Spss 26 statistics for windows version 26

The continuous variables were expressed as the median and interquartile range (IQR), and the categorical variables were expressed as counts and percentages. The normality of quantitative data was checked by measures of Kolmogorov Smirnov tests of normality. Fisher exact test or Chi-Square test was used to compare categorical variables. The student's t-test was used to compare the two independent groups in the normally distributed numerical data analyses and the Mann–Whitney-U test in the abnormal distribution of numerical data. Binary logistic regression analysis was used to assess independent parameters' relation with the primary outcome. P values of < 0.05 were considered significant. Variables that reached P-value ≤ 0.10 in the univariable analysis were selected for the regression analysis to determine the adjusted odds ratio. All analyses were performed by IBM SPSS 26 Statistics for Windows, Version 26 software.

IBM SPSS 26 Statistics for Windows, Version 26 (IBM Corp: Armonk, NY, USA), was used for data analysis. p values lower than p < 0.05 were considered statistically significant. Nonparametric Kruskal-Wallis rank-sum test and Mann-Whitney-U-test were used as appropriate for group comparisons regarding ordinal analysis variables. Correlations between variables were obtained using Spearman’s rank correlation coefficient. For survival analysis, we used Cox Mantel log rank test. Analysis of TAAR1 as an independent prognosticator was done using Cox regression analysis. IBM SPSS 25 Statistics for Windows, Version 26, as well as Microsoft^® PowerPoint for Mac Version 16.30 (19101301) were used for design of figures.