Abstract
BackgroundAs the COVID-19 pandemic continues, an initial risk-adapted allocation is crucial for managing medical resources and providing intensive care.ObjectiveIn 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.MethodsWe 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.ResultsAmong 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/mm3. 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).ConclusionsThe 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.
Highlights
Since the outbreak of unexplained pneumonia in Wuhan, China, in December 2019, which was subsequently identified as COVID-19 caused by the newly discovered pathogen SARS-CoV-2, the COVID-19 pandemic remains active in over 180 countries [1,2]
The predictive score was developed based on the development cohort, whereas the power of prediction was explored in the validation cohort
We identified that older age (50-69 or ≥70 years) and comorbidities, including dementia, chronic renal failure, presentation of dyspnea, mental disturbance at diagnosis, and absolute lymphocyte count area under the receiver operating characteristic (AUROC) (ALC)
Summary
Since the outbreak of unexplained pneumonia in Wuhan, China, in December 2019, which was subsequently identified as COVID-19 caused by the newly discovered pathogen SARS-CoV-2, the COVID-19 pandemic remains active in over 180 countries [1,2]. As of November 6, 2020, 1,231,017 of a total of 48,534,508 patients with COVID-19 have died, representing an overall infection fatality rate of 2.54% [3,4]. The majority of viral infections are self-limiting, COVID-19 cases that are severe (ie, dyspnea, hypoxia, or >50% of lung involvement observed on imaging within 24–48 h) or critical (ie, respiratory failure, shock, or multiple organ failure) are of global concern and require medical resources for intensive care. Most severe or critical cases occur in older patients or those with underlying comorbidities such as cancer, chronic obstructive pulmonary diseases, heart failure, or diabetes [11,12,13]. The clinical course of patients with COVID-19 depends on multiple factors, including the immune status of the host, viral load of SARS-CoV-2, genetic diversity of the virus, and underlying diseases. As the COVID-19 pandemic continues, an initial risk-adapted allocation is crucial for managing medical resources and providing intensive care
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