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.