Statistic package for social science spss version 17

Continuous variables were described as the mean and standard deviation for variables with normal distribution and the median and interquartile range for variables with skewed distribution. Categorical variables were described as the number and percentage. Continuous variables were compared with Student’s t-test (normal distribution) and Mann–Whitney U test (skewed distribution). Categorical variables were compared with Chi-square test. Pearson’s (continuous variables with normal distribution) and Spearman’s (continuous variables with skewed distribution and categorical variables) correlations were used to assess the simple relationships between MetS risk factors and renal function. In order to assess the independent relationships between MetS risk factors and renal function, multivariate linear regression analyses were adjusted by age, sex, smoking, WC, SBP, DBP, TC, TG, HDL-C, LDL-C and FBG, and multivariate logistic regression analyses were adjusted by age, sex, smoking, abdominal obesity, hypertension, dyslipidemia and DM. Statistical significance was accepted at the two-sided 0.05 level, and confidence interval (CI) was computed at the 95% level. Statistical analyses were performed with Statistic Package for Social Science (SPSS) version 17 (SPSS Inc., Chicago, IL, U.S.).

Continuous variables were described by mean and standard deviation (normal distribution) or median and interquartile range (skewed distribution). Continuous variables were compared by Student’s t test (normal distribution) or Mann–Whitney U test (skewed distribution). Categorical variables were described by number and percentage, and compared by chi-square test. Relationship of drugs with survival time was bivariately evaluated with Kaplan-Meier analysis (log-rank). Relationship of drugs with mortality rate were multivariately adjusted by age, gender, body mass index (BMI), CAD, CHF, AF, hypertension, heart rate, SBP, DBP, hemoglobin, albumin, GFR, FPG, triglyceride, LDL-C and HDL-C using Cox Regression (Enter). Enter is the most commonly used in different methods of Cox Regression, such as Enter, Forward conditional, Forward LR, Forward Wald, Backward conditional, Backward LR and Backward Wald. Statistical analyses were performed with Statistic Package for Social Science (SPSS) version 17 (SPSS Inc., Chicago, USA).