Death In Sepsis Patients Research Articles

Presepsin Does Not Predict Risk of Death in Sepsis Patients Admitted to the Intensive Care Unit: A Prospective Single-Center Study.

Background: Sepsis is defined as life-threatening organ dysfunction caused by an abnormal host response to infection. The study aimed to evaluate the utility of presepsin (P-SEP) in predicting the risk of death in patients with sepsis at the time of intensive care unit (ICU) admission. Methods: Adult patients were included in the study if they met SEPSIS-3 criteria at ICU admission. Demographic and clinical data were collected. The following inflammatory parameters were determined: C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), and presepsin (P-SEP). Material was collected for microbiological testing depending on the suspected source of infection. The primary endpoint was patient death before ICU discharge. The secondary endpoint was a positive microbiological test result. Results: Eighty-six patients were included in the study. Thirty patients (35%) died before discharge from the ICU. There was no difference in P-SEP, CRP, PCT, and IL-6 values between patients who survived and those who died (p > 0.05 for all). P-SEP, CRP, PCT, and IL-6 were determined at ICU admission and did not accurately predict the risk of death in ROC curve analysis (p > 0.05 for all). Confirmation of the location of the focus of bacterial infection by microbiological testing was obtained in 43 (49%) patients. P-SEP, PCT, CRP, and IL-6 were significantly higher in patients with positive microbiological findings. Conclusions: In patients with suspected sepsis admitted to the Intensive Care Unit, presepsin does not accurately predict the risk of in-hospital death, but it can predict a positive microbiological culture.

Association between albumin-bilirubin score and in-hospital mortality in patients with sepsis: Evidence from two large databases

BackgroundThe Albumin-Bilirubin (ALBI) score, recommended for assessing the prognosis of hepatocellular carcinoma patients, has garnered attention. The efficacy of ALBI score in forecasting the risk of death in sepsis patients remains limited. We designed two cohort studies to assess the association between ALBI score and in-hospital mortality in patients with sepsis. MethodsA retrospective analysis was conducted utilizing data from the Second Affiliated Hospital of Guangzhou Medical University and the Medical Information Mart for Intensive Care IV(MIMIC-IV). Patients diagnosed with sepsis were included in the analysis. The primary outcome was the in-hospital mortality. Multivariate Cox regression analysis was conducted to assess the independent association between the ALBI score and mortality, with adjustment for potential confounders. Subgroup analysis was conducted to assess the robustness of the findings. ResultsThe Guangzhou Sepsis Cohort (GZSC) of the Second Affiliated Hospital of Guangzhou Medical University comprised 2969 participants, while the MIMIC-IV database included 8841 participants. The ALBI score were categorized into < -2.60, −2.60∼-1.39, and >-1.39. After adjusting for confounders, a linear relationship was observed between ALBI score and mortality. Patients with a high ALBI grade were associated with higher in-hospital mortality in both the GZSC (HR: 1.52, 95%CI: 1.24–1.87, p < 0.001) and the MIMIC-IV database (HR: 1.57, 95%CI: 1.46–1.70, p < 0.001). ConclusionsA high ALBI score is associated with higher in-hospital mortality among sepsis patients in ICU.

Development and validation of a machine-learning model for predicting the risk of death in sepsis patients with acute kidney injury

The mortality rate of patients with sepsis-induced acute kidney injury (S-AKI) is notably elevated. The initial categorization of prognostic indicators has a beneficial impact on elucidating and enhancing disease outcomes. This study aimed to predict the mortality risk of S-AKI patients by employing machine learning techniques. The sample size determined by a four-step procedure yielded 1508 samples. The research design necessitated the inclusion of individuals with S-AKI from the Medical Information Mart for Intensive Care (MIMIC)-IV database. The patients were initially admitted to the Intensive Care Unit (ICU) for their hospital stay. Additionally, these patients (aged from 18 to 89 years old) had encountered S-AKI on the day of their admittance. Forty-two predictive factors were analyzed, with hospitalization death as the outcome variable. The training set (4001 cases) consisted of 70 % of the participants, and the remaining (1714 cases) participants were allocated to the validation set. Furthermore, an additional validation set (MIMIC-III) consisted of 1757 patients from the MIMIC-III database. Moreover, an external validation set from the Intensive Care Department of Beijing Friendship Hospital (BFH) comprised 72 patients. Six machine learning models were employed in the prediction, namely the logistic, lasso, rpart, random forest, xgboost, and artificial neural network models. The comparative efficacy of the newly developed model in relation to the APACHE II model for predicting mortality risk was also assessed. The XGBoost model exhibited a superior performance with the training set. With the internal validation set and the two external validation sets (MIMIC-III and BFH), the xgboost algorithm demonstrated the highest performance. Meanwhile, APACHE II performed poorly at predicting the mortality risk with the BFH validation set. The mortality risk was influenced by three primary clinical parameters: urine volume, lactate, and Glasgow Coma Scale (GCS) score. Thus, we developed a prediction model for the risk of death among S-AKI patients that has an improved performance compared to previous models and is a potentially valuable tool for S-AKI prediction and treatment in the clinic.

The effects of antioxidant supplementation on short-term mortality in sepsis patients

BackgroundThe occurrence and development of sepsis are related to the excessive production of oxygen free radicals and the weakened natural clearance mechanism. Further dependable evidence is required to clarify the effectiveness of antioxidant therapy, especially its impact on short-term mortality. ObjectivesThe purpose of this systematic review and meta-analysis was to evaluate the effect of common antioxidant therapy on short-term mortality in patients with sepsis. MethodsAccording to PRISMA guidelines, a systematic literature search on antioxidants in adults sepsis patients was performed on PubMed/Medline, Embase, and the Cochrane Library from the establishment of the database to November 2023. Antioxidant supplements can be a single-drug or multi-drug combination: HAT (hydrocortisone, ascorbic acid, and thiamine), ascorbic acid, thiamine, N-acetylcysteine and selenium. The primary outcome was the effect of antioxidant treatment on short-term mortality, which included 28-day mortality, in-hospital mortality, intensive care unit mortality, and 30-day mortality. Subgroup analyses of short-term mortality were used to reduce statistical heterogeneity and publication bias. ResultsSixty studies of 130,986 sepsis patients fulfilled the predefined criteria and were quantified and meta-analyzed. Antioxidant therapy reduces the risk of short-term death in sepsis patients by multivariate meta-analysis of current data, including a reduction of in-hospital mortality (OR = 0.81, 95% CI 0.67 to 0.99; P = 0.040) and 28-day mortality (OR = 0.81, 95% CI 0.69 to 0.95]; P = 0.008). Particularly in subgroup analyses, ascorbic acid treatment can reduce in-hospital mortality (OR = 0.66, 95% CI 0.90 to 0.98; P = 0.006) and 28-day mortality (OR = 0.43, 95% CI 0.24 to 0.75; P = 0.003). However, the meta-analysis of RCTs found that antioxidant therapy drugs, especially ascorbic acid, did substantially reduce short-term mortality(OR = 0.78, 95% CI 0.62 to 0.98; P = 0.030; OR = 0.57, 95% CI 0.36 to 0.91; P = 0.020). ConclusionsAccording to current data of RCTs, antioxidant therapy, especially ascorbic acid, has a trend of improving short-term mortality in patients with sepsis, but the evidence remains to be further demonstrated.

Association between lactate to hematocrit ratio and 30-day all-cause mortality in patients with sepsis: a retrospective analysis of the Medical Information Mart for Intensive Care IV database.

The lactate to hematocrit ratio (LHR) has not been assessed for predicting all-cause death in sepsis patients. This study aims to evaluate the relationship between LHR and 30-day all-cause mortality in sepsis patients. This retrospective study used the data from Medical information mart for intensive care IV (MIMIC-IV, version 2.0). Our study focused on adult sepsis patients who were initially hospitalized in the Intensive care unit (ICU). The prognostic significance of admission LHR for 30-day all-cause mortality was evaluated using a multivariate Cox regression model, ROC curve analysis, Kaplan-Meier curves, and subgroup analyses. A total of 3,829 sepsis patients participated in this study. Among the cohort, 8.5% of individuals died within of 30 days (p < 0.001). The area under the curve (AUC) for LHR was 74.50% (95% CI: 71.6-77.50%), higher than arterial blood lactate (AUC = 71.30%), hematocrit (AUC = 64.80%), and shows no significant disadvantage compared to qSOFA, SOFA, and SAPS II. We further evaluated combining LHR with qSOFA score to predict mortality in sepsis patients, which shows more clinical significance. ROC curve analysis showed that 6.538 was the optimal cutoff value for survival and non-survival groups. With LHR ≥6.538 vs. LHR <6.538 (p < 0.001). Subgroup analysis showed significant interactions between LHR, age, sex, and simultaneous acute respiratory failure (p = 0.001-0.005). LHR is an independent predictor of all-cause mortality in sepsis patients after admission, with superior predictive ability compared to blood lactate or hematocrit alone.

Effect of ethanol exposure on innate immune response in sepsis.

Alcohol use disorder, reported by 1 in 8 critically ill patients, is a risk factor for death in sepsis patients. Sepsis, the leading cause of death, kills over 270,000 patients in the United States alone and remains without targeted therapy. Immune response in sepsis transitions from an early hyperinflammation to persistent inflammation and immunosuppression and multiple organ dysfunction during late sepsis. Innate immunity is the first line of defense against pathogen invasion. Ethanol exposure is known to impair innate and adaptive immune response and bacterial clearance in sepsis patients. Specifically, ethanol exposure is known to modulate every aspect of innate immune response with and without sepsis. Multiple molecular mechanisms are implicated in causing dysregulated immune response in ethanol exposure with sepsis, but targeted treatments have remained elusive. In this article, we outline the effects of ethanol exposure on various innate immune cell types in general and during sepsis.

A simplified machine learning model utilizing platelet-related genes for predicting poor prognosis in sepsis.

Thrombocytopenia is a known prognostic factor in sepsis, yet the relationship between platelet-related genes and sepsis outcomes remains elusive. We developed a machine learning (ML) model based on platelet-related genes to predict poor prognosis in sepsis. The model underwent rigorous evaluation on six diverse platforms, ensuring reliable and versatile findings. A retrospective analysis of platelet data from 365 sepsis patients confirmed the predictive role of platelet count in prognosis. We employed COX analysis, Least Absolute Shrinkage and Selection Operator (LASSO) and Support Vector Machine (SVM) techniques to identify platelet-related genes from the GSE65682 dataset. Subsequently, these genes were trained and validated on six distinct platforms comprising 719 patients, and compared against the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ-Failure Assessment (SOFA) score. A PLT count <100×109/L independently increased the risk of death in sepsis patients (OR = 2.523; 95% CI: 1.084-5.872). The ML model, based on five platelet-related genes, demonstrated impressive area under the curve (AUC) values ranging from 0.5 to 0.795 across various validation platforms. On the GPL6947 platform, our ML model outperformed the APACHE II score with an AUC of 0.795 compared to 0.761. Additionally, by incorporating age, the model's performance was further improved to an AUC of 0.812. On the GPL4133 platform, the initial AUC of the machine learning model based on five platelet-related genes was 0.5. However, after including age, the AUC increased to 0.583. In comparison, the AUC of the APACHE II score was 0.604, and the AUC of the SOFA score was 0.542. Our findings highlight the broad applicability of this ML model, based on platelet-related genes, in facilitating early treatment decisions for sepsis patients with poor outcomes. Our study paves the way for advancements in personalized medicine and improved patient care.

Short-term survival survey and risk factors analysis of death in sepsis patients in intensive care unit

To analyze the 28-day survival status and influencing factors of adult patients with sepsis, providing reference for early diagnosis of sepsis prognosis and reducing sepsis mortality. A retrospective cohort study was conducted. A total of 160 adult patients with sepsis in the department of intensive care unit of the 940th Hospital of Joint Logistic Support Force of PLA from January 2021 to December 2022 were enrolled. The general information, laboratory examination results within 24 hours after admission, clinical treatment measures, and prognosis of patients were collected. Univariate analysis and binary multivariate Logistic regression were performed to screen the risk factors that might affect the short-term prognosis of patients with sepsis. Receiver operator characteristic curve (ROC curve) was plotted to analyze the predictive value of various risk factors on the short-term death risk of sepsis patients. A total of 160 patients with sepsis were enrolled, of whom 91 survived in 28 days, and 69 died with a mortality of 43.12%. Compared with the survival group, the patients in the death group were older, more severe, had higher blood lactic acid (Lac) level, and had more complications such as hypertension and multiple organ dysfunction syndrome (MODS). A total of 22 related factors were statistically significant: age, acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score, length of hospital stay, Lac, interleukin-6 (IL-6), fibrinogen (FIB), international normalized ratio (INR), ratio of prothrombin time (PT) to healthy people, prothrombin activity (PTA), PT, thrombin time (TT), oxygenation index (PaO2/FiO2), aspartate aminotransferase (AST), ratio of AST to alanine amninotransferase (ALT), serum creatinine (SCr), blood urea nitrogen (BUN), site of infection, history of hypertension, concurrent MODS, implementation of continuous renal replacement therapy (CRRT), and treatment with vasoactive drugs. Combined with the results of the univariate analysis, variables that might affect the short-term prognosis of septic patients were included in the multivariate Logistic regression analysis. The results showed that APACHE II score ≥ 20 [odds ratio (OR) = 1.106, 95% confidence interval (95%CI) was 1.003-1.219], Lac ≥ 5 mmol/L (OR = 1.430, 95%CI was 1.041-1.964), combined with hypertension (OR = 13.879, 95%CI was 1.082-178.016), concurrent MODS (OR = 98.139, 95%CI was 18.252-527.672) was an independent risk factor for 28-day death in adult septic patients (all P < 0.05). ROC curve analysis showed that the combination of the four indicators including APACHE II score, Lac, combined with hypertension, concurrent MODS, had predictive value for short-term outcomes in patients with sepsis. The area under the ROC curve (AUC) was higher than that of the 4 indicators alone [AUC (95%CI): 0.952 (0.918-0.986) vs. 0.745 (0.670-0.820), 0.816 (0.748-0.883), 0.608 (0.518-0.699), 0.868 (0.810-0.927)], the sensitivity was 94.2%, and the specificity was 90.1%. APACHE II score within 24 hours, Lac, combined with hypertension, and concurrent MODS are independent risk factors for short-term mortality in adult septic patients in ICU. The combination of these indicators can make meaningful early clinical judgments on the short-term prognosis of septic patients, thereby reducing the mortality.

C-reactive protein-to-albumin ratio as a biomarker in patients with sepsis: a novel LASSO-COX based prognostic nomogram

To develop a C-reactive protein-to-albumin ratio (CAR)-based nomogram for predicting the risk of in-hospital death in sepsis patients. Sepsis patients were selected from the MIMIC-IV database. Independent predictors were determined by multiple Cox analysis and then integrated to predict survival. The performance of the model was evaluated using the concordance index (C-index), receiver operating characteristic curve (ROC) analysis, and calibration curve. The risk stratifications analysis and subgroup analysis of the model in overall survival (OS) were assessed by Kaplan–Meier (K–M) curves. A total of 6414 sepsis patients were included. C-index of the CAR-based model was 0.917 [standard error (SE): 0.112] for the training set and 0.935 (SE: 0.010) for the validation set. The ROC curve analysis showed that the area under the curve (AUC) of the nomogram was 0.881 in the training set and 0.801 in the validation set. And the calibration curve showed that the nomogram performs well in both the training and validation sets. K–M curves indicated that patients with high CAR had significantly higher in-hospital mortality than those with low CAR. The CAR-based model has considerably high accuracy for predicting the OS of sepsis patients.

Association between serum sodium and 28-day mortality in sepsis patients: A secondary data analysis from three large critical illness cohorts.

The present study was designed to explore the association between serum sodium and mortality in patients with sepsis by using a large sample, multicenter MIMIC-IV database. We extracted the data of 34 925 sepsis patients from the retrospective cohort mimicIV database. After adjusting the confounders, we explored the independent effects of serum sodium on 28-day mortality. A nonlinear relationship existed between serum sodium and 28-day mortality, of which a negative association was found between serum sodium and 28-day mortality (odds ratio: 0.95, 95% CI: 0.94, 0.96, p = 0.0001) when serum sodium was in 102 mmol/L to 138 mmol/L, but a positive correlation appeared when sodium climbed to the range of 140-179 mmol/L (odds ratio: 1.04, 95% CI: 1.03-1.06, p = 0.0001). Both lower and higher serum sodium levels are associated with an increased risk of death in sepsis patients.

Study on the value of fragmented red blood cell and fragmented red blood cells percentage for predicting the prognosis of sepsis patients

To explore the predictive efficacy of fragmented red blood cells (FRC) and fragmented red blood cells percentage(FRC%) with regarding for the prognosis of septic patients, along with comparing with routine coagulation parameters. A prospective study was conducted. A total of 101 patients with sepsis who met the requirements admitted to the Intensive Care Department of the Third Xiangya Hospital of Central South University from June 1, 2022 to January 10, 2023 were selected as the research objects, they were divided into survival group and death group according to the 30-day prognosis. The clinical data and laboratory indexes such as FRCs, FRC% and Platelet (PLT) were compared between the survival group and the death group. Univariate logistic regression analysis was used first, then multivariate logistic regression analysis was used to analyze the factors affecting the prognosis. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of each parameter in the regression model for the prognosis of sepsis. The results showed that the levels of FRCs, FRC%, prothrombin time (PT), activated partial thromboplastin time (APTT) and D-dimer in death group were significantly higher than those in survival group, and PLT in death group were significantly lower than those in survival group (Z or t values were -3.712,-3.793,-2.119,-2.007,-2.209,all P<0.05). FRCs or FRC% and PLT could be independent predictors of 30-day mortality. The area under the ROC curve (AUC) of PLT for predicting 30-day death in sepsis patients was 0.727 (95%CI 0.629-0.811, P<0.01), when the optimal threshold was 137 ×109/L, the sensitivity was 83.87% and the specificity was 57.14%. The AUC of FRCs for predicting 30-day death in sepsis patients was was 0.732 (95%CI 0.635-0.815, P<0.01), when the optimal threshold was 10.1×109/L, the sensitivity was 77.42%, and the specificity was 67.14%. The AUC of FRC% for predicting 30-day death in sepsis patients was 0.737 (95%CI 0.640-0.820, P<0.01), When the optimal threshold was 0.34%, the sensitivity was 77.42%, and the specificity was 65.71%. In conclusion,PLT, FRCs and FRC% have great application value in the prognosis of sepsis. When the PLT, FRCs and FRC% of sepsis patients are more than 137 ×109/L, 10.1×109/L and 0.34% respectively, it is necessary to take necessary and reasonable clinical intervention measures as soon as possible.

PaCO2 Levels at Admission Influence the Prognosis of Sepsis Patients: A Nonlinear Relationship

ABSTRACT Background: Sepsis is a life-threatening organ dysfunction caused by a maladjusted host response to infection (Sequential Organ Failure Assessment [SOFA] ≥ 2). PaCO2 is a blood gas that is commonly tested in hospitalized patients. Few studies have investigated how abnormal PaCO2 levels influence the prognosis of sepsis patients. Methods: A retrospective study was applied to data on sepsis patients extracted from the MIMIC-III public database and the results of their first PaCO2 examination after admission. The outcome measure was all-cause death within 90 days of follow-up. The patients were divided into five quintile groups, and the relationship between PaCO2 and all-cause death in sepsis patients was studied using restricted cubic splines (RCSs). Results: Our study included 4898 sepsis patients, the hypocapnia (PaCO2 &lt; 31 mmHg) and hypercapnia (PaCO2 ≥ 49 mmHg) groups were associated with the risk of death in sepsis patients using quintile grouping and the multivariate Cox model, with HRs of 1.12 (95% CI = 1.03–1.29) and 1.25 (95% CI = 1.10–1.41), respectively, when compared with the control group (37 ≤ PaCO2 &lt; 41 mmHg). The relationship between PaCO2 and all-cause death in sepsis patients was U-shaped. Conclusion: The presence of hypercapnia and hypocapnia at the time of hospital admission will have adverse effects on all-cause death in sepsis patients.

The PaO2/FiO2 is independently associated with 28-day mortality in patients with sepsis: a retrospective analysis from MIMIC-IV database

BackgroundTo clarify the relationship between the PaO2/FiO2 and 28-day mortality in patients with sepsis.MethodsThis was a retrospective cohort study regarding MIMIC-IV database. Nineteen thousand two hundred thirty-three patients with sepsis were included in the final analysis. PaO2/FiO2 was exposure variable, 28-day mortality was outcome variable. PaO2/FiO2 was log-transformed as LnPaO2/FiO2. Binary logistic regression was used to explore the independent effects of LnPaO2/FiO2 on 28-day mortality using non-adjusted and multivariate-adjusted models. A generalized additive model (GAM) and smoothed curve fitting was used to investigate the non-linear relationship between LnPaO2/FiO2 and 28-day mortality. A two-piecewise linear model was used to calculate the OR and 95% CI on either side of the inflection point.ResultsThe relationship between LnPaO2/FiO2 and risk of 28-day death in sepsis patients was U-shape. The inflection point of LnPaO2/FiO2 was 5.30 (95%CI: 5.21—5.39), which indicated the inflection point of PaO2/FiO2 was 200.33 mmHg (95%CI: 183.09 mmHg—219.20 mmHg). On the left of inflection point, LnPaO2/FiO2 was negatively correlated with 28-day mortality (OR: 0.37, 95%CI: 0.32—0.43, p < 0.0001). On the right of inflection point, LnPaO2/FiO2 was positively correlated with 28-day mortality in patients with sepsis (OR: 1.53, 95%CI: 1.31—1.80, p < 0.0001).ConclusionsIn patients with sepsis, either a high or low PaO2/FiO2 was associated with an increased risk of 28-day mortality. In the range of 183.09 mmHg to 219.20 mmHg, PaO2/FiO2 was associated with a lower risk of 28-day death in patients with sepsis.

Prognostic value of serum sodium variability within 72 hours and lactic acid combined with severity score in patients with sepsis

To explore the predictive value of serum sodium variability within 72 hours, lactic acid (Lac), sequential organ failure assessment (SOFA) and acute physiology and chronic health evaluation II (APACHE II) in predicting the 28-day prognosis of sepsis patients. The clinical data of patients with sepsis admitted to the department of intensive care unit (ICU) of the Affiliated Qingdao Municipal Hospital of Qingdao University from December 2020 to December 2021 were retrospectively analyzed, including age, gender, previous medical history, temperature, heart rate, respiratory rate, systolic pressure, diastolic pressure, white blood cell count (WBC), hemoglobin (Hb), platelet count (PLT), C-reactive protein (CRP), pH value, arterial partial pressure of oxygen (PaO2), arterial partial pressure of carbon dioxide (PaCO2), Lac, prothrombin time (PT), activated partial thromboplastin time (APTT), serum creatinine (SCr), total bilirubin (TBil), albumin (Alb), SOFA, APACHE II score, and 28-day prognosis. Multivariate Logistic regression was used to analyze the risk factors of death in sepsis patients. Receiver operator characteristic curve (ROC curve) was used to analyze the predictive value of serum sodium variability within 72 hours, Lac, SOFA, APACHE II alone and in combination on the prognosis of patients with sepsis. A total of 135 patients with sepsis were included, 73 survived and 62 died at 28 days, with 28-day mortality of 45.93%. (1) Compared with the survival group, SOFA, APACHE II, Lac and serum sodium variability within 72 hours in the death group were significantly higher [SOFA: 10.00 (8.00, 12.00) vs. 6.00 (5.00, 8.00), APACHE II: 18.00 (16.00, 21.25) vs. 13.00 (11.00, 15.00), Lac (mmol/L): 3.55 (2.90, 4.60) vs. 2.00 (1.30, 2.80), serum sodium variability within 72 hours: 3.4% (2.6%, 4.2%) vs. 1.4% (1.1%, 2.5%)], the differences were statistically significant (all P < 0.01). (2) Multivariate Logistic regression showed that SOFA, APACHE II, Lac, serum sodium variability within 72 hours were independent risk factors of prognosis in patients with sepsis [SOFA: odds ratio (OR) = 1.479, 95% confidence interval (95%CI) was 1.114-1.963, P = 0.007; APACHE II: OR = 1.163, 95%CI was 1.009-1.340, P = 0.037; Lac: OR = 1.387, 95%CI was 1.014-1.896, P = 0.040; serum sodium variability within 72 hours: OR = 1.634, 95%CI was 1.102-2.423, P = 0.015]. (3) ROC curve analysis showed that SOFA, APACHE II, Lac and serum sodium variability within 72 hours had certain predictive value for the prognosis of sepsis patients [SOFA: the area under the ROC curve (AUC) = 0.858, 95%CI was 0.795-0.920, P = 0.000; APACHE II: AUC = 0.845, 95%CI was 0.776-0.913, P = 0.000; Lac: AUC = 0.840, 95%CI was 0.770-0.909, P = 0.000; serum sodium variability within 72 hours: AUC = 0.842, 95%CI was 0.774-0.910, P = 0.000]. The combined predictive value of the four indicators (AUC = 0.917, 95%CI was 0.870-0.965, P = 0.000) was higher than that of any single indicator, and has higher specificity (79.5%) and sensitivity (93.5%), indicating that the combined index has higher predictive value for the prognosis of sepsis patients than any single index. SOFA, APACHE II, Lac, serum sodium variability within 72 hours are independent risk factors for 28-day death in patients with sepsis. The combination of SOFA score, APACHE II score, Lac and serum sodium variability within 72 hours has higher predictive value for prognosis than single index.

Association between base excess and 28-day mortality in sepsis patients: A secondary analysis based on the MIMIC- IV database

ObjectiveThe relationship between base excess (BE) and 28-day death in sepsis patients remains to be elucidated. The aim of our clinical study is to explore the association of BE with 28-day mortality in patients with sepsis by using a large sample, multicenter Medical Information Mart for Intensive Care IV (MIMIC-IV) database. MethodsWe extracted the data of 35,010 patients with sepsis from the MIMIC-IV database, in which we used BE as an exposure variable and the 28-day mortality as an outcome variable, respectively, so as to explore the impact of BE on the 28-day mortality of patients with sepsis after adjusting for covariates. ResultsBE and the 28-day mortality of patients with sepsis appeared to have a U-shaped relationship. The calculated inflection points were −2.5 mEq/L and 1.9 mEq/L, respectively. Our data demonstrated that BE was negatively associated with 28-day mortality in the range of −41.0 mEq/L to −2.5 mEq/L (odds ratio: 0.95; 95% confidence intervals (95%CI): 0.93 to 0.96), p < 0.0001. When BE was in the range of 1.9 mEq/L to 55.5 mEq/L, however, a positive association existed between BE and 28-day mortality of patients with sepsis (odds ratio: 1.03; 95% CI: 1.00 to 1.05; p < 0.05). ConclusionThe BE levels have a U-shaped relationship with the 28-day mortality in patients with sepsis, in which the mortality of patients will gradually decrease with a BE value from −41.0 mEq/L to −2.5 mEq/L, while the mortality will increase with a BE value from 1.9 mEq/L to 55.5 mEq/L.

Overexpressing six-transmembrane protein of prostate 2 (STAMP2) alleviates sepsis-induced acute lung injury probably by hindering M1 macrophage polarization via the NF-κB pathway.

Acute lung injury (ALI) is a major cause of death in sepsis patients. The Six-transmembrane protein of prostate 2 (STAMP2) is a key regulator of inflammation, while its role in septic ALI remains unclear. Male C57BL/6 mice were subjected to cecal ligation puncture (CLP) to induce experimental sepsis whereas lipopolysaccharide (LPS)-stimulated RAW 264.7 cells were used as the models of septic ALI in vivo and in vitro, respectively. Overexpression of STAMP2 in mouse lungs and RAW264.7 cells was performed with an adenoviral vector. We measured histological lung injury, lung wet/dry weight (W/D) ratio, and pulmonary myeloperoxidase (MPO) activity to assess lung injury extent. Cell counts in bronchoalveolar lavage fluid (BALF) were measured using Giemsa staining. The concentration of inflammatory factors was detected by enzyme-linked immunosorbent assay. The polarization of macrophages was evaluated by inducible nitric oxide synthase (iNOS) and F4/80 staining. The activation of cell apoptosis and NF-κB pathway was evaluated using Western blot, TUNEL staining, immunofluorescence, and immunohistochemistry. Overexpression of STAMP2 alleviated CLP-induced lung injury of mice with decreased W/D ratio of the lung, and MPO activity in lung tissue. STAMP2 overexpression reduced the lung infiltration of inflammatory cells, and the levels of TNF-a, IL-6, and macrophage chemoattractant protein-1 (MCP-1) in BALF. Overexpressed STAMP2 inhibited macrophage M1 polarization in lung tissues as indicated by F4/80 and iNOS stainings in lung tissue. STAMP2 overexpression inhibited RAW 264.7 cell apoptosis by increasing Bcl-2 and decreasing Bax and cleaved-caspase 3 expression. Besides, STAMP2 overexpression suppressed nuclear factor κB (NF-κB) p65 pathway activation, as evidenced by reduced phosphorylation of IκBα, and phosphorylation and translocation of NF-κB p65. In vitro study further proved that STAMP2 overexpression suppressed the NF-κB pathway (IκBα/p65) in macrophages and decreased macrophage M1 polarization and M1-associated inflammatory factor production (TNF-a, IL-6, and MCP-1). Our study for the first time demonstrated that STAMP2 might be able to reduce inflammation in sepsis-induced ALI by inhibiting macrophage M1 polarization through repressing NF-κB signaling activation.

A prediction model for predicting the risk of acute respiratory distress syndrome in sepsis patients: a retrospective cohort study

BackgroundThe risk of death in sepsis patients with acute respiratory distress syndrome (ARDS) was as high as 20–50%. Few studies focused on the risk identification of ARDS among sepsis patients. This study aimed to develop and validate a nomogram to predict the ARDS risk in sepsis patients based on the Medical Information Mart for Intensive Care IV database.MethodsA total of 16,523 sepsis patients were included and randomly divided into the training and testing sets with a ratio of 7:3 in this retrospective cohort study. The outcomes were defined as the occurrence of ARDS for ICU patients with sepsis. Univariate and multivariate logistic regression analyses were used in the training set to identify the factors that were associated with ARDS risk, which were adopted to establish the nomogram. The receiver operating characteristic and calibration curves were used to assess the predictive performance of nomogram.ResultsTotally 2422 (20.66%) sepsis patients occurred ARDS, with the median follow-up time of 8.47 (5.20, 16.20) days. The results found that body mass index, respiratory rate, urine output, partial pressure of carbon dioxide, blood urea nitrogen, vasopressin, continuous renal replacement therapy, ventilation status, chronic pulmonary disease, malignant cancer, liver disease, septic shock and pancreatitis might be predictors. The area under the curve of developed model were 0.811 (95% CI 0.802–0.820) in the training set and 0.812 (95% CI 0.798–0.826) in the testing set. The calibration curve showed a good concordance between the predicted and observed ARDS among sepsis patients.ConclusionWe developed a model incorporating thirteen clinical features to predict the ARDS risk in patients with sepsis. The model showed a good predictive ability by internal validation.

Gut microbiota involved in myocardial dysfunction induced by sepsis

Myocardial dysfunction is an important complication of sepsis and an important cause of death in sepsis patients. Sepsis will significantly change the composition of gut microbiota, and the destruction of gut microbiota also creates conditions for the occurrence and progression of sepsis. Gut microbiota is an important player in myocardial injury in sepsis. This review elaborates on the possible mechanisms of gut microbiota affecting myocardial injury in sepsis, including short-chain fatty acids, trimethylamine and trimethylamine oxides, various cytokines, and mitochondrial dysfunction. A better understanding of the mechanism could help improve the treatment of sepsis and get a better prognosis for sepsis patients.

Efficacy of Pretreatment with Lycium barbarum Polysaccharide in Various Doses in Influencing Splenic Immunity and Prognosis of Sepsis in Rats.

Objective Sepsis, showing high mortality, is a lethal dysfunction of organs caused by an infection-induced disorder in the host response. It has complicated pathogenesis, which has not yet been elucidated completely. Recently, the principal factors causing pathogenesis and even death in sepsis patients are imbalance in inflammatory response and immunosuppression occurring when the host is challenged by infection. Previous studies found that Lycium barbarum polysaccharide (LBP) worked well in enhancing immunity. This study aims at exploring the efficacy of pretreatment with LPB in regulating splenic immunity during the pathogenesis of sepsis induced by cecum ligation perforation (CLP) in rats. Methods This research established the cecum ligation perforation rat model. Using immunohistochemistry and flow cytometry, the effects of Lycium barbarum polysaccharide in various doses in influencing splenic immunity and prognosis of sepsis induced by cecum ligation perforation in rats were examined. Results This study showed that LBP lowered the 72-hour mortality of sepsis rats induced by CLP, relieved systemic inflammation, improved the ratio of T-cell subgroups positive in CD3+, CD4+, or CD8+ and expression of HLA-DR protein, and repaired damage to splenic tissue, implying its efficacy in enhancing the immunity of sepsis rats induced by CLP. Conclusions LBP may ameliorate clinical symptoms of rats with cecum ligation perforation, improve cellular immunity in the spleen, and treat sepsis so as to provide a theoretical basis for the pathogenesis and development of sepsis as well as its diagnosis and treatment, and offer scientific proof for the development and utilization of LBP applied to critical diseases.

Diagnostic and Prognostic Value of Interleukin-6 in Emergency Department Sepsis Patients.

PurposeThe objective of this study was to explore the diagnostic and prognostic value of interleukin-6 (IL-6) in sepsis patients presenting to the emergency department.Patients and MethodsA total of 128 patients who visited the emergency department of West Hospital of Beijing Chaoyang Hospital, affiliated to Capital Medical University, from November 2021 to February 2022 were subjected to this study. According to Sepsis-3.0 diagnostic criteria for sepsis, patients were divided into non-sepsis group (65 cases) and sepsis group (63 cases). Demographic data and clinical characteristics of the two patient groups were compared. Serum levels of biomarkers including IL-6, blood urea nitrogen (BUN), and lactic acid (Lac) were compared with Sequential Organ Failure Assessment (SOFA) and Glasgow Coma Scale (GCS) scores. Logistic regression was used to analyze independent risk factors and Receiver Operating Characteristic Curve (ROC) method was used to analyze the Area Under the Curve (AUC) to determine the diagnostic and prognostic value of markers.ResultsCompared with non-sepsis patients, levels of IL-6, PCT, CRP and BUN were significantly higher in sepsis patients (10.84 (4.41–27.01): 92.22 (21.53–201.12), 0.03 (0.01–0.1):0.49 (0.08–3.1), 8.3 (0.5–31.8):39.8(10.3–98.6), 7.01 (4.90–11.74):13.03 (6.93–25.99), all p = 0.001). IL-6, BUN and mean arterial pressure (MAP) were independent risk factors for sepsis diagnosis. AUC values of IL-6, BUN, MAP and IL-6+BUN+MAP were 0.764, 0.696, 0.685, and 0.848, respectively. Lactate, age and SOFA score were independent risk factors for 28-day mortality in sepsis patients. The AUC of Lac, age, SOFA score and Lac+age+SOFA score to predict 28-day death in sepsis patients was 0.679, 0.626, 0.747, and 0.819, respectively.ConclusionIL-6 is an independent predictor of sepsis diagnosis, and the combination of blood BUN and MAP has superior diagnostic performance. Lac, age, and SOFA score could effectively predict clinical outcomes in patients with sepsis.