Spss 15.0 statistics software

The demographics and clinical characteristics of the CDAD and non-CDAD patients are
reported as means±SD with range for continuous variables and n (%) for categorical
variables. Differences in continuous data between the CDAD and non-CDAD patients were
compared using the two-sample t-test or the Mann-Whitney U-test if
data were not normally distributed; the Pearson chi-square test or Fisher's exact
test was used to analyze gender variation. Drug dosages are reported as the mean
defined daily dose (DDD) and mean drug utilization index (DUI; DDD/total days of drug
administration). Differences between groups were compared using the Mann-Whiney
U-test. We also used crude and multivariate logistic regression model analyses to
identify the association of CDAD with drug use. Variables with P<0.2 in the crude
logistic regression model were used in multivariate logistic regression model
analysis considering a stepwise method for variables selection. An odds ratio with
95%CI was used for logistic regression model analysis. All statistical assessments
were two-tailed, and P<0.05 was considered significant. Statistical analyses were
performed using the SPSS 15.0 statistics software (SPSS Inc., USA).

Phenotype was defined according to 2 symptoms, nausea and vomiting, which was divided into 2 groups (i.e., no symptoms and at least one symptom). The Hardy–Weinberg equilibrium test was performed by using SHEsis.^{[12 (link)]} One SNP was excluded from subsequent analysis because it contained only the CC genotype. And 2 SNPs with minor allele frequency <5% were also excluded from subsequent analysis. Age, height, weight, and body mass index (BMI) were presented by mean and standard deviation; the independent t test was performed to evaluate the differences between the 2 phenotype groups. Other categorical data were presented by number and percentage, Fisher exact test was performed to evaluate the association between the phenotype and the categorical data (prescription, wound pain, dizziness, drowsiness, genotypes of SNPs). The magnitude of association between SNPs and phenotype was generated by logistic regression and was presented with odds ratio (OR) and its 95% confidence interval (95% CI). To control for potential confounding effects, multiple logistic regression was performed with adjustment for age, body weight, prescription, type of surgery, and dose of morphine. A 2-tailed P < .05 was considered statistically significant. Data were analyzed by using SPSS 15.0 statistics software (SPSS Inc, Chicago, IL).

Continuous data were presented as mean and standard deviation, and categorical data as number and percentage. Differences between the two independent groups were tested with the independent two sample t-test and Fisher’s exact test for continuous and categorical data, respectively. The change trends between various time points within a group were analyzed by the repeated measurement ANOVA with Bonferroni correction. A two-tailed p-value < 0.05 was considered statistically significant. Statistical analyses were assessed by using SPSS 15.0 statistics software (SPSS Inc, Chicago, Illinois, USA).