Statistical analyses

Normal distribution and variance homogeneity tests were performed on all continuous variables; those with a normal distribution are expressed as the mean and standard deviation while those with non-normal distributions are expressed as medians and ranges. In this study, we divided the patients into two groups (COVID-19 pneumonia and the other viral pneumonia). First, we examined group differences in all variables between patients with COVID-19 pneumonia and patients with other types of viral pneumonia. The Kruskal-Wallis H test (skewed distribution) and chi-square tests (categorical variables) were used to determine statistical differences between the two groups. Second, a univariate regression analysis was applied to estimate effect sizes for the relationships between all variables and two types of viral pneumonia. Last, multivariable logistic models were used to evaluate the associations between exposure (imaging characteristics) and outcome (viral pneumonia). These models included model 1 (not adjusted for other co-variants), model 2 (adjusted for age, sex, and body mass index [BMI]), and model 3 (adjusted for the same factors as model 2 as well as for other significantly associated clinical and imaging characteristics in univariate regression analysis). The group with other types of viral pneumonia was considered the reference group.

A two-tailed p value of less than 0.05 was considered statistically significant. All analyses were performed using R software (version 3.3.3; The R Foundation for Statistical Computing) and EmpowerStats (X&Y Solutions, Inc).