The epidemic of coronavirus disease 2019 (COVID-19) is causing global health concerns. The aim of this study was to evaluate influence of clinical characteristics on outcomes during the Omicron outbreak. A total of 25182 hospitalized patients were enrolled, including 39 severe patients and 25143 non-severe patients. Propensity score matching (PSM) was applied to balance the baseline characteristics. Logistic regression analysis was used to assess the risk of severe disease, as well as the risk of prolonged viral shedding time (VST) and increased length of hospital stay (LOS). Before PSM, patients in the severe group were older, had higher symptom scores, and had a higher proportion of comorbidities (p<0.001). After PSM, there were no significant differences in age, gender, symptom score and comorbidities between severe (n=39) and non-severe (n=156) patients. Symptoms of fever (OR=6.358, 95%CI 1.748-23.119, p=0.005) and diarrhea (OR=6.523, 95%CI 1.061-40.110, p=0.043) were independent risk factors for development of severe disease. In non-severe patients, higher symptom score was associated with prolonged VST (OR=1.056, 95% CI 1.000-1.115, p=0.049) and LOS (OR=1.128, 95% CI 1.039-1.225, p=0.004); older age was associated with longer LOS (OR=1.045, 95% CI 1.007-1.084, p=0.020). The overall condition of the Shanghai Omicron epidemic was relatively mild. Potential risk factors for fever, diarrhea, and higher symptom score can help clinicians to predict clinical outcomes in COVID-19 patients.