Spss v28.0.1.1

The two study groups were defined using descriptive statistics (percentage, mean ± standard deviation (SD), median, and interquartile range (IQR)). The normality of variable data was tested using the Shapiro–Wilk test. Normally distributed continuous variables were expressed as mean ± SDs and compared using the independent t-test. Continuous variables with skewed distribution were plotted as medians (25th and 75th interquartile range (IQR)) and compared using the Mann–Whitney U and Kruskal–Wallis tests. Categorical variables were presented as numbers and percentages (n, %) and analyzed using the Chi-squared test. Spearman’s rank correlation coefficient (r) was used to investigate the relationships between NLR, PCT, and CRP and sepsis evolution. Multiple linear regression analysis was performed to verify which laboratory infection biomarkers (PCT, CRP, and NLR) are independently associated with sepsis. Ultimately, the receiver operating characteristic (ROC) curve was plotted to assess the discrimination ability of those variables in identifying septic patients. Youden’s index (calculated as sensitivity + specificity − 1) determined optimal threshold values. Statistical analyses were performed using Statistical Package for Social Sciences software (SPSS v28.0.1.1., IBM Corporation, Armonk, NY, USA). A two-sided p value below 0.05 was considered statistically significant.

Statistical data analysis was performed using the SPSS v28.0.1.1 statistical package (IBM Corp., Armonk, NY, USA). Normal distribution was tested using the Kolmogorov–Smirnov test. If the data were not normally distributed, they were transformed using log transformation. Cortisol data were centered and log-transformed to reduce skewness. A repeated-measurement analysis of variance with “group” and “time” was performed to investigate the effect of social threat on cortisol response and pain perception. Bonferroni-corrected post hoc tests were performed as required. For all the above analyses, p-values of less than 0.05 were considered significant.

Statistical analysis was performed in SPSS v 28.0.1.1 (IBM SPSS statistics for Windows and Macintosh v.28.0.1.1, Armonk, NY). Categorical variables are presented as frequencies or percentages, whereas continuous variables are presented by mean and range if normal distributed or median and interquartile range if not normal distributed. Statin users and non-statin users were compared as independent groups using the chi-square test (categorical data), T-test (normal distribution), or Mann–Whitney U test (not normal distribution). Uni- and multivariate analyses were performed to identify possible predictors of VS and DCI. Patients living long enough to develop VS after the ictus (day 5) were included in this subanalysis. Any variable with p < 0.100 in the univariate analysis was included in the multivariable model, unless there occurred collinearity. For VS and outcome data, we also matched pairs of statin users and non-statin users by age (fuzzy factor 5.0), exact match of Fisher and WFNS grade, and by hypertension (yes/no). When there was more than one possible match, we chose the match with the same gender. A significance level of 5% was adopted, and all p-values are provided for 2-sided tests.