Spss 20 statistical package

All data were stored and analyzed using the SPSS Statistical Package 20.0 (SPSS Inc., Chicago, Illinois, USA). Descriptive statistics were computed for continuous and categorical variables. The statistics computed included median and interquartile range of continuous variables and frequencies and relative frequencies of categorical factors. Testing for differences of continuous variables between the study groups was accomplished by the 2-sample t-test for independent samples (parametric test, normally distributed data) or the Mann-Whitney U test (nonparametric test), as appropriate. Test selection was based on evaluating the variables for normal distribution employing the Kolmogorov-Smirnov test. Comparisons between the study groups for categorical variables were done using the chi-square test or Fisher's exact test.
To show whether and how strongly pairs of variables are related correlations were assessed using Spearman's rho correlation coefficient.
All P values resulted from two-sided statistical tests and values of P < 0.05 were considered to be statistically significant.

All data were stored and analysed using the SPSS statistical package 20.0 (SPSS Inc. Chicago, IL, USA). Descriptive statistics were computed for continuous and categorical variables. The statistics computed included mean and standard deviations (SD) of continuous variables and are presented as mean ± SD, frequencies and percentages of categorical factors.
The variables analysed were age, sex, complaints at presentation, symptoms, diagnoses, specialized examinations, laboratory examinations and proposed treatment. Confidence intervals of 95% (95%-CI) for important parameters are reported to show the reliability of the point estimates. A major factor determining the length of a confidence interval is the size of the used sample. The worst case would be a point estimate of 50%. In this case, we wanted to achieve an interval length of about 8–10 percent. It was possible with 500 people taking part in the survey. The sample size was determined by using the study planning software “nQuery Advisor^® 7.0” (nQuery (2017)) (Statistical solutions, Saugus, USA).

All data were stored and analyzed using the SPSS statistical package 20.0 (SPSS Inc. Chicago, Illinois, USA). Descriptive statistics were computed for continuous and categorical variables. The computed statistics included mean and standard deviations or median and interquartile range of continuous variables, frequencies, and relative frequencies of categorical factors. Testing for the differences of continuous variables between the study groups was accomplished by the two-sample t test for independent samples or the Mann-Whitney U test, as appropriate. Test selection was based on evaluating the variables for normal distribution employing the Kolmogorov-Smirnov test.
The logistic regression model was used to assess whether TF or MVs can predict risk of mortality, high SAPS II, and SOFA score. According to their average content of PS and TF, patients were divided into three groups and odds ratios as well as 95 % confidence intervals (95 % CI) were calculated for the outcome of survival, high SAPS II, and SOFA score while one of the groups was used as a reference group. All values resulted from two-sided statistical tests, and p ≤ 0.05 was considered to be significant.