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?:abstract
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South Korea was one of the epicenters for both the 2015 MERS and 2019 COVID-19 outbreaks. However, there has been a lack of published literature, especially using the EMR records, that provides a comparative summary of the prognostic factors present in the coronavirus-derived diseases patients. Therefore, in this study, we aimed to compare and evaluate the distinct clinical traits between the patients of different coronaviruses, including the lesser pathogenic HCoV strains, SARS-CoV, MERS-CoV, and SARS-CoV-2. We also conducted observed the risk factors by the COVID severity to investigate the extent of resemblance in clinical features between the disease groups and to identify unique factor that may influence the prognosis of the COVID-19 patients. Here, we utilize the common data model (CDM), which is the database that houses the EMR records transformed into the common format to be used by the multiple institutions. For the comparative analyses between the disease groups, we used independent t-test, Scheffe post-hoc test, and Games-howell post-hoc test and for the continuous variables, chi-square test and Fisher exact test. Based on the analyses, we selected the variables with p-values less than 0.05 to predict COVID-19 severity by nominal logistic regression with adjustments to age and gender. From the study, we observed diabetes, cardio and cerebrovascular diseases, cancer, pulmonary disease, gastrointestinal disease, and renal disease in all patient groups. Of all, the proportions of cancer patients were highest in all groups with no statistical significance. Most interestingly, we observed a high degree of clinical similarity between the COVID-19 and SARS patients with more than 50% of measured clinical variables to show statistical similarities between two groups. Our research reflects the great significance within the bioinformatics field that we were able to effectively utilize the integrated CDM to reflect real-world challenges in the context of coronavirus. We expect the results from our study to provide clinical insights that can serve as predicator of risk factors from the future coronavirus outbreak as well as the prospective guidelines for the clinical treatments.
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