Author(s)

Yani Kuang¹, Susu He¹, Shuangxiang Lin¹, Rui Zhu¹, Rongzhen Zhou¹, Jian Wang¹, Renzhan Li², Haiyong Lin³, Zhibang Zhang⁴, Peipei Pang⁵, Wenbin Ji^1*

¹Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Wenzhou, China.
²Sanmen People’s Hospital, Taizhou, China.
³Wenling First People’s Hospital, Wenling, China.
⁴Tiantai People’s Hospital, Taizhou, China.
⁵GE Healthcare, Hangzhou, China.

Background: The outbreak of COVID-19 has a significant impact on the health of people around the world. In the clinical condition of COVID-19, the condition of critical cases changes rapidly with a high mortality rate. Therefore, early prediction of disease severity and active intervention play an important role in the prognosis of severe patients. Methods: All the patients with COVID-19 in Taizhou city were retrospectively included and segregated into the non-severe and severe group according to the severity of the disease. The clinical manifestations, laboratory examination results, and imaging findings of the 2 groups were analyzed for comparing the differences between the 2 groups. Univariate and multivariate logistic regression were used for screening the factors that could predict the disease, and the nomogram was constructed. Results: A total of 143 laboratory-confirmed cases were included in the study, including 110 non-severe patients and 33 severe patients. The median age of patients was 47 years (range, 4 - 86 years). Fever (73.4%) and cough (63.6%) were the most common initial clinical symptoms. By using the method of multivariate logistic regression, the variables to construct nomogram include age (OR: 1.052, 95% CI: 1.020 - 1.086, P = 0.001), body temperature (OR: 2.252, 95% CI: 1.139 - 4.450, P = 0.020), lymphocyte count (OR: 1.128, 95% CI: 1.000 - 1.272, P = 0.049), ADA (OR: 1.163, 95% CI: 1.023 - 1.323, P = 0.021), PaO₂ (OR: 0.972, 95% CI: 0.953 - 0.992, P = 0.007), IL-10 (OR: 1.184, 95% CI: 1.037 - 1.351, P = 0.012), and bronchiectasis (OR: 3.818, 95% CI: 1.694 - 8.605, P = 0.001). The AUC of the established nomogram was 0.877. Conclusions: This study analyzed the cases of patients with COVID-19 in Taizhou city and constructed a model to predict the illness severity. When patients showed the features including older age, high body temperature, low lymphocyte count, low ADA value, low PaO₂, high IL-10, and bronchiectasis sign in CT predicts a greater likelihood of severe COVID-19.

COVID-19, SARS-CoV-2, Clinical Characteristics, Severity Prediction

Kuang, Y. , He, S. , Lin, S. , Zhu, R. , Zhou, R. , Wang, J. , Li, R. , Lin, H. , Zhang, Z. , Pang, P. and Ji, W. (2020) A Nomogram for Predicting the Severity of COVID-19 Using Laboratory Examination and CT Findings. International Journal of Clinical Medicine, 11, 786-809. doi: 10.4236/ijcm.2020.1112059.