Spss version 17.0 statistical software

We first performed an a priori power analysis to determine the appropriate sample size for our study. The primary study question was whether there were any differences in outcomes between the DFO and lateral UKA groups. To date, no studies have defined the minimum clinically important difference (MCID) based on KOOS and OKS in patients undergoing lateral UKA and DFO. Therefore, according to published literature, we defined the MCID as 5 and 15 points in OKS and KOOS scores, respectively [18 (link), 19 (link)]. Hence, considering an α level with p = 0.05, a power of 80%, and an effect size of 0.5, it was estimated that 27 subjects each would be needed in the experimental and the control groups in order to detect a statistically significant difference in OKS and KOOS scores.
The sample size calculation was performed using G*Power software (version 3.1, Düsseldorf, Germany). All continuous variables are expressed as mean ± standard deviation (SD). Categorical variables are expressed as number and percentage. The Student t-test for paired data was performed for each continuous variable to compare the preoperative and postoperative values between the two groups. Differences between categorical variables were evaluated with the chi-square test. SPSS (version 17.0) statistical software was used for biometric analysis. Post hoc power analysis was performed.

The statistical analyses were performed with SPSS version 17.0 statistical software (SPSS, Chicago, IL, USA). Figures were generated using GraphPad software. (GraphPad Software, La Jolla, USA).
K-S testing was used to investigate the distribution of plasma NT-ProBNP levels in both the experimental and control groups. The results showed that distributions were not normal (Z = 2.701, P < 0.001; Z = 1.402, P = 0.041). The Kruskal Wallis test was used to compare the plasma NT-proBNP levels in patients of the sepsis HF, sepsis non-HF, and healthy control groups; and for the plasma NT-proBNP levels for patients with mild, moderate, and severe HF. Spearman’s test was applied for the correlation analysis between plasma NT-proBNP levels and heart rate, breath rate, liver enlargement, ejection fraction, and modified Ross score in all HF patients.
ROC curves were employed to determine the optimal cut-off values of plasma NT-ProBNP for heart failure in patients with sepsis, severe sepsis, or septic shock. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative likelihood ratios, and 95% confidence intervals were calculated for the cutoff values. A probability of ≤ 0.05 was taken as significant.

All data were subjected to statistical analysis with SPSS version 17.0 statistical software (SPSS, Inc., Chicago, IL, USA), and the results are expressed as mean ± standard deviation (SD). The Kolmogorov-Smirnov test was used for normality testing, and Levene’s test was used to evaluate the homogeneity of variance. The randomized block design analysis of variance (ANOVA) was applied, and further pairwise comparisons used the Dunnett’s t-test, with P=0.05 set as the test standard, and P<0.05 was considered to indicate statistically significant difference.

All statistical analyses were conducted using SPSS version 17.0 statistical software (SPSS Inc., Chicago, IL, USA). Comparisons between groups for statistical significance were performed with a 2-tailed paired Student's t test. The relationship between GOLPH3 expression and clinicopathologic characteristics was analyzed by the χ² test. Survival curves were plotted using the Kaplan-Meier method and compared using the log-rank test. Survival data were evaluated by univariate and multivariate cox regression analyses. Values are the mean ± SD of 3 independent experiments. * P < 0.05, ** P < 0.01, ***P < 0.001, relative to control.