Spss 13.0 version

Descriptive statistics were used to describe the population profile and the results are presented as average, standard deviation, medium, minimum, and maximum, and confidence interval of 95%.
For evaluation of the effects of the training on cardiovascular parameters and cardiac autonomic modulation, the difference between the values obtained at the end and start of the training protocol were compared in both groups. For this and for comparison of the group characteristics, covariance analysis (ANCOVA) was realized. This analysis compared the difference in the average between the control and training group, adjusting for possible confounders, sex, age and high blood pressure (controlled or not by betablockers and Ca+ channel blocker medication), that should be controlled due to their direct relationship with autonomic modulation. The significance level adopted was established at 5% for all tests. The statistical program SPSS (13.0 version) (SPSS Inc., Chicago, IL, EUA) was used for this analysis.

Descriptive statistics of mean and 95 % Confidence Interval (CI) were used to summarize all data. Analysis of Variance (ANOVA) was used to compare demographic variables of the participants in the different treatment groups. Kruskal Wallis test was used to compare the categorical variables such as BBQ, PSEQ and FABQ at baseline in the different treatment groups. Tukey multiple comparisons was used for post-hoc test analysis. Friedman’s ANOVA- (a non-parametric equivalent of the repeated measures ANOVA) was used for within group comparison of the effects of the different treatment regimen on the categorical variables. Wilcoxon signed ranked test was used as the post-hoc multiple comparisons to test for any significant difference found in the Friedman’s F-ratios. Alpha level was set at 0.05. The data analyses were carried out using SPSS 13.0 version software (SPSS Inc., Chicago, Illinois, USA).

Results of the RCSI and CTSI scores were given as the mean of the two raters. Inter-rater agreement for the RCSI and CTSI scores was tested using the kappa statistic, which was used to estimate the proportion of inter-rater agreement above that expected by chance. A weighted kappa statistic of 0.41–0.60 was considered moderate agreement, 0.61–0.80 good agreement, and 0.81–1.00 excellent agreement.
ROC analysis was also performed to examine the predictive effect of RCSI and CTSI scoring on the mortality and severity of AP, using mortality and severe AP as the dependent variables. The discriminative powers of the RCSI and CTSI scoring systems were visualized using ROC curves, including the area under the curve (AUC), with 95% confidence interval (CI). Additionally, the AUC values of the two scoring systems were compared using the z-test. The best cutoff values on the ROC curves of the RCSI and CTSI scores were calculated based on the maximum Youden index.
Statistical analysis was performed using commercially available software (SPSS 13.0 version, Chicago, IL, USA), except for the comparison of the AUC of the two scoring systems, which was done with MedCalc 11.6 (MedCalc Software, Mariakerke, Belgium).

Data were analyzed using Microsoft Excel and presented as mean ± SD for triplicates. Correlation coefficient matrix, principal component analysis, and cluster analysis were also conducted using SPSS 13.0 version (SPSS Inc., Chicago, IL, USA).