Spss ver 25.0 for windows

The data were analyzed with commercial software (SPSS® Ver. 25.0 for Windows; IBM Corp., Armonk, NY, USA) and expressed as means ± standard errors. Single-factor analysis of variance (ANOVA) was used for statistical comparisons, while the post hoc comparisons were analyzed through a Tukey’s test to determine the differences between means with normal distribution, as well as variables that presented a normal distribution after log (x + 1) transformation. The variables that did not present a normal distribution after the logarithmic transformation were analyzed through the Student’s t-test, and the post hoc comparisons were made through the Wilcoxon test. Differences were considered statistically significant when the p-values were <0.05.

Statistical analysis was performed using the SPSS ver. 25.0 for Windows (IBM Corp., Armonk, NY, USA). Cohen’s effect size and power was calculated using G Power ver.3.1. We performed an independent t-test and Fisher’s exact test to analyze the differences in the demographic and radiologic differences. An independent t-test was used to investigate statistical relationships of total CSA, rCSA, FCSA, FCSA/total CSA (%), MF: ES ratio, and SMI between the two groups. These variables were entered into binary logistic regression analysis. To determine which variables were the most statistically appropriate independent predictors (largest area under the curve (AUC) area) of DLS, we performed five logistic regression analyses. We used DLS as the dependent variable and five sets of variables (MF FCSA/ES FCSA, SMI FCSA, ratio of FCSA to total CSA, FCSA, rFCSA) as the independent variables. BMI, age, disk height, facet arthropathy grade, disk degeneration grade were adjusted in each logistic regression analysis. Statistical significance was set at p-values less than 0.05. All values were presented as mean ± standard deviation.