Neutrophil extracellular trap (NET) formation, an innate immune system response, is associated with thrombogenesis and vascular endothelial injury. Circulatory disorders due to microvascular thrombogenesis are one of the principal causes of organ damage. NET formation in organs contributes to the exacerbation of sepsis, which is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. We have previously reported that recombinant human soluble thrombomodulin (rTM) reduces lipopolysaccharide (LPS)-induced NET formation in vitro. Here, we aimed to show that thrombomodulin (TM)-mediated suppression of NET formation protects against organ damage in sepsis. Mice were injected intraperitoneally (i.p.) with 10 mg/kg LPS. rTM (6 mg/kg/day) or saline was administered i.p. 1 h after LPS injection. In the LPS-induced murine septic shock model, extracellular histones, which are components of NETs, were observed in the liver and lungs. In addition, the serum cytokine (interleukin-1β (IL-1β), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), macrophage chemotactic protein-1 (MCP-1), and interleukin-10 (IL-10)) levels were increased. The administration of rTM in this model prevented NET formation in the organs and suppressed the increase in the levels of all cytokines except IL-1β. Furthermore, the survival rate improved. We provide a novel role of TM in treating inflammation and NETs in organs during sepsis.

Sepsis-induced coagulopathy has poor prognosis; however, there is no established tool for predicting it. We aimed to create predictive models for coagulopathy progression using machine-learning techniques to evaluate predictive accuracies of machine-learning and conventional techniques. A post-hoc subgroup analysis was conducted based on the Japan Septic Disseminated Intravascular Coagulation retrospective study. We used the International Society on Thrombosis and Haemostasis disseminated intravascular coagulation (DIC) score to calculate the ΔDIC score as ((DIC score on Day 3) − (DIC score on Day 1)). The primary outcome was to determine whether the predictive accuracy of ΔDIC was more than 0. The secondary outcome was the actual predictive accuracy of ΔDIC (predicted ΔDIC−real ΔDIC). We used the machine-learning methods, such as random forests (RF), support vector machines (SVM), and neural networks (NN); their predictive accuracies were compared with those of conventional methods. In total, 1017 patients were included. Regarding DIC progression, predictive accuracy of the multiple linear regression, RF, SVM, and NN models was 63.7%, 67.0%, 64.4%, and 59.8%, respectively. The difference between predicted ΔDIC and real ΔDIC was 2.05, 1.54, 2.24, and 1.77 for the multiple linear regression, RF, SVM, and NN models, respectively. RF had the highest predictive accuracy.

ABO blood groups have been implicated as potential risk factors for various diseases. However, no study has investigated the association between sepsis mortality and ABO blood types. We aimed to evaluate the impact of these blood types on mortality in patients with sepsis and septic shock. This retrospective observational study was conducted at two general hospitals in Japan. Patients diagnosed with sepsis or septic shock were included and divided into four groups based on blood type (O, A, B, and AB). The association between type O vs. other types and 28- and 90-day mortalities was evaluated using multivariate logistic regression analysis adjusted for age, sex, and Sequential (Sepsis-related) Organ Failure Assessment score. This study included 415 patients, of whom 131 (31.6%), 171 (41.2%), 81 (19.5%), and 32 (7.7%) had type O, A, B, and AB, respectively. Blood type O was not associated with 28-day (odds ratio: 1.7 p = 0.08) or 90-day mortality (odds ratio: 1.53, p = 0.091). However, type O was significantly associated with higher 90-day mortality (odds ratio: 3.26, p = 0.009) in patients with septic shock. The role of ABO blood type in risk stratification for septic shock and the mechanisms that potentially affect the prognosis of sepsis patients need further investigation.

We examined whether high lactate level in septic patients was associated with 90-day mortality based on the patients’ disseminated intravascular coagulation (DIC) status. We conducted a multicenter, retrospective, observational study of patients admitted to the intensive care unit (ICU) with a suspicion of severe infection and diagnosed with sepsis. Regression analyses were performed to estimate the interaction effect between DIC status and the lactate level. Then, the association between the lactate level and 90-day mortality was assessed in the DIC and non-DIC subgroups. The data of 415 patients were analyzed. We found a significant interaction between DIC status and the lactate level for predicting 90-day mortality (pinteraction = 0.04). Therefore, we performed a subgroup analysis and found that high lactate concentration was significantly associated with 90-day mortality in the DIC group (odds ratio = 2.31, p = 0.039) but not in the non-DIC group. In patients with DIC, a high lactate level significantly predicted 90-day mortality; no such association was found in the non-DIC group. Thus, DIC status may serve as a possible effect modifier of lactate level in predicting mortality in patients with sepsis.

The study aimed to evaluate the prevalence, risk factors, and clinical outcomes of pulmonary embolism in patients diagnosed with sepsis with and without shock. The National Inpatient Sample was used to identify adults with sepsis with and without shock between 2017 and 2019. The prevalence of acute pulmonary embolism and the association of acute pulmonary embolism with in-hospital mortality, hospital length of stay for survivors, and overall costs of hospitalization were evaluated. Multivariable logistic and linear regression analyses, adjusted for various parameters, were used to explore these associations. Of the estimated 5,019,369 sepsis hospitalizations, 1.2% of patients with sepsis without shock and 2.3% of patients with septic shock developed pulmonary embolism. The odds ratio for in-hospital mortality was 1.94 (95% confidence interval (CI) 1.85–2.03, p < 0.001). The coefficient for hospital length of stay was 3.24 (95% CI 3.03–3.45, p < 0.001). The coefficient for total costs was 46,513 (95% CI 43,079–49,947, p < 0.001). The prevalence of pulmonary embolism in patients diagnosed with sepsis with and without shock was 1.2 and 2.3%, respectively. Acute pulmonary embolism was associated with higher in-hospital mortality, longer hospital length of stay for survivors, and higher overall costs of hospitalization.