Plasma-derived extracellular vesicles (EVs) as biomarkers of sepsis in burn patients via label-free Raman spectroscopy.

Sepsis following burn trauma is a global complication with high mortality, with ∼60% of burn patient deaths resulting from infectious complications. Diagnosing sepsis is complicated by confounding clinical manifestations of the burn injury, and current biomarkers lack the sensitivity and specificity required for prompt treatment. There is a strong rationale to assess circulating extracellular vesicles (EVs) from patient liquid biopsy as sepsis biomarkers due to their release by pathogens from bacterial biofilms and roles in the subsequent immune response. This study applies Raman spectroscopy to patient plasma-derived EVs for rapid, sensitive, and specific detection of sepsis in burn patients, achieving 97.5% sensitivity and 90.0% specificity. Furthermore, spectral differences between septic and non-septic burn patient EVs could be traced to specific glycoconjugates of bacterial strains associated with sepsis morbidity. This work illustrates the potential application of EVs as biomarkers in clinical burn trauma care and establishes Raman analysis as a fast, label-free method to specifically identify features of bacterial EVs relevant to infection amongst the host background.

Quantitative changes in platelet count in response to different pathogens: an analysis of patients with sepsis in both retrospective and prospective cohorts.

BACKGROUND: Thrombocytopenia is commonly observed in patients with sepsis and is an independent risk factor for poor prognosis. However, the changes of platelet count caused by different pathogens can vary significantly. Our study aims to evaluate the quantitative changes in platelet count in response to various pathogens. MATERIAL AND METHODS: We retrospectively analysed data of 3044 patients with sepsis from Medical Information Mart for Intensive Care (MIMIC, 2008-2019) database and prospectively collected data of 364 patients with sepsis from our local cohort of the Shandong Bloodstream Infection and Sepsis Collaboration Study (SBISC, 2020-2022). Propensity score matching (PSM) was employed to control for baseline differences in variables, except for the causative pathogen. RESULTS: Multivariate logistic analyses of both original and PSM populations identified Candida, Escherichia, Klebsiella, and Serratia species posing a higher risk for thrombocytopenia compared to others. Restricted cubic spline (RCS) curves showed L- or U-shaped associations between platelet count and 28-mortality with various cut-off values among different pathogens: ranging from 96 × 109/L in Candida species - 190 × 109/L in Klebsiella species. CONCLUSION: Our present findings indicate a pathogen-specific effect on platelet count, highlighting the importance of monitoring thrombocytopenia in patients infected with above microorganisms. Clinicians need to consider pathogen-specific thresholds when intervene on platelet count.

This study validated the differential incidence of thrombocytopenia among various pathogens within two distinct populations.Candida, Escherichia, Klebsiella, and Serratia species were identified as having a notably higher risk of causing thrombocytopenia compared to other pathogens.We observed L- or U-shaped relationships between platelet counts and 28-day mortality in Candida species, Enterococcus species, Escherichia species, Enterobacter species, Staphylococcus species, and Klebsiella species with platelet count cutoff values of 96 × 10⁹/L, 100 × 10⁹/L, 100 × 10⁹/L, 146 × 10⁹/L, 152 × 10⁹/L, and 190 × 10⁹/L, respectively.

Risk Factors of Sepsis-Associated Thrombocytopenia among Patients with Sepsis Induced Coagulopathy.

The study aims to evaluate the prognosis and risk factors of sepsis-associated thrombocytopenia (SAT) among patients with coagulopathy, and to provide evidence of the relationship between adverse outcomes and potential risks. Patients with sepsis-associated coagulopathy were included in the study from January 2014 to December 2022. The primary outcome was sepsis-associated thrombocytopenia (platelet count less than 100 *109/L), which was evaluated by logistic regression models adjusted for demographic characteristics and comorbidities. Among patients in the SAT group, 54% developed severe SAT, while 16% of these patients recovered from thrombocytopenia. The in-hospital mortality rate was significantly higher in the SAT group compared to the non-SAT group (31% in SAT group vs 23.9% in non-SAT group, p = 0.029). Even after adjusting for age, gender, Charlson comorbidity, white blood cell, and Sequential Organ Failure Assessment score, the differences in mortality rate persisted (Odds Ratio 0.72, [95% Confidence Interval 0.52-0.92]). Correlation analyses revealed that prothrombin time (r = 0.08, p = 0.50), international normalized ratio (r = 0.08, p = 0.42), prothrombin activity (r = -0.06, p > 0.999), D-dimer (r = -0.02, p > 0.999), and inflammatory parameters such as C-reactive protein (r = -0.11, p = 0.37) were not significantly correlated with platelet counts. According to subgroup analyses, patients with lung infection complicated by SAT had slightly higher mortality (OR 0.66, [95% CI, 0.46 to 0.94]). Sepsis-associated coagulopathy indicates a subset of critical ill patients, with those experiencing thrombocytopenia at greater risk for in-hospital death compared to those without it.

Prognostic and diagnostic utility of pancreatic stone protein in pediatric sepsis and mortality.

Background/aim: Early detection and prognosis of sepsis in critically ill children is crucial. The aim of this research was to investigate the prognostic ability of pancreatic stone protein (PSP) in validating sepsis and predicting mortality in a prospective observational study. Materials and methods: In a single-center study, pediatric intensive care unit patients were divided into cohorts of confirmed and suspected sepsis, as well as survivors and nonsurvivors. Patients with positive blood culture growth were considered to have confirmed sepsis, while their negative counterparts were considered to have suspected sepsis. Comparisons were made between complete blood counts, laboratory parameters, mortality indices, and C-reactive protein (CRP), procalcitonin (PCT), and PSP levels. The correlations between PSP and alternative inflammatory markers and mortality indices were then analyzed. The diagnostic and prognostic applicability of PSP for sepsis confirmation and mortality prediction was assessed using receiver operating characteristic curve analysis. Results: PSP levels were significantly elevated in patients with confirmed sepsis and within the nonsurvivor segment. In confirming sepsis and predicting mortality, PSP outperformed CRP and PCT in terms of sensitivity. It had sensitivity of 95% in diagnosing sepsis at a cut-off level of 50 ng/L, with an area under the curve (AUC) of 0.67 (95% CI: 0.52-0.81), and sensitivity of 92% in predicting mortality, with an AUC of 0.71 (95% CI: 0.56-0.83). In addition, PSP showed significant correlations with CRP, PCT, and mortality scores. Conclusion: PSP is emerging as a highly sensitive marker for confirming sepsis and predicting mortality in critically ill pediatric patients. Incorporating the PSP biomarker into routine clinical practice could potentially improve the management of pediatric sepsis.

KC-like chemokine as a biomarker of sepsis in dogs with pyometra.

BACKGROUND: Sepsis, defined as a dysregulated inflammatory response to infection inducing organ dysfunction, is a common cause of mortality in both humans and animals. Early detection and treatment is essential for survival, but accurate diagnosis is challenging due to the lack of specific biomarkers for sepsis. This study explored the potential of the keratinocyte-derived chemokine (KC)-like protein in dogs as a biomarker of sepsis in dogs with bacterial uterine infection (pyometra). The aim was to compare KC-like concentrations in dogs with pyometra with or without sepsis and to assess associations between KC-like and clinical variables, including days of hospitalization as an outcome. RESULTS: A mouse KC ELISA was validated and used to determine the concentrations of KC-like in serum from 34 dogs with pyometra and 18 healthy controls. Dogs with pyometra were classified as having sepsis based on two different criteria for systemic inflammatory response syndrome (SIRS), resulting in 74% and 30% sepsis-positive, respectively. The concentration of KC-like protein was higher in pyometra dogs with sepsis than in pyometra dogs without sepsis (p < 0.05) and in healthy controls (p < 0.0001) when using either of the two SIRS criteria. Moreover, KC-like was slightly increased in dogs with pyometra without sepsis compared with healthy controls when using the more stringent SIRS criteria (p < 0.05). Analyses of all dogs showed that KC-like concentrations correlated positively with hospitalization days, C-reactive protein (CRP) concentrations, white blood cells, and percentage of band neutrophils; however, KC-like correlated negatively with hemoglobin and did not correlate with circulating creatinine. CONCLUSIONS: Our results suggest that circulating KC-like protein increases in dogs with sepsis in pyometra and that KC-like is associated with more severe clinical illness. These findings support a potential role of KC-like as a biomarker of sepsis; however, the true identity of KC-like in dogs has yet to be uncovered.

Analysis of the diagnostic value of coagulation markers and coagulation function indices on the occurrence of DIC in sepsis and its prognosis.

Sepsis is a life-threatening condition that has the potential to multiple organ dysfunction and mortality. One of its frequent complications is disseminated intravascular coagulation (DIC), characterized by hyperactive clotting mechanisms that cause widespread clot formation and tissue damage. This study aimed to investigate early diagnostic markers of sepsis-associated DIC by comparing inflammatory factor levels, 28-day survival rates, coagulation function, and markers between patients with sepsis (non-DIC group) and those with sepsis-induced DIC (DIC group). The study analyzed the diagnostic efficacy of coagulation function and markers in predicting the occurrence and prognosis of sepsis-associated DIC, presenting survival curves. Results indicated significantly increased levels of APTT, TAT, tPAIC, PIC, and sTM in the DIC group compared to the non-DIC group. Sequential Organ Failure Assessment (SOFA) scores on days 1, 3, and 7 were notably lower in the non-DIC group. Correlation analysis revealed positive associations between PT, APTT, TAT, tPAIC, PIC, sTM levels, and SOFA scores, as well as negative associations with Fib and SOFA scores. Survival curves showed substantially lower mortality rates in the non-DIC group, highlighting significant survival disparities between groups. Combining all four coagulation indicators (TAT+ tPAIC + PIC + sTM) showed promising diagnostic value in evaluating disease severity, early DIC diagnosis, and sepsis prognosis.

The Circulating CDC42 Expression in Sepsis: Relation to Disease Susceptibility, Inflammation, Multiple Organ Dysfunctions and Mortality Risk.

OBJECTIVE: Cell division cycle 42 (CDC42) modulates inflammation and multiple organ dysfunction by regulating T-cell differentiation and macrophage polarization. This research intended to explore the association of blood CDC42 expression with septic risk, multi-organ dysfunctions, and mortality. METHODS: 145 sepsis patients and 50 health controls were recruited, then CDC42 expression in peripheral blood mononuclear cell (PBMC) from them was measured by RT-qPCR. RESULTS: CDC42 was decreased in sepsis patients versus health controls (P<0.001); meanwhile, the receiver operating characteristic (ROC) curve showed that CDC42 had a certain value to predict sepsis risk with an area under the curve (AUC) (95% confidence interval (CI): 0.797 (0.725-0.869). Furthermore, CDC42 was negatively correlated with C-reactive protein (P<0.001), tumor necrosis factor-alpha (P<0.001) and interleukin-17A (P<0.001) but less with interleukin-6 (P=0.056). Moreover, CDC42 was negatively related to the SOFA score (P<0.001) and its several subscales (respiratory system, liver, cardiovascular, and renal system) (P<0.05). Furthermore, CDC42 was lower in septic deaths versus survivors (P<0.001); meanwhile, the ROC curve exhibited a certain ability of CDC42 in estimating 28-day mortality with an AUC (95%CI) of 0.766 (0.676-0.855). CONCLUSION: Circulating CDC42 exhibits potency to be a prognostic biomarker reflecting multi-organ dysfunctions and higher mortality risk in sepsis.

Heart-type fatty acid binding protein (H-FABP) as an early biomarker in sepsis-induced cardiomyopathy: a prospective observational study.

BACKGROUND: Sepsis-induced cardiomyopathy (SICM) is a common and life-threatening complication of sepsis, significantly contributing to elevated mortality. This study aimed to identify crucial indicators for the prompt and early assessment of SICM. METHODS: Patients diagnosed with sepsis or SICM within 24 h of intensive care unit (ICU) admission were enrolled in this prospective observational study. Patients were assigned to the training set, validation set and external test set. The primary endpoint was 7-day ICU mortality, and the secondary endpoint was 28-day ICU mortality. Three machine learning algorithms were utilized to identify relevant indicators for diagnosing SICM, incorporating 64 indicators including serum biomarkers associated with cardiac, renal, and liver function, lipid metabolism, coagulation, and inflammation. Internal and external validations were performed on the screening results. Patients were then stratified based on the cut-off value of the most diagnostically effective biomarker identified, and their prognostic outcomes were observed and analyzed. RESULTS: A total of 270 patients were included in the training and validation set, and 52 patients were included in the external test set. Age, sex, and comorbidities did not significantly differ between the sepsis and SICM groups (P > 0.05). The support vector machine (SVM) algorithm identified six indicators with an accuracy of 84.5%, the random forest (RF) algorithm identified six indicators with an accuracy of 81.9%, and the logistic regression (LR) algorithm screened out seven indicators. Following rigorous selection, a diagnostic model for sepsis-induced cardiomyopathy was established based on heart-type fatty acid binding protein (H-FABP) (OR 1.308, 95% CI 1.170-1.462, P < 0.001) and retinol-binding protein (RBP) (OR 1.020, 95% CI 1.006-1.034, P < 0.05). H-FABP alone exhibited the highest diagnostic performance in both the internal (AUROC 0.689, P < 0.05) and external sets (AUROC 0.845, P < 0.05). Patients with SICM were further stratified based on an H-FABP diagnostic cut-off value of 8.335 ng/mL. Kaplan-Meier curve analysis demonstrated that elevated H-FABP levels at admission were associated with higher 7-day ICU mortality in patients with SICM (P < 0.05). CONCLUSIONS: This study revealed that H-FABP concentrations measured within 24 h of patient admission could serve as a crucial biomarker for the early and rapid diagnosis and short-term prognostic evaluation of SICM.

Urinary cystatin-C and urinary NGAL associated with sepsis predicts longer hospital stay in premature newborns.

Aim: To evaluate the urinary biomarkers related to sepsis in preterm newborns (NBs) and to investigate the predictive capacity of these biomarkers for a longer hospital stay.Methods: Serum and urine were collected from 27 healthy NBs, 24 NBs with neonatal infection without sepsis and 11 NBs with sepsis for the measurement of sindecan-1, lipocalin associated with urinary neutrophil gelatinase (uNGAL), urinary cystatin-C (uCysC) and urinary kidney injury molecule-1.Results: Levels of uNGAL and urinary cystatin-C were elevated in NBs with sepsis and neonatal infection, and uNGAL was significant predictor of hospital stay longer than 30 days (odds ratio: 1.052; 95% CI: 1.012-1.093; p = 0.01).Conclusion: uNGAL was associated with sepsis in preterm NBs and was useful to predict extended hospital stay.

[Box: see text].

The Role of Serum Albumin and Secretory Phospholipase A2 in Sepsis.

Sepsis is caused by a dysregulated host response to an infection that leads to cascading cell death and eventually organ failure. In this study, the role of inflammatory response serum secretory phospholipase A2 (sPLA2) and albumin in sepsis was investigated by determining the activities of the two proteins in serial serum samples collected on different days from patients with sepsis after enrollment in the permissive underfeeding versus standard enteral feeding protocols in an intensive care unit. Serum sPLA2 and albumin showed an inverse relationship with increasing sPLA2 activity and decreasing albumin membrane-binding activity in patients with evolving complications of sepsis. The activities of sPLA2 and albumin returned to normal values more rapidly in the permissive underfeeding group than in the standard enteral feeding group. The inverse sPLA2-albumin activity relationship suggests a complex interplay between these two proteins and a regulatory mechanism underlying cell membrane phospholipid homeostasis in sepsis. The decreased albumin-membrane binding activity in patients' serum was due to its fatty acid-binding sites occupied by pre-bound fatty acids that might alter albumin's structure, binding capacities, and essential functions. The sPLA2-albumin dual serum assays may be useful in determining whether nutritional intervention effectively supports the more rapid recovery of appropriate immune responses in critically ill patients with sepsis.

Novel cortisol trajectory sub-phenotypes in sepsis.

BACKGROUND: Sepsis is a heterogeneous syndrome. This study aimed to identify new sepsis sub-phenotypes using plasma cortisol trajectory. METHODS: This retrospective study included patients with sepsis admitted to the intensive care unit of Zhongshan Hospital Fudan University between March 2020 and July 2022. A group-based cortisol trajectory model was used to classify septic patients into different sub-phenotypes. The clinical characteristics, biomarkers, and outcomes were compared between sub-phenotypes. RESULTS: A total of 258 patients with sepsis were included, of whom 186 were male. Patients were divided into two trajectory groups: the lower-cortisol group (n = 217) exhibited consistently low and slowly declining cortisol levels, while the higher-cortisol group (n = 41) showed relatively higher levels in comparison. The 28-day mortality (65.9% vs.16.1%, P < 0.001) and 90-day mortality (65.9% vs. 19.8%, P < 0.001) of the higher-cortisol group were significantly higher than the lower-cortisol group. Multivariable Cox regression analysis showed that the trajectory sub-phenotype (HR = 5.292; 95% CI 2.218-12.626; P < 0.001), APACHE II (HR = 1.109; 95% CI 1.030-1.193; P = 0.006), SOFA (HR = 1.161; 95% CI 1.045-1.291; P = 0.006), and IL-1ß (HR = 1.001; 95% CI 1.000-1.002; P = 0.007) were independent risk factors for 28-day mortality. Besides, the trajectory sub-phenotype (HR = 4.571; 95% CI 1.980-10.551; P < 0.001), APACHE II (HR = 1.108; 95% CI 1.043-1.177; P = 0.001), SOFA (HR = 1.270; 95% CI 1.130-1.428; P < 0.001), and IL-1ß (HR = 1.001; 95% CI 1.000-1.001; P = 0.015) were also independent risk factors for 90-day mortality. CONCLUSION: This study identified two novel cortisol trajectory sub-phenotypes in patients with sepsis. The trajectories were associated with mortality, providing new insights into sepsis classification.

[Effect of fluid resuscitation with crystalloid combined with plasma on the prognosis of septic patients with hypoalbuminemia].

OBJECTIVE: To evaluate the difference in efficacy of two fluid resuscitation regimens, crystalloid alone versus crystalloid combined with plasma infusion, on the prognosis of septic patients with hypoalbuminemia. METHODS: A retrospective study was conducted. Septic patients with hypoalbuminemia admitted to the department of critical care medicine of Dongtai People's Hospital from January 2017 to December 2022 were selected as study subjects. Patients were divided into single group (crystalloid alone) and combined group (crystalloid combined with plasma) according to the fluid resuscitation regimen at the time of admission. General information, as well as coagulation indices before resuscitation (on day 1) and day 3 of resuscitation were collected. The primary study endpoint was 28-day mortality. The single and combined groups were stratified according to albumin level at resuscitation (< 25 g/L, 25-30 g/L, and > 30 g/L) to compare the differences in 28-day mortality among patients with different albumin levels. Kaplan-Meier survival curves of patients' 28-day prognosis were plotted. RESULTS: A total of 164 septic patients with hypoalbuminemia were included, including 60 patients in the single group and 104 patients in the combined group. (1) There were no significantly differences in age, gender, acute physiology and chronic health evaluation II (APACHE II), sequential organ failure assessment (SOFA), as well as pre-resuscitation platelet count (PLT), prothrombin time (PT), activated partial thromboplastin time (APTT), D-dimer, antithrombin- III (AT- III), international normalized ratio (INR), fibrin degradation product (FDP), serum lactic acid (Lac), and albumin level between the two groups, indicating comparability. (2) The levels of PT and AT- III in the combined group improved significantly on day 3 compared to before resuscitation, and the level of AT- III in the combined group improved more significantly on day 3 compared to the single group [(79.80±17.95)% vs. (66.67±18.69)%, P < 0.01]. Lac and albumin levels improved significantly after resuscitation in both the single and combined groups, but there were no significantly differences in the degree of improvement between the two groups. (3) There was no significantly difference in the 28-day mortality between the single group and the combined group [55.0% (33/60) vs. 42.3% (44/104), P > 0.05]. The 28-day mortality of patients with albumin < 25 g/L was significantly higher than that with albumin 25-30 g/L and > 30 g/L [63.1% (41/65) vs. 36.2% (25/69), 36.7% (11/30), both P < 0.05]. (4) Kaplan-Meier survival curve analysis showed that there was no significantly difference in 28-day cumulative survival rate between the single group and the combined group (Log-Rank: χ 2 = 2.067,P = 0.151). The median survival rate of albumin was 27.1 g/L [95% confidence interval (95%CI) was 24.203-29.997] in the single group and 28.7 g/L (95%CI was 26.065-31.335) in the combined group. CONCLUSIONS: Fluid resuscitation with crystalloid combined with plasma improves exogenous coagulation dysfunction in septic patients with hypoalbuminemia, but does not improve 28-day mortality outcome. The higher the initial albumin level in septic patients, the lower the mortality.

[Exploring the optimal range of pulse oxygen saturation in patients with sepsis: a retrospective study based on MIMIC- IV data].

OBJECTIVE: To explore the optimal pulse oxygen saturation (SpO2) range during hospitalization for patients with sepsis. METHODS: A case-control study design was employed. Demographic information, vital signs, comorbidities, laboratory parameters, critical illness scores, clinical treatment information, and clinical outcomes of sepsis patients were extracted from the Medical Information Mart for Intensive Care- IV (MIMIC- IV). A generalized additive model (GAM) combined with a Loess smoothing function was employed to analyze and visualize the nonlinear relationship between SpO2 levels during hospitalization and in-hospital all-cause mortality. The optimal range of SpO2 was determined, and Logistic regression model along with Kaplan-Meier curve were utilized to validate the association between the determined range of SpO2 and in-hospital all-cause mortality. RESULTS: A total of 5 937 patients met the inclusion criteria, among whom 1 191 (20.1%) died during hospitalization. GAM analysis revealed a nonlinear and U-shaped relationship between SpO2 levels and in-hospital all-cause mortality among sepsis patients during hospitalization. Multivariable Logistic regression analysis further confirmed that patients with SpO2 levels between 0.96 and 0.98 during hospitalization had a decreased mortality compared to those with SpO2 < 0.96 [hypoxia group; odds ratio (OR) = 2.659, 95% confidence interval (95%CI) was 2.190-3.229, P < 0.001] and SpO2 > 0.98 (hyperoxia group; OR = 1.594, 95%CI was 1.337-1.900, P < 0.001). Kaplan-Meier survival curve showed that patients with SpO2 between 0.96 and 0.98 during hospitalization had a higher probability of survival than those patient with SpO2 < 0.96 and SpO2 > 0.98 (Log-Rank test: χ 2 = 113.400, P < 0.001). Sensitivity analyses demonstrated that, with the exception of subgroups with smaller sample sizes, across the strata of age, gender, body mass index (BMI), admission type, race, heart rate, systolic blood pressure, diastolic blood pressure, mean arterial pressure, respiratory rate, body temperature, myocardial infarction, congestive heart failure, cerebrovascular disease, chronic liver disease, diabetes mellitus, sequential organ failure assessment (SOFA), simplified acute physiology score II (SAPS II), systemic inflammatory response syndrome score (SIRS), and Glasgow coma score (GCS), the mortality of patients with SpO2 between 0.96 and 0.98 was significantly lower than those of patients with SpO2 < 0.96 and SpO2 > 0.98. CONCLUSIONS: During hospitalization, the level of SpO2 among sepsis patients exhibits a U-shaped relationship with in-hospital all-cause mortality, indicating that heightened and diminished oxygen levels are both associated with increased mortality risk. The optimal SpO2 range is determined to be between 0.96 and 0.98.

[Establishment and evaluation of a nomogram model for predicting the risk of sepsis in diabetic foot patients].

OBJECTIVE: To establish a nomogram model for predicting the risk of sepsis in diabetic foot patients, and to provide reference for clinical prevention and treatment. METHODS: The clinical data of 430 patients with diabetic foot who were hospitalized in Chu Hsien-I Memorial Hospital of Tianjin Medical University from January 2022 to March 2023 were reviewed and collected, including age, gender, past medical history, smoking and drinking history, family history, diabetes course, Texas grade of diabetic foot and laboratory indicators within 24 hours after admission. Patients were divided into sepsis group and non-sepsis group according to the presence or absence of sepsis during hospitalization. The differences in clinical data between the two groups were compared. Multivariate Logistic regression analysis was used to screen the influencing factors of sepsis in patients with diabetic foot during hospitalization, and a nomogram predictive model was established. The performance of the prediction model was evaluated by receiver operator characteristic curve (ROC curve), calibration curve and decision curve analysis (DCA). Internal validation was performed by using Bootstrap method. RESULTS: A total of 430 patients were enrolled, among which 90 patients developed sepsis during hospitalization and 340 patients did not. There were statistically significant differences in diabetes course, Texas grade of diabetic foot, white blood cell count (WBC), neutrophil count (NEU), lymphocyte count (LYM), neutrophil to lymphocyte ratio (NLR), hemoglobin (Hb), albumin (Alb), glycosylated hemoglobin (HbA1c), C-reactive protein (CRP), and blood urea nitrogen (BUN) between the two groups. Multivariate Logistic regression analysis showed that diabetes course [odds ratio (OR) = 2.774, 95% confidence interval (95%CI) was 1.053-7.308, P = 0.039], Texas grade of diabetic foot (OR = 2.312, 95%CI was 1.014-5.273, P = 0.046), WBC (OR = 1.160, 95%CI was 1.042-1.291, P = 0.007), HbA1c (OR = 1.510, 95%CI was 1.278-1.784, P < 0.001), CRP (OR = 1.007, 95%CI was 1.000-1.014, P = 0.036) were independent risk factors for sepsis in patients with diabetic foot during hospitalization, while Alb was a protective factor (OR = 0.885, 95%CI was 0.805-0.972, P = 0.011). A nomogram predictive model was constructed based on the above 6 indicators. The ROC curve showed that the area under ROC curve (AUC) of the nomogram predictive model for identifying the sepsis patients was 0.919 (95%CI was 0.889-0.948). The AUC of the nomogram predictive model after internal verification was 0.918 (95%CI was 0.887-0.946). Hosmer-Lemeshow test showed χ 2 = 2.978, P = 0.936, indicating that the calibration degree of the predictive model was good. Calibration curve showed that the predicted probability of sepsis was in good agreement with the actual probability. DCA curve showed that the nomogram predictive model had good clinical usefulness. CONCLUSIONS: The nomogram predictive model based on the risk factors of diabetes course, Texas grade of diabetic foot, WBC, HbA1c, CRP and Alb has good predictive value for the occurrence of sepsis in patients with diabetic foot during hospitalization, which is helpful for clinical screening of the possibility of diabetic foot patients progressing to sepsis, and timely personalized intervention for different patients.

[Predictive value of plasma exosome count for the prognosis in septic patients].

OBJECTIVE: To investigate the predictive value of plasma exosome count for the prognosis of patients with sepsis. METHODS: A prospective observational study was conducted. The patients with sepsis admitted to intensive care unit (ICU) of Zhejiang Hospital from November 2020 to December 2021 were enrolled as the study subjects. On the 1st day of admission to the ICU, the patient's gender, age, underlying disease, infection site, mean arterial pressure (MAP) and severity scores were recorded, and venous blood was taken for detecting the blood routine, blood biochemistry, and procalcitonin (PCT), and arterial blood was taken for blood gas analysis, simultaneously, the patient's noradrenaline (NA) dosage was recorded. On the 1st, 3rd, 5th, and 7th day of ICU admission, plasma exosomes were extracted, and the number of exosomes was detected by nanoparticle tracking analyzer. The endpoint of observation was the death of the patient 28 days after admission to the ICU. The differences in baseline data and plasma exosome counts of patients with different 28-day prognosis were analyzed and compared. The Spearman correlation method was used to analyze the correlation between plasma exosome counts and other clinical indicators. Binary multivariate Logistic regression analysis was used to screen the 28-day death risk factors of septic patients. The receiver operator characteristic curve (ROC curve) was plotted to analyze the predictive value of each index on the 28-day death of septic patients. The Kaplan-Meier method was used to analyze the 28-day survival curve. RESULTS: A total of 26 patients with sepsis were enrolled, of whom 21 survived and 5 died on the 28th day. Compared with the survival group, the patients in the death group had lower MAP, higher sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation II (APACHE II) score, white blood cell count (WBC), cardiac troponin I (cTnI), and worse oxygenation. The plasma exosome count on the 1st day of ICU admission in the death group was significantly higher than that in the survival group (×1015/L: 16.96±9.11 vs. 5.20±2.42, P < 0.05). Subsequently, the plasma exosome counts in both groups continued to decrease, and there was no statistically significant difference between the two groups. Spearman correlation analysis showed that the plasma exosome count on the 1st day of ICU admission in septic patients was significantly positively correlated with SOFA score, APACHE II score, blood lactic acid (Lac), alanine aminotransferase (ALT) and NA dosage (r values were 0.572, 0.585, 0.463, 0.411, 0.696, all P < 0.05), and it significantly negatively correlated with MAP and oxygenation index (PaO2/FiO2; r values were -0.392 and -0.496, both P < 0.05). Multivariate Logistic regression analysis showed that plasma exosome count on the 1st day of ICU admission was an independent risk factor for 28-day death in septic patients [odds ratio (OR) = 1.385, 95% confidence interval (95%CI) was 1.075-1.785, P = 0.012]. ROC curve analysis showed that the area under the ROC curve (AUC) of plasma exosome count on the 1st day of ICU admission for predicting 28-day death in septic patients was 0.800 (95%CI was 0.449-1.000); when the optimal cut-off value was 14.50×1015/L, the sensitivity was 80.0% and the specificity was 100%. According to the optimal cut-off value of 1-day plasma exosome count, the patients were divided into two groups for Kaplan-Meier survival curve analysis, and the results showed that the cumulative survival rate of patients with plasma exosome count < 14.50×1015/L was significantly higher than that of patients with plasma exosome count ≥ 14.50×1015/L (Log-Rank test: χ 2 = 19.100, P < 0.001). CONCLUSIONS: The plasma exosome count of septic patients is significantly increased on the 1st day of admission to the ICU, which is related to the severity, and can predict the risk of death at 28 days.

Can We Improve Mortality Prediction in Patients with Sepsis in the Emergency Department?

Background and Objectives: Sepsis represents a global health challenge and requires advanced diagnostic and prognostic approaches due to its elevated rate of morbidity and fatality. Our study aimed to assess the value of a novel set of six biomarkers combined with severity scores in predicting 28 day mortality among patients presenting with sepsis in the Emergency Department (ED). Materials and Methods: This single-center, observational, prospective cohort included sixty-seven consecutive patients with septic shock and sepsis enrolled from November 2020 to December 2022, categorized into survival and non-survival groups based on outcomes. The following were assessed: procalcitonin (PCT), soluble Triggering Receptor Expressed on Myeloid Cells-1 (sTREM-1), the soluble form of the urokinase plasminogen activator receptor (suPAR), high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and azurocidin 1 (AZU1), alongside clinical scores such as the Quick Sequential Organ Failure Assessment (qSOFA), Systemic Inflammatory Response Syndrome (SIRS), the Sequential Organ Failure Assessment (SOFA), the Acute Physiology and Chronic Health Evaluation II (APACHE II), the Simplified Acute Physiology Score II and III (SAPS II/III), the National Early Warning Score (NEWS), Mortality in Emergency Department Sepsis (MEDS), the Charlson Comorbidity Index (CCI), and the Glasgow Coma Scale (GCS). The ability of each biomarker and clinical score and their combinations to predict 28 day mortality were evaluated. Results: The overall mortality was 49.25%. Mechanical ventilation was associated with a higher mortality rate. The levels of IL-6 were significantly higher in the non-survival group and had higher AUC values compared to the other biomarkers. The GCS, SOFA, APACHEII, and SAPS II/III showed superior predictive ability. Combining IL-6 with suPAR, AZU1, and clinical scores SOFA, APACHE II, and SAPS II enhanced prediction accuracy compared with individual biomarkers. Conclusion: In our study, IL-6 and SAPS II/III were the most accurate predictors of 28 day mortality for sepsis patients in the ED.

Combining host immune response biomarkers and clinical scores for early prediction of sepsis in infection patients.

BACKGROUND: The performance of host immune responses biomarkers and clinical scores was compared to identify infection patient populations at risk of progression to sepsis, ICU admission and mortality. METHODS: Immune response biomarkers were measured and NEWS, SIRS, and MEWS. Logistic and Cox regression models were employed to evaluate the strength of association. RESULTS: IL-10 and NEWS had the strongest association with sepsis development, whereas IL-6 and CRP had the strongest association with ICU admission and in-hospital mortality. IL-6 [HR (95%CI) = 2.68 (1.61-4.46)] was associated with 28-day mortality. Patient subgroups with high IL-10 (≥ 5.03 pg/ml) and high NEWS (> 5 points) values had significantly higher rates of sepsis development (88.3% vs 61.1%; p < 0.001), in-hospital mortality (35.0% vs. 16.7%; p < 0.001), 28-day mortality (25.0% vs. 5.6%; p < 0.001), and ICU admission (66.7% vs. 38.9%; p < 0.001). CONCLUSIONS: Patients exhibiting low severity signs of infection but high IL-10 levels showed an elevated probability of developing sepsis. Combining IL-10 with the NEWS score provides a reliable tool for predicting the progression from infection to sepsis at an early stage. Utilizing IL-6 in the emergency room can help identify patients with low NEWS or SIRS scores.

Risk and mediation analyses of hemoglobin glycation index and survival prognosis in patients with sepsis.

An increasing number of studies have reported the close relation of the hemoglobin glycation index (HGI) with metabolism, inflammation, and disease prognosis. However, the prognostic relationship between the HGI and patients with sepsis remains unclear. Thus, this study aimed to analyze the association between the HGI and all-cause mortality in patients with sepsis using data from the MIMIC-IV database. In this study, 2605 patients with sepsis were retrospectively analyzed. The linear regression equation was established by incorporating glycated hemoglobin (HbA1c) and fasting plasma glucose levels. Subsequently, the HGI was calculated based on the difference between the predicted and observed HbA1c levels. Furthermore, the HGI was divided into the following three groups using X-tile software: Q1 (HGI ≤ - 0.50%), Q2 (- 0.49% ≤ HGI ≤ 1.18%), and Q3 (HGI ≥ 1.19%). Kaplan-Meier survival curves were further plotted to analyze the differences in 28-day and 365-day mortality among patients with sepsis patients in these HGI groups. Multivariate corrected Cox proportional risk model and restricted cubic spline (RCS) were used. Lastly, mediation analysis was performed to assess the factors through which HGI affects sepsis prognosis. This study included 2605 patients with sepsis, and the 28-day and 365-day mortality rates were 19.7% and 38.9%, respectively. The Q3 group had the highest mortality risk at 28 days (HR = 2.55, 95% CI: 1.89-3.44, p < 0.001) and 365 days (HR = 1.59, 95% CI: 1.29-1.97, p < 0.001). In the fully adjusted multivariate Cox proportional hazards model, patients in the Q3 group still displayed the highest mortality rates at 28 days (HR = 2.02, 95% CI: 1.45-2.80, p < 0.001) and 365 days (HR = 1.28, 95% CI: 1.08-1.56, p < 0.001). The RCS analysis revealed that HGI was positively associated with adverse clinical outcomes. Finally, the mediation effect analysis demonstrated that the HGI might influence patient survival prognosis via multiple indicators related to the SOFA and SAPS II scores. There was a significant association between HGI and all-cause mortality in patients with sepsis, and patients with higher HGI values had a higher risk of death. Therefore, HGI can be used as a potential indicator to assess the prognostic risk of death in patients with sepsis.

Triglyceride-glucose index and clinical outcomes in sepsis: A retrospective cohort study of MIMIC-IV.

Although accumulating researches were done for investigating the relationship between triglyceride-glucose index (TyG index) and different diseases, none of the researches have been made in sepsis yet. In this study, we aimed to explore the relationship between TyG index and clinical outcomes in sepsis based on a large critical care public database. Sepsis patients in Medical Information Mart for Intensive Care IV (MIMIC-IV) Database were included. The exposure was TyG index, which was calculated by the equation: ln (TG (mg/dL) × FBG (mg/dL)/2). The outcomes were in-hospital mortality and 1-year mortality. The relationship between TyG index and outcomes was performed by Cox regression analysis. Smooth fitting curves were constructed by using generalized additive model. Kaplan-Meier analyses for cumulative hazard of 1-year mortality in different groups were done. 1103 sepsis patients were included with a median TyG index of 9.78. The mortalities of in-hospital and 1-year were 37.53% (n = 414) and 42.25% (n = 466), respectively. After adjusting confounders, there was a significantly negative relationship between TyG index and mortalities of in-hospital and 1-year. With the per unit increment in TyG index, the risk of in-hospital and 1-year mortality both decreased by 21% (HR = 0.79, 95% CI: 0.66-0.94, p = 0.0086 and HR = 0.79, 95% CI: 0.66-0.94, p = 0.0080, respectively). A negative relationship between TyG index and clinical outcomes in sepsis was found.