This study aims to investigate the mechanism by which resveratrol(RES) alleviates cerebral vascular endothelial damage in sepsis-associated encephalopathy(SAE) through network pharmacology and animal experiments. By using network pharmacology, the study identified common targets and genes associated with RES and SAE and constructed a protein-protein interaction( PPI) network. Gene Ontology(GO) analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed to pinpoint key signaling pathways, followed by molecular docking validation. In the animal experiments, a cecum ligation and puncture(CLP) method was employed to induce SAE in mice. The mice were randomly assigned to the sham group, CLP group, and medium-dose and high-dose groups of RES. The sham group underwent open surgery without CLP, and the CLP group received an intraperitoneal injection of 0. 9% sodium chloride solution after surgery. The medium-dose and high-dose groups of RES were injected intraperitoneally with 40 mg·kg-1 and 60 mg·kg~(-1) of RES after modeling, respectively, and samples were collected 12 hours later. Neurological function scores were assessed, and the wet-dry weight ratio of brain tissue was detected. Serum superoxide dismutase(SOD), catalase( CAT) activity, and malondialdehyde( MDA) content were measured by oxidative stress kit. Histopathological changes in brain tissue were examined using hematoxylin-eosin(HE) staining. Transmission electron microscopy was employed to evaluate tight cell junctions and mitochondrial ultrastructure changes in cerebral vascular endothelium. Western blot analysis was performed to detect the expression of zonula occludens1( ZO-1), occludin, claudins-5, optic atrophy 1( OPA1), mitofusin 2(Mfn2), dynamin-related protein 1(Drp1), fission 1(Fis1), and hypoxia-inducible factor-1α(HIF-1α). Network pharmacology identified 76 intersecting targets for RES and SAE, with the top five core targets being EGFR, PTGS2, ESR1, HIF-1α, and APP. GO enrichment analysis showed that RES participated in the SAE mechanism through oxidative stress reaction. KEGG enrichment analysis indicated that RES participated in SAE therapy through HIF-1α, Rap1, and other signaling pathways. Molecular docking results showed favorable docking activity between RES and key targets such as HIF-1α. Animal experiment results demonstrated that compared to the sham group, the CLP group exhibited reduced nervous reflexes, decreased water content in brain tissue, as well as serum SOD and CAT activity, and increased MDA content. In addition, the CLP group exhibited disrupted tight junctions in cerebral vascular endothelium and abnormal mitochondrial morphology. The protein expression levels of Drp1, Fis1, and HIF-1α in brain tissue were increased, while those of ZO-1, occludin, claudin-5, Mfn2, and OPA1 were decreased. In contrast, the medium-dose and high-dose groups of RES showed improved neurological function, increased water content in brain tissue and SOD and CAT activity, and decreased MDA content. Cell morphology in brain tissue, tight junctions between endothelial cells, and mitochondrial structure were improved. The protein expressions of Drp1, Fis1, and HIF-1α were decreased, while those of ZO-1, occludin, claudin-5, Mfn2, and OPA1 were increased. This study suggested that RES could ameliorate cerebrovascular endothelial barrier function and maintain mitochondrial homeostasis by inhibiting oxidative stress after SAE damage, potentially through modulation of the HIF-1α signaling pathway.
Animals ; Mice ; Network Pharmacology ; Resveratrol/administration & dosage* ; Male ; Sepsis-Associated Encephalopathy/genetics* ; Signal Transduction/drug effects* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Endothelium, Vascular/metabolism* ; Molecular Docking Simulation ; Protein Interaction Maps/drug effects* ; Humans ; Sepsis/complications* ; Oxidative Stress/drug effects*

Microglial pyroptosis and neuroinflammation have been implicated in the pathogenesis of sepsis-associated encephalopathy (SAE). OGT-mediated O-GlcNAcylation is involved in neurodevelopment and injury. However, its regulatory function in microglial pyroptosis and involvement in SAE remains unclear. In this study, we demonstrated that OGT deficiency augmented microglial pyroptosis and exacerbated secondary neuronal injury. Furthermore, OGT inhibition impaired cognitive function in healthy mice and accelerated the progression in SAE mice. Mechanistically, OGT-mediated O-GlcNAcylation of ATF2 at Ser44 inhibited its phosphorylation and nuclear translocation, thereby amplifying NLRP3 inflammasome activation and promoting inflammatory cytokine production in microglia in response to LPS/Nigericin stimulation. In conclusion, this study uncovers the critical role of OGT-mediated O-GlcNAcylation in modulating microglial activity through the regulation of ATF2 and thus protects against SAE progression.
Animals ; Microglia/metabolism* ; Pyroptosis/physiology* ; Mice ; Sepsis-Associated Encephalopathy/prevention & control* ; Activating Transcription Factor 2/metabolism* ; N-Acetylglucosaminyltransferases/genetics* ; Mice, Inbred C57BL ; Male ; Mice, Knockout

Sepsis-associated encephalopathy (SAE) is a common complication of sepsis, referring to a diffuse brain dysfunction caused by sepsis in the absence of direct central nervous system (CNS) infection. SAE occurs in up to 70% of patients with sepsis. Globally, the annual incidence of sepsis ranges from 30.0 to 48.9 million cases, resulting in approximately 11 million deaths per year, which accounts for 20% of all global mortalities. SAE is identified as an independent risk factor contributing to the increased mortality rate among these patients. Early diagnosis of SAE and related cerebral protection interventions hold significant clinical importance. Currently, the main indicators of brain function for sepsis patients include Glasgow coma score (GCS), confusion assessment method for the intensive care unit (CAM-ICU), electroencephalogram (EEG), brain CT or magnetic resonance imaging (MRI) and other related imaging changes, which have the problems of low sensitivity, poor specificity, and non-objective evaluation of the results of the diagnosis of SAE. This article focuses on the latest progress in the pathogenesis of SAE and systematically reviews potential biomarkers related to the onset of SAE from multiple aspects, including inflammatory markers, endothelial and neuronal injury markers, and metabolic markers. This will provide new insights for the clinical diagnosis and treatment of SAE.
Humans ; Sepsis-Associated Encephalopathy/therapy* ; Biomarkers ; Sepsis/complications* ; Magnetic Resonance Imaging ; Electroencephalography ; Brain Diseases/etiology*

Sepsis-associated encephalopathy (SAE) is one of the complications of sepsis, causes cognitive dysfunction ranging from mild attention deficits to progression into coma, which severely impairs patients' ability to live and mental health, and increases the long-term disability and mortality rates. Although the clinical attention to SAE has been increasing in recent years, effective interventions to improve cognitive dysfunction in sepsis survivors are still in the preclinical stage. The pathogenesis of SAE is numerous and complex, and mitochondrial dysfunction, as one of the key pathogenic mechanisms, plays a role in the cognitive development process through oxidative stress imbalance, energy metabolism disorders, and activation of apoptosis signaling pathway. The present review systematically integrates the recent studies on mitochondrial dysfunction in the development of cognitive disorders. This review systematically integrates the cutting-edge research results in recent years, discusses the mitochondrial structural disruption, mitochondrial kinetic abnormalities, respiratory chain dysfunction, and comprehensively comprehends the research progress of mitochondria-targeted antioxidant, mitochondrial autophagy activator, mitochondrial biosynthesis modifier and other novel intervention strategies in improving cognitive function of SAE patients, with the aim of providing theoretical basis for the breakthrough of the current status of clinical treatment of SAE and the targeting of mitochondria for treatment. The aim is to provide theoretical basis for breaking through the status of SAE clinical treatment and targeting mitochondrial therapy.
Humans ; Sepsis-Associated Encephalopathy/metabolism* ; Mitochondria/metabolism* ; Sepsis/complications* ; Oxidative Stress ; Cognitive Dysfunction ; Autophagy

OBJECTIVE: To construct machine learning prediction model for sepsis-associated encephalopathy (SAE), and analyze the application value of the model on early identification of SAE risk in elderly septic patients. METHODS: Patients aged over 60 years with a primary diagnosis of sepsis admitted to intensive care unit (ICU) from 2008 to 2023 were selected from Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2). Demographic variables, disease severity scores, comorbidities, interventions, laboratory indicators, and hospitalization details were collected. Key factors associated with SAE were identified using univariate Logistic regression analysis. The data were randomly divided into training and validation sets in a 7 : 3 ratio. Multivariable Logistic regression analysis was conducted in the training set and visualized using a nomogram model for prediction of SAE. The discrimination of the model was evaluated in the validation set using the receiver operator characteristic curve (ROC curve), and its calibration was assessed using calibration curve. Furthermore, multiple machine learning algorithms, including multi-layer perceptron (MLP), support vector machine (SVM), naive bayes (NB), gradient boosting machine (GBM), random forest (RF), and extreme gradient boosting (XGB), were constructed in the training set. Their predictive performance was subsequently evaluated on the validation set. Taking the XGB model as an example, the interpretability of the model through the SHapley Additive exPlanations (SHAP) algorithm was enhanced to identify the key predictive factors and their contributions. RESULTS: A total of 2 204 septic patients were finally enrolled, of whom 840 developed SAE (38.1%). A total of 21 variables associated with SAE were screened through univariate Logistic regression analysis. Multivariable Logistic regression analysis showed that endotracheal intubation [odds ratio (OR) = 0.40, 95% confidence interval (95%CI) was 0.19-0.88, P < 0.001], oxygen therapy (OR = 0.76, 95%CI was 0.53-0.95, P = 0.023), tracheotomy (OR = 0.20, 95%CI was 0.07-0.53, P < 0.001), continuous renal replacement therapy (CRRT; OR = 0.32, 95%CI was 0.15-0.70, P < 0.001), cerebrovascular disease (OR = 0.31, 95%CI was 0.16-0.60, P < 0.001), rheumatic disease (OR = 0.44, 95%CI was 0.19-0.99, P < 0.001), male (OR = 0.68, 95%CI was 0.54-0.86, P = 0.001), and maximum anion gap (AG; OR = 0.95, 95%CI was 0.93-0.97, P < 0.001) were associated with an decreased probability of SAE, and age (OR = 1.05, 95%CI was 1.03-1.06, P < 0.001), acute physiology score III (APSIII; OR = 1.02, 95%CI was 1.01-1.02, P < 0.001), Oxford acute severity of illness score (OASIS; OR = 1.04, 95%CI was 1.03-1.06, P < 0.001), and length of hospital stay (OR = 1.01, 95%CI was 1.01-1.02, P < 0.001) were associated with an increased probability of SAE. A nomogram model was constructed based on these variables. In the validation set, ROC curve analysis showed that the model achieved an area under the ROC curve (AUC) of 0.723, and the calibration curve showed good consistency between the predicted probability of the model and the observed probability. Among the machine learning algorithms, including MLP, SVM, NB, GBM, RF, and XGB, the SVM model and RF model demonstrated relatively good predictive performance, with AUC of 0.748 and 0.739, respectively, and the sensitivity was both exceeding 85%. The predictive performance of the XGB model was explained through SHAP analysis, and the results indicated that APSIII score (SHAP value was 0.871), age (SHAP value was 0.521), and OASIS score (SHAP value was 0.443) were important factors affecting the predictive performance of the model. CONCLUSIONS The machine learning-based SAE prediction model exhibits good predictive capability and holds significant application value for the early identification of SAE risk in elderly septic patients.
Humans ; Machine Learning ; Aged ; Sepsis-Associated Encephalopathy ; Sepsis/complications* ; Intensive Care Units ; Logistic Models ; Middle Aged ; Male ; ROC Curve ; Female ; Bayes Theorem ; Nomograms ; Support Vector Machine ; Algorithms

OBJECTIVES: Sepsis-associated encephalopathy (SAE) is a common complication of sepsis, which can lead to long-term cognitive impairment and anxiety in patients, and may even contribute to mortality in septic individuals. There is substantial individual variability in the incidence and severity and susceptibility of SAE, but the mechanisms regulating susceptibility remain unclear. Previous studies have shown that hippocampal damage is directly associated with cognitive and emotional disturbances in SAE. This study aims to explore the impact of hippocampal differentially expressed genes on SAE susceptibility in a mouse model. METHODS: Male specific pathogen-free (SPF)-grade C57BL/6 mice (6-8 weeks old) were randomly divided into a saline control group (Con group) and an SAE model group. SAE was induced by intraperitoneal injection of 10 mg/kg lipopolysaccharide (LPS), while control mice received an equivalent volume of saline. Cognitive and anxiety-like behaviors were assessed using the open field test (OFT), novel object recognition (NOR), and Y-maze test. Based on mean±standard deviation of behavioral results from the Con group, SAE mice were further classified into high-sensitivity (HS) and low-sensitivity (LS) subgroups. Immunohistochemistry was performed to detect the expression of immediate early gene c-Fos and neuronal marker neuronal nuclei (NeuN). Nissl staining was used to assess neuronal injury in the dentate gyrus (DG), cornu ammonis 1 (CA1), and cornu ammonis 3 (CA3) regions of the hippocampus. RNA sequencing (RNA-seq) was conducted on hippocampal tissues from HS and LS mice to identify differentially expressed genes, followed by pathway enrichment analysis. RESULTS: No significant behavioral susceptibility differences were observed between the overall SAE group and controls. However, HS mice showed severer cognitive deficits and anxiety-like behavior compared to LS mice. Immunohistochemistry revealed significantly higher expression of c-Fos in the hippocampus of LS mice (P<0.05), while Nissl and NeuN staining revealed milder neuronal damage in the hippocampus of LS mice than that of HS mice (both P<0.05). RNA-seq analysis identified 130 upregulated and 142 downregulated DEGs in LS and HS mice, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that upregulated genes in LS mice were primarily involved in pluripotency regulation, cyclic adenosine monophosphate (cAMP) signaling, and Wnt signaling pathways, in contrast, the downregulated genes were mainly related to cell adhesion, neuroactive ligand-receptor interaction, and calcium signaling pathways. CONCLUSIONS Differential gene expression in the hippocampus may contribute to individual susceptibility to cognitive and emotional dysfunction in SAE, suggesting potential genetic targets for individualized intervention.
Animals ; Sepsis-Associated Encephalopathy/genetics* ; Male ; Hippocampus/pathology* ; Mice, Inbred C57BL ; Mice ; Anxiety/genetics* ; Lipopolysaccharides ; Genetic Predisposition to Disease ; Disease Models, Animal ; Sepsis/genetics*

OBJECTIVE: To investigate the role and underlying mechanism of human myeloid differentiation protein 2 (MD2) in the process of neuronal death induced by lipopolysaccharide (LPS) by establishing an in vitro model of sepsis-associated encephalopathy (SAE) by LPS. METHODS: Healthy C57BL/6J mice at 14-18 days of gestation were selected, and brain cortical tissue was taken from fetal mice. Neurons were stimulated with 0 (control), 1, 5 and 10 g/L of LPS for 24 hours. The release of lactate dehydrogenase (LDH) was detected and the death of neurons was observed. Enzyme-linked immunosorbent assay (ELISA) was used to detect the levels of inflammatory factors interleukins (IL-6, IL-1β), in order to determine the optimal dose of LPS for establishing an in vitro neuroinflammation model of SAE. The cells were divided into blank control group and LPS group. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end-labeling (TUNEL) was used to discover apoptosis. Western blotting was used to detect the expression of the relevant protein markers activated caspase-3, necroptosis-associated protein neuronal receptor-interacting serine/threonine-protein kinase 3 (RIPK3) and phosphorylated RIPK3 (p-RIPK3). Immunofluorescence chemical staining was used to detect the expressions of p-RIPK3 and microtubule-associated protein 2 (MAP2) to evaluate the type of cell death and the degree of neuronal death. Western blotting was used to detect MD2 expression. Immunofluorescence chemical staining was performed to observe the expression and distribution of p-RIPK3 and MD2 in neurons to assess whether MD2 was involved in the inflammatory response promoting neuronal death. In addition, the cells were divided into blank control group, LPS group, and MD2 interfering peptide group (LPS+TC group), and the levels of IL-6, IL-1β and LDH were detected to evaluate whether interfering with MD2 can alleviate LPS induced neuroinflammation. RESULTS: 10 g/L LPS induced notable neuronal death, and the release of LDH in neurons stimulated with this concentration for 24 hours was significantly higher than that in the blank control group (relative release: 1.45±0.04 vs. 1.00±0.00, P < 0.01), indicating apoptosis and necroptosis occurred in neurons, and the levels of inflammatory factors IL-6 and IL-1β were remarkable increased [IL-6 (relative level): 1.94±0.04 vs. 1.00±0.00, IL-1β (relative level): 1.53±0.09 vs. 1.00±0.00, both P < 0.01]. Compared with the blank control group, the apoptosis of cells, cleaved-caspase-3 expression, the p-RIPK3/RIPK3 ratio, and p-RIPK3 expression around neurons in the LPS group were significantly increased [cleaved-caspase-3/GAPDH: 1.55±0.10 vs. 1.00±0.00, P < 0.01; p-RIPK3/RIPK3 ratio (relative value): 1.54±0.06 vs. 1.00±0.00, P < 0.05], which suggested that typical apoptosis and necroptosis apoptosis occurred in neurons in the septic environment. Furthermore, MD2 expression was significantly increased in the LPS group compared with the blank control group (MD2/GAPDH: 1.91±0.07 vs. 1.00±0.00, P < 0.01), and MD2 expression around neurons was increased, indicating that LPS-induced MD2 upregulation may play a key role in neuroinflammation and induction of neuronal death in sepsis. In addition, compared with the LPS group, the MD2-interfering peptide could reduce the expression levels of inflammatory factors IL-6 and IL-1β [IL-6 (relative level): 1.16±0.08 vs. 1.94±0.04, IL-1β (relative level): 1.15±0.05 vs. 1.75±0.09, both P < 0.01] and decrease LDH release (relative release: 1.09±0.01 vs. 1.44±0.04, P < 0.05). CONCLUSIONS LPS induced neuronal inflammatory responses via MD2, which ultimately leads to apoptosis and necroptosis. Interfering with MD2 reduces inflammation and inhibits neuronal death.
Mice ; Humans ; Animals ; Sepsis-Associated Encephalopathy ; Caspase 3 ; Interleukin-6 ; Neuroinflammatory Diseases ; Lipopolysaccharides ; Mice, Inbred C57BL ; Cell Differentiation ; Tumor Necrosis Factor-alpha

OBJECTIVE: To investigate the effects of gene of phosphate and tension homology (PTEN)-induced putative kinase 1 (PINK1)/Parkin pathway on hippocampal mitophagy and cognitive function in mice with sepsis-associated encephalopathy (SAE) and its possible mechanism. METHODS: A total of 80 male C57BL/6J mice were randomly divided into Sham group, cecal ligation puncture (CLP) group, PINK1 plasmid transfection pretreatment groups (p-PINK1+Sham group, p-PINK1+CLP group), empty vector plasmid transfection control group (p-vector+CLP group), with 16 mice in each group. The mice in CLP groups were treated with CLP to reproduce SAE models. The mice in the Sham groups were performed laparotomy only. Animals in the p-PINK1+Sham and p-PINK1+CLP groups were transfected with PINK1 plasmid through the lateral ventricle at 24 hours before surgery, while mice in the p-vector+CLP group were transfected with the empty plasmid. Morris water maze experiment was performed 7 days after CLP. The hippocampal tissues were collected, the pathological changes were observed under a light microscope after hematoxylin-eosin (HE) staining, and the mitochondrial autophagy was observed under a transmission electron microscopy after uranyl acetate and lead citrate staining. The expressions of PINK1, Parkin, Beclin1, interleukins (IL-6, IL-1β) and microtubule-associated protein 1 light chain 3 (LC3) were detected by Western blotting. RESULTS: Compared with the Sham group, CLP group mice in Morris water maze experiment had longer escape latency, shorter target quadrant residence time, and fewer times of crossing the platform at 1-4 days. Under the light microscope, the hippocampal structure of the mouse was injured, the neuronal cells were arranged in disorder, and the nuclei were pyknotic. Under the electron microscope, the mitochondria appeared swollen, round, and wrapped by bilayer or multilayer membrane structures. Compared with the Sham group, CLP group had higher expressions of PINK1, Parkin, Beclin1, LC3II/LC3I ratio, IL-6 and IL-1β in hippocampus, indicating that sepsis induced by CLP could activated inflammatory response and caused PINK1/Parkin-mediated mitophagy. Compared with the CLP group, p-PINK1+CLP group had shorter escape latencies, spent more time in the target quadrant and had more number of crossings in the target quadrant at 1-4 days. Under the light microscope, the hippocampal structures of mice was destroyed, the neurons were arranged disorderly, and the nuclei were pyknotic. Under transmission electron microscope, swollen and rounded mitochondria and mitochondrial structure wrapped by double membrane or multilayer membrane structure were observed. Compared with the CLP group, the levels of PINK1, Parkin, Beclin1 and LC3II/LC3 ratio in the p-PINK1+CLP group were significantly increased [PINK1 protein (PINK1/β-actin): 1.95±0.17 vs. 1.74±0.15, Parkin protein (Parkin/β-actin): 2.06±0.11 vs. 1.78±0.12, Beclin1 protein (Beclin1/β-actin): 2.11±0.12 vs. 1.67±0.10, LC3II/LC3I ratio: 3.63±0.12 vs. 2.27±0.10, all P < 0.05], while the levels of IL-6 and IL-1β were significantly decreased [IL-6 protein (IL-6/β-actin): 1.69±0.09 vs. 2.00±0.11, IL-1β protein (IL-1β/β-actin): 1.11±0.12 vs. 1.65±0.12, both P < 0.05], suggesting that overexpression of PINK1 protein could further activate mitophagy and reduce the inflammatory response caused by sepsis. There was no statistically significant difference in the above pathological changes and related indicators between Sham group and p-PINK1+Sham group, CLP group and p-vector+CLP group. CONCLUSIONS PINK1 overexpression can further activate CLP-induced mitophagy by upregulating Parkin, thereby inhibiting inflammation response and alleviate cognitive function impairment in SAE mice.
Male ; Animals ; Mice ; Mice, Inbred C57BL ; Sepsis-Associated Encephalopathy ; Phosphates ; Actins ; Beclin-1 ; Interleukin-6 ; Autophagy ; Ubiquitin-Protein Ligases ; Cognitive Dysfunction ; Sepsis ; Mitochondria ; Protein Kinases

Sepsis-associated encephalopathy(SAE) caused by infections outside the central nervous system always presents extensive brain damage.It is common in clinical practice and associated with a poor prognosis.There are problems in the assessing and diagnosing of SAE.Many factors,such as sedation and mechanical ventilation,make it difficult to assess SAE,while electrophysiological examination may play a role in the assessment.We reviewed the studies of electrophysiological techniques such as electroencephalography and somatosensory evoked potentials for monitoring SAE,hoping to provide certain evidence for the clinical evaluation and diagnosis of SAE.
Humans ; Sepsis-Associated Encephalopathy/complications* ; Sepsis/diagnosis* ; Electroencephalography

Objective: To explore the value of cerebral hypoxic-ischemic injury markers in the early diagnosis of sepsis associated encephalopathy (SAE) in burn patients with sepsis. Methods: A retrospective case series study was conducted. From October 2018 to May 2021, 41 burn patients with sepsis who were admitted to Zhengzhou First People's Hospital met the inclusion criteria, including 23 males and 18 females, aged 18-65 (35±3) years. According to whether SAE occurred during hospitalization, the patients were divided into SAE group (21 cases) and non-SAE group (20 cases). The gender, age, deep partial-thickness burn area, full-thickness burn area, and acute physiology and chronic health evaluation Ⅱ (APACHE Ⅱ) scores of patients were compared between the two groups. The serum levels of central nervous system specific protein S100β and neuron specific enolase (NSE) at 12, 24, and 48 h after sepsis diagnosis (hereinafter referred to as after diagnosis), the serum levels of interleukin-6 (IL-6), IL-10, tumor necrosis factor α (TNF-α), Tau protein, adrenocorticotropic hormone (ACTH), and cortisol at 12, 24, 48, 72, 120, and 168 h after diagnosis, and the mean blood flow velocity of middle cerebral artery (VmMCA), pulsatility index, and cerebral blood flow index (CBFi) on 1, 3, and 7 d after diagnosis of patients in the two groups were counted. Data were statistically analyzed with chi-square test, analysis of variance for repeated measurement, independent sample t test, and Bonferroni correction. The independent variables to predict the occurrence of SAE was screened by multi-factor logistic regression analysis. The receiver operating characteristic (ROC) curve was drawn for predicting the occurrence of SAE in burn patients with sepsis, and the area under the curve (AUC), the best threshold, and the sensitivity and specificity under the best threshold were calculated. Results: The gender, age, deep partial-thickness burn area, full-thickness burn area, and APACHE Ⅱ score of patients in the two groups were all similar (χ²=0.02, with t values of 0.71, 1.59, 0.91, and 1.07, respectively, P>0.05). At 12, 24, and 48 h after diagnosis, the serum levels of S100β and NSE of patients in SAE group were all significantly higher than those in non-SAE group (with t values of 37.74, 77.84, 44.16, 22.51, 38.76, and 29.31, respectively, P<0.01). At 12, 24, 48, 72, 120, and 168 h after diagnosis, the serum levels of IL-10, Tau protein, and ACTH of patients in SAE group were all significantly higher than those in non-SAE group (with t values of 10.68, 13.50, 10.59, 8.09, 7.17, 4.71, 5.51, 3.20, 3.61, 3.58, 3.28, 4.21, 5.91, 5.66, 4.98, 4.69, 4.78, and 2.97, respectively, P<0.01). At 12, 24, 48, 72, and 120 h after diagnosis, the serum levels of IL-6 and TNF-α of patients in SAE group were all significantly higher than those in non-SAE group (with t values of 8.56, 7.32, 2.08, 2.53, 3.37, 4.44, 5.36, 5.35, 6.85, and 5.15, respectively, P<0.05 or P<0.01). At 12, 24, and 48 h after diagnosis, the serum level of cortisol of patients in SAE group was significantly higher than that in non-SAE group (with t values of 5.44, 5.46, and 3.55, respectively, P<0.01). On 1 d after diagnosis, the VmMCA and CBFi of patients in SAE group were significantly lower than those in non-SAE group (with t values of 2.94 and 2.67, respectively, P<0.05). On 1, 3, and 7 d after diagnosis, the pulsatile index of patients in SAE group was significantly higher than that in non-SAE group (with t values of 2.56, 3.20, and 3.12, respectively, P<0.05 or P<0.01). Serum IL-6 at 12 h after diagnosis, serum Tau protein at 24 h after diagnosis, serum ACTH at 24 h after diagnosis, and serum cortisol at 24 h after diagnosis were the independent risk factors for SAE complicated in burn patients with sepsis (with odds ratios of 2.42, 1.38, 4.29, and 4.19, 95% confidence interval of 1.76-3.82, 1.06-2.45, 1.37-6.68, and 3.32-8.79, respectively, P<0.01). For 41 burn patients with sepsis, the AUC of ROC of serum IL-6 at 12 h after diagnosis for predicting SAE was 0.92 (95% confidence interval was 0.84-1.00), the best threshold was 157 pg/mL, the sensitivity was 81%, and the specificity was 89%. The AUC of ROC of serum Tau protein at 24 h after diagnosis for predicting SAE was 0.92 (95% confidence interval was 0.82-1.00), the best threshold was 6.4 pg/mL, the sensitivity was 97%, and the specificity was 99%. The AUC of ROC of serum ACTH at 24 h after diagnosis for predicting SAE was 0.96 (95% confidence interval was 0.89-1.00), the best threshold was 14.7 pg/mL, the sensitivity was 90%, and the specificity was 94%. The AUC of ROC of serum cortisol at 24 h after diagnosis for predicting SAE was 0.93 (95% confidence interval was 0.86-1.00), the best threshold was 89 nmol/L, the sensitivity was 94%, and the specificity was 97%. Conclusions: Serum Tau protein, ACTH, and cortisol have high clinical diagnostic value for SAE complicated in burn patients with sepsis.
Adolescent ; Adult ; Aged ; Burns/complications* ; Early Diagnosis ; Female ; Humans ; Male ; Middle Aged ; Prognosis ; ROC Curve ; Retrospective Studies ; Sepsis/diagnosis* ; Sepsis-Associated Encephalopathy ; Young Adult