <1000/mm <superscript>3</superscript> . The following risk groups were formed: low-risk (score 0-2), intermediate-risk (score 3), high-risk (score 4), and very high-risk (score 5-7) groups. The COPS system yielded an area under the curve value of 0.918 for predicting the 14-day survival rate and 0.896 for predicting the 28-day survival rate in the validation cohort. Using the COPS system, 28-day survival rates were discriminatively estimated at 99.8%, 95.4%, 82.3%, and 55.1% in the low-risk, intermediate-risk, high-risk, and very high-risk groups, respectively, of the total cohort (P<.001). The length of hospital stay and disease severity were directly associated with overall survival (P<.001), and the hospital stay duration was significantly longer among survivors (mean 26.1, SD 10.7 days) than among nonsurvivors (mean 15.6, SD 13.3 days).<br />Conclusions: The newly developed predictive COPS system may assist in making risk-adapted decisions for the allocation of medical resources, including intensive care, during the COVID-19 pandemic.<br /> (©Sung-Yeon Cho, Sung-Soo Park, Min-Kyu Song, Young Yi Bae, Dong-Gun Lee, Dong-Wook Kim. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 22.02.2021.)
- Subjects :
- Age Factors
Aged
Critical Care statistics & numerical data
Dementia epidemiology
Female
Humans
Kidney Failure, Chronic epidemiology
Length of Stay statistics & numerical data
Male
Middle Aged
Pandemics
Prognosis
Proportional Hazards Models
ROC Curve
Republic of Korea epidemiology
Retrospective Studies
Risk Factors
Severity of Illness Index
Survival Rate
COVID-19 diagnosis
COVID-19 mortality
Subjects
Details
- Language :
- English
- ISSN :
- 1438-8871
- Volume :
- 23
- Issue :
- 2
- Database :
- MEDLINE
- Journal :
- Journal of medical Internet research
- Publication Type :
- Academic Journal
- Accession number :
- 33539312
- Full Text :
- https://doi.org/10.2196/26257