Statistical Analysis
Descriptive statistics were used to present patient’s demographics,
COVID-19 infection and respiratory sequalae. Then, the patients were
categorized into two groups: those with any respiratory sequalae and
those without. Continuous variables between the two groups were compared
using Student’s t-test and categorical variables were compared using
Chi-square or Fisher Exact test.
The association between the presence of any post COVID-19 symptoms and
the presence of pulmonary function impairments was examined using Fisher
Exact test. Logistic regression was used to determine risk factors
associated with the symptoms or the pulmonary function impairments. If
there are more than one variable with p -value < 0.20
from univariate regression analysis, the variables will be subjected to
multivariate regression analysis. Additionally, we evaluated pulmonary
function as continuous data through linear regression analysis to
evaluate its associated risk factors. Three measures of pulmonary
function were assessed including FEV1 z-score, FVC
z-score, and FEV1/FVC z-score.
P-value < 0.05 were considered statistical significance. The
analysis was performed by using STATA version 17.1 (College Station,
Texas 77845 USA).