BACKGROUND: As the coronavirus disease 2019 (COVID-19) pandemic continues, initial risk-adapted allocation is crucial for managing medical resources and providing intensive care .
OBJECTIVE: This study aimed to identify factors that predict COVID-19 overall survival rate and develop a COVID-19 prognosis score (COPS) based on these factors . Also, severity of patients' illness and length of hospital stay were analyzed .
METHODS: This study retrospectively analyzed nationwide cohort of laboratory-confirmed COVID-19 cases between January and April 2020 in Korea . The cohort was split randomly into the development cohort and the validation cohorts with 2:1 ratio . In the development cohort (n=3,729), we tried to identify factors associated with overall survival (OS) and create a scoring system to predict OS using identified parameters by Cox proportional hazard regression model with bootstrapping methods . The prediction accuracy was evaluated in the validation cohort (n=1,865) using the area under the curve (AUC) by receiver operating characteristics curves . Each variable's score in the COPS system was rounded off following the log-scaled conversion of the adjusted hazard ratio .
RESULTS: Among the 5,594 patients included in this analysis , 234 died after COVID-19 diagnosis . In the development cohort, six parameters were significantly related to poor overall survival: advanced age; dementia; chronic renal failure; dyspnea; mental disturbance; and absolute lymphocyte count <1,000 /mm3 . Afterward, the COPS system was developed, and risk groups were created: low-risk (score , 0-2), intermediate-risk (score , 3), high-risk (score , 4), and very high-risk (score , 5-7). The COPS system yielded an AUC of .918 for predicting 14-days survival rate and .896 for predicting 28-days survival rate in the validation cohort . Using the COPS system, 28-days overall survival rates were discriminatively estimated as 99.8% , 95.4% , 82.3%, and 55.1% in low-risk, intermediate-risk, high risk, and very high-risk groups in the total cohort, respectively (P <.001). Length of hospital stay and disease severity were directly associated with the survivors (P <.001), and survivors stayed in a hospital significantly longer than non-survivors (26.1±10.7 vs. 15.6±13.3 days).
CONCLUSIONS: The newly developed predictive COPS system may assist in risk-adapted decisions for medical resources allocation, including intensive care, during the COVID-19 pandemic.