2.3 Data collection
Age, BMI, underlying comorbidities and other basic information were collected retrospectively from the two groups. The medical records were used to collect information about the patients’ new coronavirus infection, such as the time of onset of symptoms, time of diagnosis, time of conversion and common symptoms such as fever, cough, nasal congestion and runny nose, muscle aches and pains.
2.4 Diagnostic criteria
The diagnostic criteria were based on the Chinese Novel Coronavirus Infection Treatment Protocol (Trial Version 10). Positive nucleic acid or antigen was diagnosed as Coronavirus infection. Patients were divided into four categories according to their severity as follows: Mild COVID-19, Medium COVID-19,Heavy COVID-19,Critical COVID-19
2.5 Statistical analysis
Normally distributed measures were expressed as mean ± standard deviation and t-tests were used for comparisons between groups; non-normally distributed measures were expressed as median (interquartile range) and non-parametric tests were used for comparisons between groups. Frequency (expressed as proportion) was used for count data and the chi-squared test was used for comparisons between groups. Multifactor logistic regression analysis was used to compare differences in the occurrence of symptoms after novel coronavirus infection between the two groups. In addition, Kaplan-Meier curves for the occurrence of adverse outcomes in the two populations were plotted to compare the occurrence of adverse outcomes between the two groups. All statistical analyses were performed with SPSS (22.0) software.