Sas enterprise guide software version 6

In the general characteristics of the analysis data, the subjects of hypertension and non-hypertension were classified, and the mean and median values for the continuous variable and the frequency and ratio for the categorical variable were indicated. In hypertensive patients, a chi-square test was performed for each independent variable, frequency and ratio, which are expected to affect COVID-19 infection risk. In addition, multivariate logistic regression was performed to confirm the influence of the independent variable considering the interaction of each variable. The severity of COVID-19 patients was divided into five stages, and the independent variables, frequencies and ratios expected to affect clinical severity were analyzed by performing a chi-square test. Multivariate analysis was performed using logistic regression to evaluate the association between selected clinical characteristics and a likelihood of a positive test for COVID-19/COVID-19 severity. SAS Enterprise Guide Software version 6.1 (SAS Institute Inc., Cary, NC) was used for these analyses, and a P value of less than .05 was considered statistically significant.

Data are presented as mean ± standard deviation (SD) for continuous variables or as numbers and percentages for categorical variables. Univariate Cox's proportional-hazards regression model was used to assess hazard ratios (HR) and 95% confidence intervals (CI) of TB occurrence between each treatment and control group. To achieve a balance of patient's age, sex, and disease duration between groups in IBD patients, a one-to-one greedy matching (one case per one control) with the nearest-neighbor algorithm was performed. The same matching procedure was conducted within CD and UC patients. The incidence of TB and its 95% CI for each treatment group was calculated per 10,000 person-years. The median days on medication before TB was defined as the median value of the medication period from the initial to the onset of TB in each treatment group. A stratified Cox proportional-hazards regression analysis for the matched-pair data were used to evaluate the relative hazard of events in the treatment group compared to the control group. Cumulative incidence for the study outcome was estimated using the Kaplan-Meier method. A two-sided P-value < 0.05 was considered to be statistically significant. All statistical analyses were performed using the SAS Enterprise Guide software version 6.1 (SAS Institute Inc., Cary, NC, USA).