Background: There was considerable debate regarding the effect of mean blood glucose (MBG) and glycemic variability (GV) on the mortality of septic patients. This retrospective cohort study aimed to assess the association between MBG and GV with ICU mortality of sepsis patients and to explore the optimal MBG range.Methods: Sepsis patients were enrolled from the Medical Information Mart for Intensive Care IV database (MIMIC-IV). MBG and glycemic coefficient of variation (Glu_CV) were, respectively, calculated to represent the overall glycemic status and GV during ICU stay. The associations between MBG, Glu_CV, and ICU mortality of the septic patients were assessed by using multivariate logistic regression in different subgroups and the severity of sepsis. Restricted cubic splines evaluated the optimal MBG target.Results: A total of 7,104 adult sepsis patients were included. The multivariate logistic regression results showed that increased MBG and Glu_CV were significantly correlated with ICU mortality. The adjusted odds ratios were 1.14 (95% CI 1.09–1.20) and 1.05 (95% CI 1.00–1.12). However, there was no association between hyperglycemia and ICU mortality among diabetes, liver disease, immunosuppression, and hypoglycemia patients. And the impact of high Glu_CV on ICU mortality was not observed in those with diabetes, immunosuppression, liver disease, and non-septic shock. The ICU mortality risk of severe hyperglycemia (≧200 mg/dl) and high Glu_CV (>31.429%), respectively, elevated 2.30, 3.15, 3.06, and 2.37, 2.79, 3.14-folds in mild (SOFA ≦ 3), middle (SOFA 3–7), and severe group (SOFA ≧ 7). The MBG level was associated with the lowest risk of ICU mortality and hypoglycemia between 120 and 140 mg/dl in the subgroup without diabetes. For the diabetic subset, the incidence of hypoglycemia was significantly reduced when the MBG was 140–190 mg/dl, but a glycemic control target effectively reducing ICU mortality was not observed.Conclusion: MBG and Glu_CV during the ICU stay were associated with all-cause ICU mortality in sepsis patients; however, their harms are not apparent in some particular subgroups. The impact of hyperglycemia and high GV on death increased with the severity of sepsis. The risk of ICU mortality and hypoglycemia in those with no pre-existing diabetes was lower when maintaining the MBG in the range of 120–140 mg/dl.

Objective: Sepsis-induced coagulopathy (SIC) is extremely common in individuals with sepsis, significantly associated with poor outcomes. This study attempted to develop an interpretable and generalizable machine learning (ML) model for early predicting the risk of 28-day death in patients with SIC. Methods: In this retrospective cohort study, we extracted SIC patients from the Medical Information Mart for Intensive Care III (MIMIC-III), MIMIC-IV, and eICU-CRD database according to Toshiaki Iba's scale. And the overlapping in the MIMIC-IV was excluded for this study. Afterward, only the MIMIC-III cohort was randomly divided into the training set, and the internal validation set according to the ratio of 7:3, while the MIMIC-IV and eICU-CRD databases were considered the external validation sets. The predictive factors for 28-day mortality of SIC patients were determined using recursive feature elimination combined with tenfold cross-validation (RFECV). Then, we constructed models using ML algorithms. Multiple metrics were used for evaluation of performance of the models, including the area under the receiver operating characteristic curve (AUROC), area under the precision recall curve (AUPRC), accuracy, sensitivity, specificity, negative predictive value, positive predictive value, recall, and F1 score. Finally, Shapley Additive Explanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME) were employed to provide a reasonable interpretation for the prediction results. Results: A total of 3280, 2798, and 1668 SIC patients were screened from MIMIC-III, MIMIC-IV, and eICU-CRD databases, respectively. Seventeen features were selected to construct ML prediction models. XGBoost had the best performance in predicting the 28-day mortality of SIC patients, with AUC of 0.828, 0.913 and 0.923, the AUPRC of 0.807, 0.796 and 0.921, the accuracy of 0.785, 0.885 and 0.891, the F₁ scores were 0.63, 0.69 and 0.70 in MIMIC-III (internal validation set), MIMIC-IV, and eICU-CRD databases. The importance ranking and SHAP analyses showed that initial SOFA score, red blood cell distribution width (RDW), and age were the top three critical features in the XGBoost model. Conclusions: We developed an optimal and explainable ML model to predict the risk of 28-day death of SIC patients 28-day death risk. Compared with conventional scoring systems, the XGBoost model performed better. The model established will have the potential to improve the level of clinical practice for SIC patients. Graphical

Emerging evidence suggests that dipeptidyl peptidase-4 (DPP-4) inhibitors, including sitagliptin, exert favourable effects on the vascular endothelium. DPP-4 inhibitors suppress the degradation of glucagon-like peptide-1 (GLP‑1), which has been reported to enhance nitric oxide (NO) production. However, the effects of DPP-4 inhibitors on endothelin-1 (ET-1) expression in the aorta, as well as the underlying mechanisms responsible for these effects, have yet to be investigated in animal models of diabetes mellitus (DM). In the present study, the rats were randomly divided into the following four groups: i) control; ii) DM; iii) DM + low‑dose sitagliptin (10 mg/kg); and iv) DM + high‑dose sitagliptin (30 mg/kg). Apart from the control group, all the rats received a high-fat diet for 8 weeks prior to the induction of diabetes with an intraperitoneal injection of streptozotocin. The treatments were then administered for 12 weeks. The serum levels of ET-1, NO, GLP-1 and insulin were measured as well as endothelial function. The expression of ET-1, AMP-activated protein kinase (AMPK) and nuclear factor (NF)-κB/IκBα were determined. After 12 weeks of treatment, the diabetic rats receiving sitagliptin showed significantly elevated serum levels of GLP-1 and NO, and reduced levels of ET-1. Moreover, sitagliptin significantly attenuated endothelial dysfunction as well as the remodeling of the aortic wall. Notably, sitagliptin inhibited ET-1 expression at the transcriptional and translational level in the aorta, which may have been mediated by the suppression of the NF-κB/IκBα system induced by AMPK activation. The majority of the above-mentioned effects were dose dependent. Taken together, the findings of the present study indicate that sitagliptin inhibits ET-1 expression in the aortic endothelium by suppressing the NF-κB/IκBα system through the activation of the AMPK pathway in diabetic rats. These findings further demonstrate some of the vasoprotective properties of DPP-4 inhibitors in vivo.

Glucagon-like peptide-1 (GLP-1) showed protective effects on endothelium-dependent dilatation. Since endothelial barrier dysfunction also plays a pivotal role in atherosclerosis, this study was designed to investigate the effects of GLP-1 on endothelial barrier function in diabetic aortic endothelium and explore the underlying mechanism. For in vivo studies, diabetic rats were established and subjected to 12- and 24-week treatment of exenatide. The morphological changes of aortic endothelium were observed with transmission electron microscope. A permeability assay of aortic endothelium was performed using the surface biotinylation technique. Protein expression was detected by immunohistochemical analysis and Western blots. For in vitro studies, human umbilical vein endothelial cells (HUVECs) were cultured in medium enriched with advanced glycation end products (AGEs) or AGEs plus GLP-1 and other reagents. The integrity of endothelium was evaluated by endothelial monolayer permeability assay and transendothelial resistance. The in vitro expressions of relevant proteins in signaling pathways were also detected by immunofluorescence and Western blots. In vivo, the enhanced aortic endothelial permeability in diabetic aortas were attenuated by exenatide treatment. Additionally, myosin light chain (MLC) phosphorylation, related to actomyosin contractility, and activation of its upstream targets in diabetic aorta were inhibited after administration of exenatide. In vitro, the endothelial monolayer permeability and the assembly of stress fibers were reduced by GLP-1 intervention under diabetic condition. Meanwhile, AGE-induced MLC phosphorylation mediating ECs contractility was inhibited by GLP-1. Furthermore, GLP-1 down-regulated the upstream targets of MLC phosphorylation, including RAGE, Rho/ROCK and MAPK signaling pathways. Intriguingly, the effects of GLP-1 elicited on ECs contractility and barrier function in diabetes were blunted by inhibition of GLP-1R, cAMP or PKA and stimulation of Rho/ROCK and MAPK signaling pathways. The findings of this study suggest that the stabilizing effect of GLP-1 on the endothelial barrier and contraction of AGE-treated ECs is caused by GLP-1R/cAMP/PKA activation and the subsequent inactivation of RAGE/Rho/ROCK as well as MAPK signaling pathways.