Journal Article

Prognosis Score System to Predict Survival for COVID-19 Cases: a Korean Nationwide Cohort Study

Kim, Dong-Wook, Park, Sung-Soo, Lee, Dong-Gun, Bae, Young Yi, Cho, Sung-Yeon, Song, Min-Kyu

2021

Overview

As the COVID-19 pandemic continues, an initial risk-adapted allocation is crucial for managing medical resources and providing intensive care. 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. 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. 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 . 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). 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.

• Publisher: Gunther Eysenbach MD MPH, Associate Professor,JMIR Publications
• Subject: Age Factors / Aged / Allocation / Bootstrap method / Bootstrapping / Cohort analysis / Coronaviruses / COVID-19 / COVID-19 - diagnosis / COVID-19 - mortality / Critical Care - statistics & numerical data / Dementia / Dementia - epidemiology / Demographics / Diabetes / Disease / Dyspnea / Extracorporeal membrane oxygenation / Fatalities / Female / Heart failure / High risk / Hospitals / Humans / Hypertension / Infectious diseases / Intensive care / Kidney diseases / Kidney Failure, Chronic - epidemiology / Laboratories / Length of stay / Length of Stay - statistics & numerical data / Male / Medical decision making / Medical diagnosis / Medical prognosis / Medical research / Middle Aged / Mortality / Multiple organ dysfunction syndrome / Original Paper / Pandemics / Patients / Prognosis / Proportional Hazards Models / Republic of Korea - epidemiology / Resource allocation / Retrospective Studies / Risk / Risk Factors / ROC Curve / Scores / Severe acute respiratory syndrome coronavirus 2 / Severity of Illness Index / Survival Rate / Validity / Variables / Ventilators / Viral infections