A machine learning model for the early diagnosis of bloodstream infection in patients admitted to the pediatric intensive care unit.

Bloodstream infection (BSI) is associated with increased morbidity and mortality in the pediatric intensive care unit (PICU) and high healthcare costs. Early detection and appropriate treatment of BSI may improve patient's outcome. Data on machine-learning models to predict BSI in pediatric patients are limited and neither study included time series data. We aimed to develop a machine learning model to predict an early diagnosis of BSI in patients admitted to the PICU. This was a retrospective cohort study of patients who had at least one positive blood culture result during stay at a PICU of a tertiary-care university hospital, from January 1st to December 31st 2019. Patients with positive blood culture results with growth of contaminants and those with incomplete data were excluded. Models were developed using demographic, clinical and laboratory data collected from the electronic medical record. Laboratory data (complete blood cell counts with differential and C-reactive protein) and vital signs (heart rate, respiratory rate, blood pressure, temperature, oxygen saturation) were obtained 72 hours before and on the day of blood culture collection. A total of 8816 data from 76 patients were processed by the models. The machine committee was the best-performing model, showing accuracy of 99.33%, precision of 98.89%, sensitivity of 100% and specificity of 98.46%. Hence, we developed a model using demographic, clinical and laboratory data collected on a routine basis that was able to detect BSI with excellent accuracy and precision, and high sensitivity and specificity. The inclusion of vital signs and laboratory data variation over time allowed the model to identify temporal changes that could be suggestive of the diagnosis of BSI. Our model might help the medical team in clinical-decision making by creating an alert in the electronic medical record, which may allow early antimicrobial initiation and better outcomes.

The prognostic value of platelet aggregation in patients with sepsis.

BACKGROUND: This study aims to investigate the relevance of platelet aggregation markers, specifically arachidonic acid (AA) and adenosine diphosphate (ADP), in relation to the prognosis of sepsis patients. METHODS: A cohort of 40 sepsis patients was included and stratified, based on their 28-day post-treatment prognosis, into two groups: a survival group (n = 31) and a severe sepsis group (n = 9. Then, their various clinical parameters, including patient demographics, platelet counts (PLT), inflammatory markers, and platelet aggregation rates (PAR) induced by AA and ADP between the two groups, were compared. Long-term health implications of sepsis were assessed using the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) score, and logistic regression analysis was conducted to evaluate the prognostic significance of PAR in sepsis patients. RESULTS: Patients with severe sepsis exhibited significantly elevated levels of procalcitonin (PCT), platelet adhesion rates, and PAR induced by ADP (P < 0.05), but having lower PLT (P < 0.05), compared to those in the survival group. Logistic regression analysis demonstrated that PAR induced by ADP was a protective factor in predicting prognosis in sepsis patients (P < 0.01). CONCLUSIONS: Activation of platelets in sepsis intensifies inflammatory response. Patients with sepsis whose ADP-induced PAR was < 60% displayed significant impairment in platelet aggregation function, and had higher mortality rate. Monitoring ADP-induced PAR is crucial for management of sepsis.

Identification of sepsis-associated mitochondrial genes through RNA and single-cell sequencing approaches.

BACKGROUND: Sepsis ranks among the most formidable clinical challenges, characterized by exorbitant treatment costs and substantial demands on healthcare resources. Mitochondrial dysfunction emerges as a pivotal risk factor in the pathogenesis of sepsis, underscoring the imperative to identify mitochondrial-related biomarkers. Such biomarkers are crucial for enhancing the accuracy of sepsis diagnostics and prognostication. METHODS: In this study, adhering to the SEPSIS 3.0 criteria, we collected peripheral blood within 24 h of admission from 20 sepsis patients at the ICU of the Southwest Medical University Affiliated Hospital and 10 healthy volunteers as a control group for RNA-seq. The RNA-seq data were utilized to identify differentially expressed RNAs. Concurrently, mitochondrial-associated genes (MiAGs) were retrieved from the MitoCarta3.0 database. The differentially expressed genes were intersected with MiAGs. The intersected genes were then subjected to GO (Gene Ontology), and KEGG (Kyoto Encyclopedia of Genes and Genomes) analyses and core genes were filtered using the PPI (Protein-Protein Interaction) network. Subsequently, relevant sepsis datasets (GSE65682, GSE28750, GSE54514, GSE67652, GSE69528, GSE95233) were downloaded from the GEO (Gene Expression Omnibus) database to perform bioinformatic validation of these core genes. Survival analysis was conducted to assess the prognostic value of the core genes, while ROC (Receiver Operating Characteristic) curves determined their diagnostic value, and a meta-analysis confirmed the accuracy of the RNA-seq data. Finally, we collected 5 blood samples (2 normal controls (NC); 2 sepsis; 1 SIRS (Systemic Inflammatory Response Syndrome), and used single-cell sequencing to assess the expression levels of the core genes in the different blood cell types. RESULTS: Integrating high-throughput sequencing with bioinformatics, this study identified two mitochondrial genes (COX7B, NDUFA4) closely linked with sepsis prognosis. Survival analysis demonstrated that patients with lower expression levels of COX7B and NDUFA4 exhibited a higher day survival rate over 28 days, inversely correlating with sepsis mortality. ROC curves highlighted the significant sensitivity and specificity of both genes, with AUC values of 0.985 for COX7B and 0.988 for NDUFA4, respectively. Meta-analysis indicated significant overexpression of COX7B and NDUFA4 in the sepsis group in contrast to the normal group (P < 0.01). Additionally, single-cell RNA sequencing revealed predominant expression of these core genes in monocytes-macrophages, T cells, and B cells. CONCLUSION: The mitochondrial-associated genes (MiAGs) COX7B and NDUFA4 are intimately linked with the prognosis of sepsis, offering potential guidance for research into the mechanisms underlying sepsis.

Association between the stress hyperglycemia ratio and 28-day all-cause mortality in critically ill patients with sepsis: a retrospective cohort study and predictive model establishment based on machine learning.

BACKGROUND: Sepsis is a severe form of systemic inflammatory response syndrome that is caused by infection. Sepsis is characterized by a marked state of stress, which manifests as nonspecific physiological and metabolic changes in response to the disease. Previous studies have indicated that the stress hyperglycemia ratio (SHR) can serve as a reliable predictor of adverse outcomes in various cardiovascular and cerebrovascular diseases. However, there is limited research on the relationship between the SHR and adverse outcomes in patients with infectious diseases, particularly in critically ill patients with sepsis. Therefore, this study aimed to explore the association between the SHR and adverse outcomes in critically ill patients with sepsis. METHODS: Clinical data from 2312 critically ill patients with sepsis were extracted from the MIMIC-IV (2.2) database. Based on the quartiles of the SHR, the study population was divided into four groups. The primary outcome was 28-day all-cause mortality, and the secondary outcome was in-hospital mortality. The relationship between the SHR and adverse outcomes was explored using restricted cubic splines, Cox proportional hazard regression, and Kaplan‒Meier curves. The predictive ability of the SHR was assessed using the Boruta algorithm, and a prediction model was established using machine learning algorithms. RESULTS: Data from 2312 patients who were diagnosed with sepsis were analyzed. Restricted cubic splines demonstrated a "U-shaped" association between the SHR and survival rate, indicating that an increase in the SHR is related to an increased risk of adverse events. A higher SHR was significantly associated with an increased risk of 28-day mortality and in-hospital mortality in patients with sepsis (HR > 1, P < 0.05) compared to a lower SHR. Boruta feature selection showed that SHR had a higher Z score, and the model built using the rsf algorithm showed the best performance (AUC = 0.8322). CONCLUSION: The SHR exhibited a U-shaped relationship with 28-day all-cause mortality and in-hospital mortality in critically ill patients with sepsis. A high SHR is significantly correlated with an increased risk of adverse events, thus indicating that is a potential predictor of adverse outcomes in patients with sepsis.

The role of platelets in central hubs of inflammation: A literature review.

Platelets are increasingly recognized for their multifaceted roles in inflammation beyond their traditional involvement in haemostasis. This review consolidates knowledge on platelets as critical players in inflammatory responses. This study did an extensive search of electronic databases and identified studies on platelets in inflammation, focusing on molecular mechanisms, cell interactions, and clinical implications, emphasizing recent publications. Platelets contribute to inflammation via surface receptors, release of mediators, and participation in neutrophil extracellular trap formation. They are implicated in diseases like atherosclerosis, rheumatoid arthritis, and sepsis, highlighting their interaction with immune cells as pivotal in the onset and resolution of inflammation. Platelets are central to regulating inflammation, offering new therapeutic targets for inflammatory diseases. Future research should explore specific molecular pathways of platelets in inflammation for therapeutic intervention.

Blood calprotectin as a biomarker for infection and sepsis - the prospective CASCADE trial.

BACKGROUND: Early in the host-response to infection, neutrophils release calprotectin, triggering several immune signalling cascades. In acute infection management, identifying infected patients and stratifying these by risk of deterioration into sepsis, are crucial tasks. Recruiting a heterogenous population of patients with suspected infections from the emergency department, early in the care-path, the CASCADE trial aimed to evaluate the accuracy of blood calprotectin for detecting bacterial infections, estimating disease severity, and predicting clinical deterioration. METHODS: In a prospective, observational trial from February 2021 to August 2022, 395 patients (n = 194 clinically suspected infection; n = 201 controls) were enrolled. Blood samples were collected at enrolment. The accuracy of calprotectin to identify bacterial infections, and to predict and identify sepsis and mortality was analysed. These endpoints were determined by a panel of experts. RESULTS: The Area Under the Receiver Operating Characteristic (AUROC) of calprotectin for detecting bacterial infections was 0.90. For sepsis within 72 h, calprotectin's AUROC was 0.83. For 30-day mortality it was 0.78. In patients with diabetes, calprotectin had an AUROC of 0.94 for identifying bacterial infection. CONCLUSIONS: Calprotectin showed notable accuracy for all endpoints. Using calprotectin in the emergency department could improve diagnosis and management of severe infections, in combination with current biomarkers. CLINICAL TRIAL REGISTRATION NUMBER: DRKS00020521.

Diagnostic and Prognostic Value of C1q in Sepsis-Induced Coagulopathy.

Early identification of biomarkers that can predict the onset of sepsis-induced coagulopathy (SIC) in septic patients is clinically important. This study endeavors to examine the diagnostic and prognostic utility of serum C1q in the context of SIC. Clinical data from 279 patients diagnosed with sepsis at the Departments of Intensive Care, Respiratory Intensive Care, and Infectious Diseases at the Renmin Hospital of Wuhan University were gathered spanning from January 2022 to January 2024. These patients were categorized into two groups: the SIC group comprising 108 cases and the non-SIC group consisting of 171 cases, based on the presence of SIC. Within the SIC group, patients were further subdivided into a survival group (43 cases) and non-survival group (65 cases). The concentration of serum C1q in the SIC group was significantly lower than that in the non-SIC group. Furthermore, A significant correlation was observed between serum C1q levels and both SIC score and coagulation indices. C1q demonstrated superior diagnostic and prognostic performance for SIC patients, as indicated by a higher area under the curve (AUC). Notably, when combined with CRP, PCT, and SOFA score, C1q displayed the most robust diagnostic efficacy for SIC. Moreover, the combination of C1q with the SOFA score heightened predictive value concerning the 28-day mortality of SIC patients.

Lactate dynamics in paediatric patients with severe sepsis: insights from a prospective cohort study.

BACKGROUND: Sepsis is an infection-related systemic inflammatory response that often leads to elevated lactate levels. Monitoring lactate levels during severe sepsis is vital for influencing clinical outcomes. The aim of this study was to assess the association between plasma lactate levels and mortality in children with severe sepsis or septic shock. METHODS: The current prospective study was conducted in the PICU of University Children's Hospital. The International Paediatric Sepsis Consensus Conference criteria for Definitions of Sepsis and Organ Failure in 2005 were used to diagnose patients with sepsis. We measured plasma lactate levels upon admission (Lac H0) and 6 h later (Lac H6). The static indices included the absolute lactate values (Lac H0 and Lac H6), while the dynamic indices included the delta-lactate level (ΔLac) and the 6-hour lactate clearance. The 6-hour lactate clearance was calculated using the following formula: [(Lac H0-Lac H6)100/Lac H0]. ΔLac was calculated as the difference between the Lac H0 and Lac H6 levels. Patient survival or death after a PICU stay was the primary outcome. RESULTS: A total of 46 patients were included in this study: 25 had septic shock, and 21 had severe sepsis. The mortality rate was 54.3%. The Lac H0 did not significantly differ between survivors and nonsurvivors. In contrast, the survivors had significantly lower Lac H6 levels, higher ΔLac levels, and higher 6-hour lactate clearance rates than nonsurvivors. Lactate clearance rates below 10%, 20%, and 30% were significantly associated with mortality. The best cut-off values for the lactate clearance rate and Lac H6 for the prediction of mortality in the PICU were < 10% and ≥ 4 mmol/L, respectively. Patients with higher Lac H6 levels and lower lactate clearance rates had significantly higher PICU mortality based on Kaplan-Meier survival curve analysis. CONCLUSIONS: This study highlights the significance of lactate level trends over time for the prediction of mortality in the PICU in patients with severe sepsis or septic shock. Elevated lactate levels and decreased lactate clearance six hours after hospitalisation are associated with a higher mortality rate.

Mendelian randomization analysis reveals causal associations of serum metabolites with sepsis and 28-day mortality.

Metabolic disorder has been found to be an important factor in the pathogenesis and progression of sepsis. However, the causation of such an association between serum metabolites and sepsis has not been established. We conducted a two-sample Mendelian randomization (MR) study. A genome-wide association study of 486 human serum metabolites was used as the exposure, whereas sepsis and sepsis mortality within 28 days were set as the outcomes. In MR analysis, 6 serum metabolites were identified to be associated with an increased risk of sepsis, and 6 serum metabolites were found to be related to a reduced risk of sepsis. Furthermore, there were 9 metabolites positively associated with sepsis-related mortality, and 8 metabolites were negatively correlated with sepsis mortality. In addition, "glycolysis/gluconeogenesis" (p = 0.001), and "pyruvate metabolism" (p = 0.042) two metabolic pathways were associated with the incidence of sepsis. This MR study suggested that serum metabolites played significant roles in the pathogenesis of sepsis, which may provide helpful biomarkers for early disease diagnosis, therapeutic interventions, and prognostic assessments for sepsis.

Machine learning derived serum creatinine trajectories in acute kidney injury in critically ill patients with sepsis.

BACKGROUND: Current classification for acute kidney injury (AKI) in critically ill patients with sepsis relies only on its severity-measured by maximum creatinine which overlooks inherent complexities and longitudinal evaluation of this heterogenous syndrome. The role of classification of AKI based on early creatinine trajectories is unclear. METHODS: This retrospective study identified patients with Sepsis-3 who developed AKI within 48-h of intensive care unit admission using Medical Information Mart for Intensive Care-IV database. We used latent class mixed modelling to identify early creatinine trajectory-based classes of AKI in critically ill patients with sepsis. Our primary outcome was development of acute kidney disease (AKD). Secondary outcomes were composite of AKD or all-cause in-hospital mortality by day 7, and AKD or all-cause in-hospital mortality by hospital discharge. We used multivariable regression to assess impact of creatinine trajectory-based classification on outcomes, and eICU database for external validation. RESULTS: Among 4197 patients with AKI in critically ill patients with sepsis, we identified eight creatinine trajectory-based classes with distinct characteristics. Compared to the class with transient AKI, the class that showed severe AKI with mild improvement but persistence had highest adjusted risks for developing AKD (OR 5.16; 95% CI 2.87-9.24) and composite 7-day outcome (HR 4.51; 95% CI 2.69-7.56). The class that demonstrated late mild AKI with persistence and worsening had highest risks for developing composite hospital discharge outcome (HR 2.04; 95% CI 1.41-2.94). These associations were similar on external validation. CONCLUSIONS: These 8 classes of AKI in critically ill patients with sepsis, stratified by early creatinine trajectories, were good predictors for key outcomes in patients with AKI in critically ill patients with sepsis independent of their AKI staging.

The beneficial effects of neutrophil elastase inhibitor on gastrointestinal dysfunction in sepsis.

To investigate the effects of neutrophil elastase inhibitor (sivelestat sodium) on gastrointestinal function in sepsis. A reanalysis of the data from previous clinical trials conducted at our center was performed. Septic patients were divided into either the sivelestat group or the non-sivelestat group. The gastrointestinal dysfunction score (GIDS), feeding intolerance (FI) incidence, serum levels of intestinal barrier function and inflammatory biomarkers were recorded. The clinical severity and outcome variables were also documented. A total of 163 septic patients were included. The proportion of patients with GIDS ≥2 in the sivelestat group was reduced relative to that in the non-sivelestat group (9.6% vs. 22.5%, p = 0.047) on the 7th day of intensive care unit (ICU) admission. The FI incidence was also remarkably reduced in the sivelestat group in contrast to that in the non-sivelestat group (21.2% vs. 37.8%, p = 0.034). Furthermore, the sivelestat group had fewer days of FI [4 (3, 4) vs. 5 (4-6), p = 0.008]. The serum levels of d-lactate (p = 0.033), intestinal fatty acid-binding protein (p = 0.005), interleukin-6 (p = 0.001), white blood cells (p = 0.007), C-reactive protein (p = 0.001), and procalcitonin (p < 0.001) of the sivelestat group were lower than those of the non-sivelestat group. The sivelestat group also demonstrated longer ICU-free days [18 (0-22) vs. 13 (0-17), p = 0.004] and ventilator-free days [22 (1-24) vs. 16 (1-19), p = 0.002] compared with the non-sivelestat group. In conclusion, sivelestat sodium administration appears to improve gastrointestinal dysfunction, mitigate dysregulated inflammation, and reduce disease severity in septic patients.

Cell-free DNA in patients with sepsis: long term trajectory and association with 28-day mortality and sepsis-associated acute kidney injury.

Introduction: Outcome-prediction in patients with sepsis is challenging and currently relies on the serial measurement of many parameters. Standard diagnostic tools, such as serum creatinine (SCr), lack sensitivity and specificity for acute kidney injury (AKI). Circulating cell-free DNA (cfDNA), which can be obtained from liquid biopsies, can potentially contribute to the quantification of tissue damage and the prediction of sepsis mortality and sepsis-associated AKI (SA-AKI). Methods: We investigated the clinical significance of cfDNA levels as a predictor of 28-day mortality, the occurrence of SA-AKI and the initiation of renal replacement therapy (RRT) in patients with sepsis. Furthermore, we investigated the long-term course of cfDNA levels in sepsis survivors at 6 and 12 months after sepsis onset. Specifically, we measured mitochondrial DNA (mitochondrially encoded NADH-ubiquinone oxidoreductase chain 1, mt-ND1, and mitochondrially encoded cytochrome C oxidase subunit III, mt-CO3) and nuclear DNA (nuclear ribosomal protein S18, n-Rps18) in 81 healthy controls and all available samples of 150 intensive care unit patients with sepsis obtained at 3 ± 1 days, 7 ± 1 days, 6 ± 2 months and 12 ± 2 months after sepsis onset. Results: Our analysis revealed that, at day 3, patients with sepsis had elevated levels of cfDNA (mt-ND1, and n-Rps18, all p<0.001) which decreased after the acute phase of sepsis. 28-day non-survivors of sepsis (16%) had higher levels of cfDNA (all p<0.05) compared with 28-day survivors (84%). Patients with SA-AKI had higher levels of cfDNA compared to patients without AKI (all p<0.05). Cell-free DNA was also significantly increased in patients requiring RRT (all p<0.05). All parameters improved the AUC for SCr in predicting RRT (AUC=0.88) as well as APACHE II in predicting mortality (AUC=0.86). Conclusion: In summary, cfDNA could potentially improve risk prediction models for mortality, SA-AKI and RRT in patients with sepsis. The predictive value of cfDNA, even with a single measurement at the onset of sepsis, could offer a significant advantage over conventional diagnostic methods that require repeated measurements or a baseline value for risk assessment. Considering that our data show that cfDNA levels decrease after the first insult, future studies could investigate cfDNA as a "memoryless" marker and thus bring further innovation to the complex field of SA-AKI diagnostics.

[Research progress of diagnostic and therapeutic value of carbon dioxide-derived indicators in patients with sepsis].

Effectively assessing oxygen delivery and demand is one of the key targets for fluid resuscitation in sepsis. Clinical signs and symptoms, blood lactic acid levels, and mixed venous oxygen saturation (SvO2) or central venous oxygen saturation (ScvO2) all have their limitations. In recent years, these limitations have been overcome through the use of derived indicators from carbon dioxide (CO2) such as mixed veno-arterial carbon dioxide partial pressure difference (Pv-aCO2, PCO2 gap, or ΔPCO2), the ratio of mixed veno-arterial carbon dioxide partial pressure difference to arterial-mixed venous oxygen content difference (Pv-aCO2/Ca-vO2). Pv-aCO2, PCO2 gap or ΔPCO2 is not a purely anaerobic metabolism indicator as it is influenced by oxygen consumption. However, it reliably indicates whether blood flow is sufficient to carry CO2 from peripheral tissues to the lungs for clearance, thus reflecting the adequacy of cardiac output and metabolism. The Pv-aCO2/Ca-vO2 may serve as a marker of hypoxia. SvO2 and ScvO2 represent venous oxygen saturation, reflecting tissue oxygen utilization. When oxygen delivery decreases but tissues still require more oxygen, oxygen extraction rate usually increases to meet tissue demands, resulting in decreased SvO2 and ScvO2. But in some cases, even if the oxygen delivery rate and tissue utilization rate of oxygen are reduced, it may still lead to a decrease in SvO2 and ScvO2. Sepsis is a classic example where tissue oxygen utilization decreases due to factors such as microcirculatory dysfunction, even when oxygen delivery is sufficient, leading to decrease in SvO2 and ScvO2. Additionally, the solubility of CO2 in plasma is approximately 20 times that of oxygen. Therefore, during sepsis or septic shock, derived variables of CO2 may serve as sensitive markers for monitoring tissue perfusion and microcirculatory hemodynamics. Its main advantage over blood lactic acid is its ability to rapidly change and provide real-time monitoring of tissue hypoxia. This review aims to demonstrate the principles of CO2-derived variables in sepsis, assess the available techniques for evaluating CO2-derived variables during the sepsis process, and discuss their clinical relevance.

Prussian Blue Analogues-Derived Molecularly Imprinted Nanozyme Array for Septicemia Detection.

Septicemia, a severe bacterial infection, poses significant risks to human health. Early detection of septicemia by tracking specific biomarkers is crucial for a timely intervention. Herein, we developed a molecularly imprinted (MI) TiO2-Fe-CeO2 nanozyme array derived from Ce[Fe(CN)6] Prussian blue analogues (PBA), specifically targeting valine, leucine, and isoleucine, as potential indicators of septicemia. The synthesized nanozyme arrays were thoroughly characterized using various analytical techniques, including Fourier transform infrared spectroscopy, X-ray diffraction, field-emission scanning electron microscope, and energy-dispersive X-ray. The results confirmed their desirable physical and chemical properties, indicating their suitability for the oxidation of 3,3',5,5'-tetramethylbenzidine serving as a colorimetric probe in the presence of a persulfate oxidizing agent, further highlighting the potential of these arrays for sensitive and accurate detection applications. The MITiO2 shell selectively captures valine, leucine, and isoleucine, partially blocking the cavities for substrate access and thereby hindering the catalyzed TMB chromogenic reaction. The nanozyme array demonstrated excellent performance with linear detection ranges of 5 µM to 1 mM, 10-450 µM, and 10-450 µM for valine, leucine, and isoleucine, respectively. Notably, the corresponding limit of detection values were 0.69, 1.46, and 2.76 µM, respectively. The colorimetric assay exhibited outstanding selectivity, reproducibility, and performance in the detection of analytes in blood samples, including C-reactive protein at a concentration of 61 mg/L, procalcitonin at 870 ng/dL, and the presence of Pseudomonas aeruginosa bacteria. The utilization of Ce[Fe(CN)6]-derived MITiO2-Fe-CeO2 nanozyme arrays holds considerable potential in the field of septicemia detection. This approach offers a sensitive and specific method for early diagnosis and intervention, thereby contributing to improved patient outcomes.

Comparison between XGboost model and logistic regression model for predicting sepsis after extremely severe burns.

OBJECTIVE: To compare an Extreme Gradient Boosting (XGboost) model with a multivariable logistic regression (LR) model for their ability to predict sepsis after extremely severe burns. METHODS: For this observational study, patient demographic and clinical information were collected from medical records. The two models were evaluated using area under curve (AUC) of the receiver operating characteristic (ROC) curve. RESULTS: Of the 103 eligible patients with extremely severe burns, 20 (19%) were in the sepsis group, and 83 (81%) in the non-sepsis group. The LR model showed that age, admission time, body index (BI), fibrinogen, and neutrophil to lymphocyte ratio (NLR) were risk factors for sepsis. Comparing AUC of the ROC curves, the XGboost model had a higher predictive performance (0.91) than the LR model (0.88). The SHAP visualization tool indicated fibrinogen, NLR, BI, and age were important features of sepsis in patients with extremely severe burns. CONCLUSIONS: The XGboost model was superior to the LR model in predictive efficacy. Results suggest that, fibrinogen, NLR, BI, and age were correlated with sepsis after extremely severe burns.

Gene expression signatures in blood from a West African sepsis cohort define host response phenotypes.

Our limited understanding of the pathophysiological mechanisms that operate during sepsis is an obstacle to rational treatment and clinical trial design. There is a critical lack of data from low- and middle-income countries where the sepsis burden is increased which inhibits generalized strategies for therapeutic intervention. Here we perform RNA sequencing of whole blood to investigate longitudinal host response to sepsis in a Ghanaian cohort. Data dimensional reduction reveals dynamic gene expression patterns that describe cell type-specific molecular phenotypes including a dysregulated myeloid compartment shared between sepsis and COVID-19. The gene expression signatures reported here define a landscape of host response to sepsis that supports interventions via targeting immunophenotypes to improve outcomes.

The association of arterial partial oxygen pressure with mortality in critically ill sepsis patients: a nationwide observational cohort study.

BACKGROUND: Although several trials were conducted to optimize the oxygenation range in intensive care unit (ICU) patients, no studies have yet reached a universal recommendation on the optimal a partial pressure of oxygen in arterial blood (PaO2) range in patients with sepsis. Our aim was to evaluate whether a relatively high arterial oxygen tension is associated with longer survival in sepsis patients compared with conservative arterial oxygen tension. METHODS: From the Korean Sepsis Alliance nationwide registry, patients treated with liberal PaO2 (PaO2 ≥ 80 mm Hg) were 1:1 matched with those treated with conservative PaO2 (PaO2 < 80 mm Hg) over the first three days after ICU admission according to the propensity score. The primary outcome was 28-day mortality. RESULTS: The median values of PaO2 over the first three ICU days in 1211 liberal and 1211 conservative PaO2 groups were, respectively, 107.2 (92.0-134.0) and 84.4 (71.2-112.0) in day 1110.0 (93.4-132.0) and 80.0 (71.0-100.0) in day 2, and 106.0 (91.9-127.4) and 78.0 (69.0-94.5) in day 3 (all p-values < 0.001). The liberal PaO2 group showed a lower likelihood of death at day 28 (14.9%; hazard ratio [HR], 0.79; 95% confidence interval [CI] 0.65-0.96; p-value = 0.017). ICU (HR, 0.80; 95% CI 0.67-0.96; p-value = 0.019) and hospital mortalities (HR, 0.84; 95% CI 0.73-0.97; p-value = 0.020) were lower in the liberal PaO2 group. On ICU days 2 (p-value = 0.007) and 3 (p-value < 0.001), but not ICU day 1, hyperoxia was associated with better prognosis compared with conservative oxygenation., with the lowest 28-day mortality, especially at PaO2 of around 100 mm Hg. CONCLUSIONS: In critically ill patients with sepsis, higher PaO2 (≥ 80 mm Hg) during the first three ICU days was associated with a lower 28-day mortality compared with conservative PaO2.

Soluble Neuropilin-1 Is Elevated in Sepsis and Correlates with Organ Dysfunction and Long-Term Mortality in Critical Illness.

Critical illness and sepsis may cause organ failure and are recognized as mortality drivers in hospitalized patients. Neuropilin-1 (NRP-1) is a multifaceted transmembrane protein involved in the primary immune response and is expressed in immune cells such as T and dendritic cells. The soluble form of NRP-1 (sNRP-1) acts as an antagonist to NRP-1 by scavenging its ligands. The aim of this study was to determine the value of sNRP-1 as a biomarker in critical illness and sepsis. We enrolled 180 critically ill patients admitted to a medical intensive care unit and measured serum sNRP-1 concentrations at admission, comparing them to 48 healthy individuals. Critically ill and septic patients showed higher levels of sNRP-1 compared to healthy controls (median of 2.47 vs. 1.70 nmol/L, p < 0.001). Moreover, sNRP-1 was also elevated in patients with sepsis compared to other critical illness (2.60 vs. 2.13 nmol/L, p = 0.01), irrespective of disease severity or organ failure. In critically ill patients, sNRP-1 is positively correlated with markers of kidney and hepatic dysfunction. Most notably, critically ill patients not surviving in the long term (one year after admission) showed higher concentrations of sNRP-1 at the time of ICU admission (p = 0.036), with this association being dependent on the presence of organ failure. Critically ill and septic patients exhibit higher serum concentrations of circulating sNRP-1, which correlates to organ failure, particularly hepatic and kidney dysfunction.