High-throughput mass spectrometry maps the sepsis plasma proteome and differences in patient response.

Sepsis, the dysregulated host response to infection causing life-threatening organ dysfunction, is a global health challenge requiring better understanding of pathophysiology and new therapeutic approaches. Here, we applied high-throughput tandem mass spectrometry to delineate the plasma proteome for sepsis and comparator groups (noninfected critical illness, postoperative inflammation, and healthy volunteers) involving 2612 samples (from 1611 patients) and 4553 liquid chromatography-mass spectrometry analyses acquired through a single batch of continuous measurements, with a throughput of 100 samples per day. We show how this scale of data can delineate proteins, pathways, and coexpression modules in sepsis and be integrated with paired leukocyte transcriptomic data (837 samples from n = 649 patients). We mapped the plasma proteomic landscape of the host response in sepsis, including changes over time, and identified features relating to etiology, clinical phenotypes (including organ failures), and severity. This work reveals subphenotypes informative for sepsis response state, disease processes, and outcome; identifies potential biomarkers; and advances opportunities for a precision medicine approach to sepsis.

Clinical biomarker profiles reveals gender differences and mortality factors in sepsis.

Background: Sepsis is a major contributor to global morbidity and mortality, affecting millions each year. Notwithstanding the decline in sepsis incidence and mortality over decades, gender disparities in sepsis outcomes persist, with research suggesting higher mortality rates in males. Methods: This retrospective study aims to delineate gender-specific clinical biomarker profiles impacting sepsis progression and mortality by examining sepsis cases and related clinical data from the past three years. Propensity score matching was used to select age-matched healthy controls for comparison. Results: Among 265 sepsis patients, a significantly higher proportion were male (60.8%, P<0.001). While mortality did not significantly differ by gender, deceased patients were significantly older (mean 69 vs 43 years, P=0.003), more likely to have hypertension (54% vs 25%, P=0.019), and had higher SOFA scores (mean ~10 vs 4, P<0.01) compared to survivors. Principal Component Analysis (PCA) showed clear separation between sepsis patients and healthy controls. 48 serum biomarkers were significantly altered in sepsis, with Triiodothyronine, Apolipoprotein A, and Serum cystatin C having the highest diagnostic value by ROC analysis. Gender-stratified comparisons identified male-specific (e.g. AFP, HDLC) and female-specific (e.g. Rheumatoid factor, Interleukin-6) diagnostic biomarkers. Deceased patients significantly differed from survivors, with 22 differentially expressed markers; Antithrombin, Prealbumin, HDL cholesterol, Urea nitrogen and Hydroxybutyrate had the highest diagnostic efficiency for mortality. Conclusion: These findings enhance our understanding of gender disparities in sepsis and may guide future therapeutic strategies. Further research is warranted to validate these biomarker profiles and investigate the molecular mechanisms underlying these gender differences in sepsis outcomes.

Circulating bacterial peptides and linked metabolomic signatures are indicative of early mortality in pediatric cirrhosis.

BACKGROUND: Patients with pediatric cirrhosis-sepsis (PC-S) attain early mortality. Plasma bacterial composition, the cognate metabolites, and their contribution to the deterioration of patients with PC-S to early mortality are unknown. We aimed to delineate the plasma metaproteome-metabolome landscape and identify molecular indicators capable of segregating patients with PC-S predisposed to early mortality in plasma, and we further validated the selected metabolite panel in paired 1-drop blood samples using untargeted metaproteomics-metabolomics by UHPLC-HRMS followed by validation using machine-learning algorithms. METHODS: We enrolled 160 patients with liver diseases (cirrhosis-sepsis/nonsepsis [n=110] and noncirrhosis [n=50]) and performed untargeted metaproteomics-metabolomics on a training cohort of 110 patients (Cirrhosis-Sepsis/Nonsepsis, n=70 and noncirrhosis, n=40). The candidate predictors were validated on 2 test cohorts-T1 (plasma test cohort) and T2 (1-drop blood test cohort). Both T1 and T2 had 120 patients each, of which 70 were from the training cohort. RESULTS: Increased levels of tryptophan metabolites and Salmonella enterica and Escherichia coli-associated peptides segregated patients with cirrhosis. Increased levels of deoxyribose-1-phosphate, N5-citryl-d-ornithine, and Herbinix hemicellulolytic and Leifsonia xyli segregated patients with PC-S. MMCN-based integration analysis of WMCNA-WMpCNA identified key microbial-metabolic modules linked to PC-S nonsurvivors. Increased Indican, Staphylobillin, glucose-6-phosphate, 2-octenoylcarnitine, palmitic acid, and guanidoacetic acid along with L. xyli, Mycoplasma genitalium, and Hungateiclostridium thermocellum segregated PC-S nonsurvivors and superseded the liver disease severity indices with high accuracy, sensitivity, and specificity for mortality prediction using random forest machine-learning algorithm. CONCLUSIONS: Our study reveals a novel metabolite signature panel capable of segregating patients with PC-S predisposed to early mortality using as low as 1-drop blood.

Random forest differentiation of Escherichia coli in elderly sepsis using biomarkers and infectious sites.

This study addresses the challenge of accurately diagnosing sepsis subtypes in elderly patients, particularly distinguishing between Escherichia coli (E. coli) and non-E. coli infections. Utilizing machine learning, we conducted a retrospective analysis of 119 elderly sepsis patients, employing a random forest model to evaluate clinical biomarkers and infection sites. The model demonstrated high diagnostic accuracy, with an overall accuracy of 87.5%, and impressive precision and recall rates of 93.3% and 87.5%, respectively. It identified infection sites, platelet distribution width, reduced platelet count, and procalcitonin levels as key predictors. The model achieved an F1 Score of 90.3% and an area under the receiver operating characteristic curve of 88.0%, effectively differentiating between sepsis subtypes. Similarly, logistic regression and least absolute shrinkage and selection operator analysis underscored the significance of infectious sites. This methodology shows promise for enhancing elderly sepsis diagnosis and contributing to the advancement of precision medicine in the field of infectious diseases.

Postoperative bioactive adrenomedullin is associated with the onset of ARDS and adverse outcomes in patients undergoing open thoracoabdominal aortic surgery.

Cytokine-mediated systemic inflammation after open thoracoabdominal aortic aneurysm (TAAA) repairs plays a pivotal role in disrupting circulatory homeostasis, potentially leading to organ dysfunction. The bioactive form of adrenomedullin (bio-ADM) is a peptide hormone with immunomodulatory and vasomotor effects, making it a potential diagnostic agent in these cases. This retrospective, bicentric study, conducted between January 2019 and December 2022, recruited 36 elective open TAAA repair patients in two German centres. Serum and plasma samples were collected at multiple time points to measure bio-ADM levels. The primary objective was to evaluate the association of bio-ADM levels with the onset of acute respiratory distress syndrome (ARDS), with secondary endpoints focusing on mortality and SIRS-related morbidity. Results showed a significant association between postoperative bio-ADM levels (12-48 h after surgery) and the onset of ARDS (p < .001), prolonged ventilation (p = .015 at 12h after surgery), atrial fibrillation (p < .001), and mortality (p = .05 at 24h). The biomarker was also strongly associated with sepsis (p = .01 at 12 h) and multi-organ dysfunction syndrome (MODS) (p = .02 at 24 h after surgery). The study underscores the potential utility of bio-ADM as a diagnostic tool for identifying patients at risk of postoperative complications following open TAAA repairs.

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.

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.

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.

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.

Predictive value of laboratory indicators for in-hospital death in children with community-onset sepsis: a prospective observational study of 266 patients.

BACKGROUND AND OBJECTIVES: This study aimed to identify predictors of sepsis-associated in-hospital mortality from readily available laboratory biomarkers at onset of illness that include haematological, coagulation, liver and kidney function, blood lipid, cardiac enzymes and arterial blood gas. METHODS: Children with sepsis were enrolled consecutively in a prospective observational study involving paediatric intensive care units (PICUs) of two hospitals in Beijing, between November 2016 and January 2020. The data on demographics, laboratory examinations during the first 24 hours after PICU admission, complications and outcomes were collected. We screened baseline laboratory indicators using the Least Absolute Shrinkage and Selection Operator (LASSO) analysis, then we constructed a mortality risk model using Cox proportional hazards regression analysis. The ability of risk factors to predict in-hospital mortality was evaluated by receiver operating characteristic (ROC) curves. RESULTS: A total of 266 subjects were enrolled including 44 (16.5%) deaths and 222 (83.5%) survivors. Those who died showed a shorter length of hospitalisation, and a higher proportion of mechanical ventilation, complications and organ failure (p<0.05). LASSO analysis identified 13 clinical parameters related to prognosis, which were included in the final Cox model. An elevated triglyceride (TG) remained the most significant risk factor of death (HR=1.469, 95% CI: 1.010 to 2.136, p=0.044), followed by base excess (BE) (HR=1.131, 95% CI: 1.046 to 1.223, p=0.002) and pH (HR=0.95, 95% CI: 0.93 to 0.97, p<0.001). The results of the ROC curve showed that combined diagnosis of the three indicators-TG+BE+pH-has the best area under the curve (AUC) (AUC=0.77, 95% CI: 0.69 to 0.85, p<0.001), with a 68% sensitivity and 80% specificity. CONCLUSION: Laboratory factors of TG, BE and pH during the first 24 hours after intensive care unit admission are associated with in-hospital mortality in PICU patients with sepsis. The combination of the three indices has high diagnostic value.

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.

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.

Suppression PCR-Based Selective Enrichment Sequencing for Pathogen and Antimicrobial Resistance Detection on Cell-Free DNA in Sepsis-A Targeted, Blood Culture-Independent Approach for Rapid Pathogen and Resistance Diagnostics in Septic Patients.

Sepsis is a life-threatening syndrome triggered by infection and accompanied by high mortality, with antimicrobial resistances (AMRs) further escalating clinical challenges. The rapid and reliable detection of causative pathogens and AMRs are key factors for fast and appropriate treatment, in order to improve outcomes in septic patients. However, current sepsis diagnostics based on blood culture is limited by low sensitivity and specificity while current molecular approaches fail to enter clinical routine. Therefore, we developed a suppression PCR-based selective enrichment sequencing approach (SUPSETS), providing a molecular method combining multiplex suppression PCR with Nanopore sequencing to identify most common sepsis-causative pathogens and AMRs using plasma cell-free DNA. Applying only 1 mL of plasma, we targeted eight pathogens across three kingdoms and ten AMRs in a proof-of-concept study. SUPSETS was successfully tested in an experimental research study on the first ten clinical samples and revealed comparable results to clinical metagenomics while clearly outperforming blood culture. Several clinically relevant AMRs could be additionally detected. Furthermore, SUPSETS provided first pathogen and AMR-specific sequencing reads within minutes of starting sequencing, thereby potentially decreasing time-to-results to 11-13 h and suggesting diagnostic potential in 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.