Risk model for predicting mortality in patients with necrotizing soft tissue infections in the intensive care unit.

BACKGROUND: The goal of this study is to look into the factors that lead to death in patients with necrotizing soft tissue infections（NSTIs） in the intensive care unit and create a mortality risk model. METHODS: The clinical data of 106 patients with necrotizing soft tissue infections admitted to intensive care unit(ICU) of the First Affiliated Hospital of Wenzhou Medical University between January 2008 and December 2021 were retrospectively analyzed. Univariate analysis and multivariate analysis were performed to evaluate the risk factors impacting patient mortality. The regression coefficient in binary logistic regression analysis was converted into the item score in the model, and then the model score of each patient was calculated. Finally, an ROC curve was constructed to evaluate the efficiency of the model for predicting mortality. Thirteen patients with NSTIs admitted to ICU between January 2022 and November 2022 were used to validate the model. RESULTS: The death group had 44 patients, while the survival group had 62 patients. The overall mortality was 41.5%. Binary logistic regression analysis showed that risk factors for mortality were age≥ 60 years(OR:4.419; 95%CI:1.093-17.862; P = 0.037), creatinine ≥ 132µmol/L(OR:11.166; 95%CI:2.234-55.816; P = 0.003), creatine kinase ≥ 1104 U/L(OR:4.019; 95%CI:1.134-14.250; P = 0.031), prothrombin time ≥ 24.4 s(OR:11.589; 95%CI:2.510-53.506; P = 0.002), and invasive mechanical ventilation (OR:17.404; 95%CI:4.586-66.052; P＜0.000). The AUC of the model for predicting mortality was 0.940 (95% CI:0.894-0.986). When the cut-off value for the model was 4 points, the sensitivity was 95.5% and the specificity was 83.9%. CONCLUSION: The death risk model in this study for NSTIs patients in the intensive care unit shows high sensitivity and specificity. Patients with a score of ≥ 4 points have a higher risk of mortality.

Orai1 overexpression improves sepsis-induced T-lymphocyte immunosuppression and acute organ dysfunction in mice.

Immune paralysis induced by sepsis, especially dysfunction of CD4+ T cells, leads to an increased risk of infection. In sepsis, abnormal differentiation of T lymphocytes is associated with multiorgan dysfunction syndrome. In T lymphocytes, the Orai1/nuclear factor of activated T Cells (NFAT) pathway is a critical mediator of infection, inflammation, and autoimmunity. In this study, we confirmed immunosuppression of splenic CD4+ T cells and abnormal differentiation of T lymphocytes in septic mice. Furthermore, we found that the Orai1/NFAT signaling pathway was inhibited in septic mice; however, the overexpression of Orai1 not only improved immune function of T cells in sepsis but also reduced the mortality and organ damage in septic mice. Moreover, the overexpression of Orai1 could reverse the increases in the numbers of T regulatory and T helper 17 cells in septic mice. These data suggest that the Orai1-mediated NFAT signaling pathway can improve sepsis-induced T-lymphocyte immunosuppression and acute organ dysfunction.

A latent profile analysis of emotional expression among patients with unintentional injuries.

BACKGROUND: Emotional expression has been suggested to affect the well-being of individuals with unintentional injuries. However, few studies have investigated it as a heterogeneous phenomenon. The purpose of this study was to characterize the patterns of emotional expression among patients with unintentional injuries using latent profile analysis, and to examine the relationship among these latent profiles and cognitive processing, posttraumatic growth, and posttraumatic stress disorder. METHODS: A cross-sectional study was carried out at two general hospitals in Wenzhou, China. In total, 352 patients with unintentional injuries completed the socio-demographic questionnaire, Berkeley Expressivity Questionnaire, Ambivalence Over Emotional Expression Questionnaire, Event-Related Rumination Inventory, the Posttraumatic Growth Inventory, and PTSD Checklist-Civilian Version.  RESULTS: Three unique profiles were identified: high emotional expressivity (n = 238, 67.6%), moderate emotional expressivity (n = 45, 12.8%), and low emotional expressivity (n = 69, 19.6%). The ANOVA and chi-square tests demonstrated significant differences among the three groups concerning deliberate rumination and posttraumatic growth. Multinomial logistic regression analysis indicated that monthly income and time since injury significantly predicted profile membership. CONCLUSIONS: Most patients showed high emotional expressivity after an unintentional injury. Emotional expression profiles were associated with deliberate rumination and posttraumatic growth. Emotional expression interventions tailored for different profiles are warranted after an unintentional injury.