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).