Spss windows version

Data were entered using EpiData and exported to SPSS windows version 20.0 for analysis. Both descriptive and analytical analyses were done. The descriptive results have been presented by tables and graphs. Bivariate logistic regression analysis was used to identify associations between independent and study variables. The possible effects of confounders were controlled through multivariate logistic regression analysis. The association between the explanatory and dependent variables were assessed at p value of 0.05.

The categorical data are reported as the number or percentage of observations while continuous variables are presented as mean ± standard deviations of the values. The differences between categorical variables were assessed by a chi-square test. Differences between groups of continuous variables that were non-parametrically distributed were assessed using Kruskal–Wallis tests. Univariate analysis of variables was performed by using univariate cox regression analysis. All variables selected on univariate analysis (p < 0.05) were included in the multivariate analysis. Multivariate prognostic analyses were performed by using the Cox proportional hazards regression model. A Kaplan–Meier survival analysis with a log-rank test was performed to compare the OS of patients in different the groups. P values < 0.05 are considered statistically significant. All statistical procedures were performed using SPSS Windows (version 21; SPSS Inc., Chicago, IL, USA).

Normally distributed data are expressed as mean ± standard deviation and non-normally distributed data median or as numbers and percentages. Non-normally distributed data were logtransformed for use with parametric statistics. Unpaired t test was used to compare the differences in clinical characteristics between groups at baseline and after treatment assessed for significance using for the discrete or continuous data and the chi-square test for frequency distributions. The changes in HbA1c, FBG and 2 h-BG over time (at baseline and at the other 2 visits) were studied using the repeated measurements ANOVA with treatment as grouping factor. Paired t tests were used to compare within-group changes. And unpaired t tests were also used to compare baseline variables between Responders and Non-responders in subjects treated with glimepiride-added. Linear regressions were performed to determine relationships between changes in serum HMW adiponectin levels and changes in HbA1c. The statistical analyses were performed using SPSS windows version 18.0, and p value < 0.05 was considered to be statistical significance.