**2.5 End points**

*Primary end points*


*Secondary end points*


#### **2.6 Data collection**

All clinical data are stored on the clinical informatic platform CLINIC DATA PRO (System Line—Empoli, Italy). All microbiological, immunological, and coagulation data are stored on the laboratory informatic platform—MODULAB GOLD ITALY (WERFEN UK). The data of 25 patients were transmitted and stored on the clinical platform REDCUP Villa.

#### **2.7 Ethical consideration**

The study protocol was approved by the Ethics Committee of the Azienda Ospedaliera San Camillo – Forlanini (reference No. 418 CE Lazio 1/2019) and registered at clinicaltrials.gov (NCT03914586). Written informed consent was obtained from each patient or next of kin.

#### **2.8 Statistical analysis**

Sample size calculation was based on changes in EAA level detected using the EAA test in a previous study on oXiris in patients with AKI and septic shock [BPUF]. Using a Student's paired t-test with a two-sided α = 0.05, it was calculated that 90% power would be obtained with a sample size of 60 patients, based on a decrease in endotoxin levels from 0.78[ 0.98–0.65 ] EU/ to 0.58 [0.13–0.41] EU/ml. To compensate for potentially larger variation in endotoxin levels, we estimated that 80 patients with complete datasets should be included.

Continuous variables are reported as mean ± SD or median (first–third quartiles) and categorical variables as count and proportion. Comparisons of proportions were made using Chi-square test or Fisher exact test. Continuous variables were compared

## *Extracorporeal Blood Purification with the Oxiris Membrane in Septic Shock DOI: http://dx.doi.org/10.5772/intechopen.106227*

using Student t-test or Wilcoxon rank-sum test and one-way anal-ysis of variance or Kruskal-Wallis test, as appropriate. Post hoc Tukey range test and Dunn's test for multiple comparisons were used. We performed stepwise (forward and backward) multivariable logistic regression analyses to identify factors associated with different types of infections.

We performed multivariate analyses to identify factors potentially associated with different infections: abdominal infection vs. thoracic infection. Covariates found to be associated with abdominal infection in the bivariate analysis with a p value of less than or equal to 0.20 were entered in stepwise (forward and backward) multivariable logistic regression analyses with significance alpha levels less than or equal to 0.05 for retention. Multicollinearity was assessed calculating a variance inflation factor of each variable and rules out if the variance inflation factor was lower than 4. Results are shown as ORs with 95% CIs, and model performance was assessed using the Hosmer-Lemeshow goodness-of-fit test statistic. These analyses were conducted with GraphPad Prism 7.02 (La Jolla, CA, USA).
