The study was approved by the Ethics Committee of Justus Liebig University Giessen (Local Registration Number: GI AZ 293/20, Amendment 2 (12.08.2022) and has a unique identifier on www.clinicaltrials.gov: NCT06365827. All participants gave their written consent to participate in this prospective registry study.

This prospective observational study included 500 out of 929 consecutive patients who underwent open-heart surgery at a clinic between March 2022 and December 2023. Patients with chronic organ insufficiency, preoperative infections (e.g., endocarditis), severe immunodeficiency, or lack of consent were excluded. Anonymized medical data were recorded electronically and evaluated using REDCap (Research Electronic Data Capture). The present study adheres to the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines for observational research, with specific consideration given to the combined design structure—namely, a nested case-control study embedded within a prospective cohort. Detailed methodological transparency is provided in accordance with the STROBE checklist (Supplementary STROBE Statement) [14].

Of 500 consecutive patients, 6 (1.2%) showed confirmed Me-Is. One patient was excluded from the analysis due to non-occlusive Me-Is (NOMI) diagnosed early after admission to the intensive care unit (ICU) and was treated with prostaglandin perfusion. Of 101 high-risk patients with hyperinflammatory status (interleukin-6 [IL-6] >600 ng/l) and metabolic acidosis (lactate >4 mmol/l), a target population of 25 were assigned by propensity matching to a Me-Is group (n = 5) or a control group (n = 20) in a ratio of 1:4. The combined use of lactate ≥ 4 mmol/L and IL-6 concentrations of approximately 600 pg/mL as inclusion thresholds is supported by previous studies, demonstrating their prognostic value in critically ill patients [15,16,17,18]. This ensured that the study cohort represented patients with severe metabolic and inflammatory dysregulation at high risk of adverse outcomes. In the Me-Is group, all five patients underwent laparotomy 2–3 days after ICU admission because of clinical signs of peritonitis, and the diagnosis of mesenteric ischemia was confirmed intraoperatively and subsequently by histopathological examination. Baseline characteristics of the overall and target populations are presented in Table 1, while Table 2 provides the intraoperative characteristics and the matched comparison of the Me-Is and control groups. The study population was thus divided into two groups: Me-Is and non-Me-Is controls (Fig. 2).

Overview of the total and target populations From a biobank of 500 surgical patients, 101 high-risk individuals (IL-6 > 600 pg/mL, lactate > 4 mmol/L) were identified. Five patients with confirmed mesenteric ischemia (Me-IS) were matched to 20 non-Me-IS controls (1:4 ratio). (Created in BioRender. Taghiyev, T. (2025) Abbreviations: Me-Is = mesenteric ischemia; IL-6 = Interleukin-6

Sampling and laboratory measurements of the citrate blood samples were taken perioperatively at 3 time points: T0 – preoperatively; T1 – upon admission to the ICU; T2 – 12 hours after ICU admission. An overview is given in Figure 3.

Overview of sampling time points of citrat-blood samples Patients undergoing cardiac surgery with extracorporeal circulation (ECC) were monitored from admission through discharge. Blood samples were collected at T₀ (pre-surgery), T₁ (ICU admission), and T₂ (12 h post-ICU admission) to enable perioperative analysis. (Created in BioRender. Taghiyev, T. (2025). Abbreviations: ECC = Extracorporeal Circulation; ICU = Intensive Care Unit; T0: Preoperative timepoint (before surgery); T1: Timepoint at ICU admission; T2 12 h after ICU admission

Blood was collected in citrate tubes and centrifuged twice (2000 × g, 10 min, at room temperature) to obtain platelet-poor plasma. Plasma was carefully removed, aliquoted, and immediately stored at −80 °C. Before analysis, rapid thawing (37 °C water bath), careful mixing, and storage at 4 °C until examination (maximum 2 h after thawing) were carried out.

For quality control, visual assessments of the platelet-free supernatant were made after each centrifugation step. The samples were immediately frozen to protect labile biomarkers. Polypropylene tubes were used to minimize adsorption.

For the quantitative determination of the prothrombin fragment F1.2 in human plasma, the Enzygnost™ F1 + 2 (monoclonal) assay from Siemens Healthineers (Marburg, Germany) was used. This enzyme-based immunological test is used to diagnose, monitor, and evaluate acquired or hereditary blood clotting disorders and supports the risk assessment for thrombosis and the monitoring of the effectiveness of anticoagulants.

The concentration of TAT was determined using the Enzygnost™ TAT microassay from Siemens Healthineers. This ELISA test enables the quantitative determination of TAT complexes in plasma and is used to diagnose hypercoagulability conditions such as disseminated intravascular coagulopathy (DIC).

Thrombin formation was analyzed with the RC Low reagents on the Ceveron® s100 system of Technoclone (Vienna, Austria). The Ceveron® s100 is a fully automated system designed to perform coagulation, chromogenic, and turbidimetric assays as well as thrombin generation testing (TGA) and quenching assays. The RC Low reagents have been specially developed for the investigation of thrombophilic tendencies and enable a detailed analysis of thrombin formation.

The statistical analyses were conducted utilizing Statistical Package for the Social Sciences (SPSS®) version 27.0 for Mac OS (IBM® Corporation released 2019, Armonk, New York, United States) and GraphPad Prism version 9.0.0 for Mac OS (GraphPad Software released 2020, San Diego, California USA) following appropriate coding procedures. Continuous variables are expressed as mean ± standard deviation (SD), and categorical variables are presented as frequencies and percentages. Inter-group disparities across various time points were assessed employing one-way analysis of variance (ANOVA), with Tukey’s post hoc test being applied in instances of observed differences. The normality of data distribution within each group was evaluated using the Shapiro-Wilk test. For normally distributed variables, Student’s t-test (unpaired) was utilized for comparison, and non-normally distributed variables were subjected to analysis using either the Mann-Whitney U-test or the Wilcoxon-signed-rank test.

Comparisons between different groups were made employing Pearson’s chi-squared test or Fisher’s exact test to ascertain independence of measurements. A standard confidence level of 95% was set, and statistical significance was determined at a p-value less than 0.05 (two-tailed). In instances of multiple comparisons, adjustments were made utilizing the Bonferroni correction method. Furthermore, the handling of outliers has been clarified, indicating that no extreme values were excluded from the analyses.

For propensity score matching, perioperative risk variables including age, body mass index (BMI), sex, EuroSCORE II, platelet count, partial thromboplastin time (PTT), and IL-6 and lactate levels were used to compare the two groups and minimize selection bias. Matching was performed at a 1:4 ratio (5 Me-Is patients vs. 20 control patients) based on propensity scores, without replacement, in order to minimize baseline differences and reduce the risk of selection bias.

No formal correction for multiple testing was performed, as the study was designed with an exploratory character and primarily aimed to generate hypotheses.