Survival Analysis and Risk Factors in COVID-19 Patients

Abstract

Abstract Objective: The aim of this study is to evaluate the clinical characteristics and outcomes in 2019 coronavirus disease (COVID-19) patients and to help clinicians perform correct treatment and evaluate prognosis and guide the treatment. Methods: Patients totaling 239 were diagnosed with COVID-19 and were included in this study. Patients were divided into the improvement group and the death group according to their outcome (improvement or death). Clinical characteristics and laboratory parameters were collected from medical records. Continuous variables were tested by an independent sample T test, and categorical variables were analyzed by the chi-square test or Fisher’s exact test. The Cox proportional hazard regression model was used for survival analysis in death patients. The time-dependent area under curves (AUC) based on white blood cell count, lymphocyte count, neutrophil count by age, blood urea nitrogen, and C-reactive protein were plotted. Results: Efficacy evaluation indicated that 99 (41.4%) patients had deteriorated, and 140 (58.6%) patients had improved. Oxygen saturation, hemoglobin levels, infection-related indicators, lymphocyte and platelet counts, C-reactive protein, serum albumin, liver and kidney function, and lactate dehydrogenase in improvement group were statistically significant between the improvement and death groups. A survival analysis revealed that comorbidities, lymphocyte counts, platelet count, serum albumin, C-reactive protein level, and renal dysfunction may be risk factors in patients with COVID-19. Conclusion: Patients with comorbidities, lower lymphocyte counts in hemogram, platelet count and serum albumin, high C-reactive protein level, and renal dysfunction may have higher risk for death. More attention should be given to risk management in the progression of COVID-19.