Biomarkers of sepsis: time for a reappraisal

The predictive value of left ventricular global longitudinal strain in normotensive critically ill septic patients

OBJECTIVE

Evaluation of left ventricular systolic function using speckle tracking echocardiography is more sensitive than conventional echocardiographic measurement in detecting subtle left ventricular dysfunction in septic patients. Our purpose was to investigate the predictive significance of left ventricular global longitudinal strain in normotensive septic intensive care patients.

METHODS

This observational, prospective cohort study included septic normotensive adults admitted to the intensive care unit between June 1, 2021, and August 31, 2021. Left ventricular systolic function was measured using speckle-tracking echocardiography within 24 hours of admission.

RESULTS

One hundred fifty-two patients were enrolled. The intensive care unit mortality rate was 27%. Left ventricular global longitudinal strain was less negative, which indicated worse left ventricular function in non-survivors than survivors (median [interquartile range], -15.2 [-17.2 - -12.5] versus -17.3 [-18.8 - -15.5]; p < 0.001). The optimal cutoff value for left ventricular global longitudinal strain was -17% in predicting intensive care unit mortality (area under the curve, 0.728). Patients with left ventricular global longitudinal strain > -17% (less negative than -17%, which indicated worse left ventricular function) showed a significantly higher mortality rate (39.2% versus 13.7%; p < 0.001). According to multivariate analysis, left ventricular global longitudinal strain was an independent predictor of intensive care unit mortality [OR (95%CI), 1.326 (1.038 - 1.693); p = 0.024], along with invasive mechanical ventilation and Glasgow coma scale, APACHE II, and SOFA risk scores.

CONCLUSION

Impaired left ventricular global longitudinal strain is associated with mortality and provided predictive data in normotensive septic intensive care patients.

Circulating protein and lipid markers of early sepsis diagnosis and prognosis: a scoping review

PURPOSE OF REVIEW

Sepsis is the extreme response to infection associated with high mortality, yet reliable biomarkers for its identification and stratification are lacking.

RECENT FINDINGS

Our scoping review of studies published from January 2017 to September 2022 that investigated circulating protein and lipid markers to inform non-COVID-19 sepsis diagnosis and prognosis identified interleukin (IL)-6, IL-8, heparin-binding protein (HBP), and angiopoietin-2 as having the most evidence. Biomarkers can be grouped according to sepsis pathobiology to inform biological data interpretation and four such physiologic processes include: immune regulation, endothelial injury and coagulopathy, cellular injury, and organ injury. Relative to proteins, the pleiotropic effects of lipid species' render their categorization more difficult. Circulating lipids are relatively less well studied in sepsis, however, low high-density lipoprotein (HDL) is associated with poor outcome.

SUMMARY

There is a lack of robust, large, and multicenter studies to support the routine use of circulating proteins and lipids for sepsis diagnosis or prognosis. Future studies will benefit from standardizing cohort design as well as analytical and reporting strategies. Incorporating biomarker dynamic changes and clinical data in statistical modeling may improve specificity for sepsis diagnosis and prognosis. To guide future clinical decisions at the bedside, point-of-care circulating biomarker quantification is needed.

CTRP family in diseases associated with inflammation and metabolism: molecular mechanisms and clinical implication

C1q/tumor necrosis factor (TNF) related proteins (CTRPs) is a newly discovered adipokine family with conservative structure and ubiquitous distribution and is secreted by adipose tissues. Recently, CTRPs have attracted increasing attention due to the its wide-ranging effects upon inflammation and metabolism. To-date, 15 members of CTRPs (CTRP1-15) with the characteristic C1q domain have been characterized. Earlier in-depth phenotypic analyses of mouse models of CTRPs deficiency have also unveiled ample function of CTRPs in inflammation and metabolism. This review focuses on the rise of CTRPs, with a special emphasis on the latest discoveries with regards to the effects of the CTRP family on inflammation and metabolism as well as related diseases. We first introduced the structure of characteristic domain and polymerization of CTRPs to reveal its pleiotropic biological functions. Next, intimate association of CTRP family with inflammation and metabolism, as well as the involvement of CTRPs as nodes in complex molecular networks, were elaborated. With expanding membership of CTRP family, the information presented here provides new perspectives for therapeutic strategies to improve inflammatory and metabolic abnormalities.

Host Response Biomarkers for Sepsis in the Emergency Room

This article is one of ten reviews selected from the Annual Update in Intensive Care and Emergency Medicine 2023. Other selected articles can be found online at https://www.biomedcentral.com/collections/annualupdate2023 . Further information about the Annual Update in Intensive Care and Emergency Medicine is available from https://link.springer.com/bookseries/8901 .

Exploring Dysregulated Ferroptosis-Related Genes in Septic Myocardial Injury Based on Human Heart Transcriptomes: Evidence and New Insights

Introduction

Sepsis is currently a common condition in emergency and intensive care units, and is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Cardiac dysfunction caused by septic myocardial injury (SMI) is associated with adverse prognosis and has significant economic and human costs. The pathophysiological mechanisms underlying SMI have long been a subject of interest. Recent studies have identified ferroptosis, a form of programmed cell death associated with iron accumulation and lipid peroxidation, as a pathological factor in the development of SMI. However, the current understanding of how ferroptosis functions and regulates in SMI remains limited, particularly in the absence of direct evidence from human heart.

Methods

We performed a sequential comprehensive bioinformatics analysis of human sepsis cardiac transcriptome data obtained through the GEO database. The lipopolysaccharide-induced mouse SMI model was used to validate the ferroptosis features and transcriptional expression of key genes.

Results

We identified widespread dysregulation of ferroptosis-related genes (FRGs) in SMI based on the human septic heart transcriptomes, deeply explored the underlying biological mechanisms and crosstalks, followed by the identification of key functional modules and hub genes through the construction of protein-protein interaction network. Eight key FRGs that regulate ferroptosis in SMI, including HIF1A, MAPK3, NOX4, PPARA, PTEN, RELA, STAT3 and TP53, were identified, as well as the ferroptosis features. All the key FRGs showed excellent diagnostic capability for SMI, part of them was associated with the prognosis of sepsis patients and the immune infiltration in the septic hearts, and potential ferroptosis-modulating drugs for SMI were predicted based on key FRGs.

Conclusion

This study provides human septic heart transcriptome-based evidence and brings new insights into the role of ferroptosis in SMI, which is significant for expanding the understanding of the pathobiological mechanisms of SMI and exploring promising diagnostic and therapeutic targets for SMI.

Hematological Parameters and Procalcitonin as Discriminants between Bacterial Pneumonia-Induced Sepsis and Viral Sepsis Secondary to COVID-19: A Retrospective Single-Center Analysis

Bacterial and viral sepsis induce alterations of all hematological parameters and procalcitonin is used as a biomarker of infection and disease severity. Our aim was to study the hematological patterns associated with pulmonary sepsis triggered by bacteria and Severe Acute Respiratory Syndrome-Coronavirus-type-2 (SARS-CoV-2) and to identify the discriminants between them. We performed a retrospective, observational study including 124 patients with bacterial sepsis and 138 patients with viral sepsis. Discriminative ability of hematological parameters and procalcitonin between sepsis types was tested using receiver operating characteristic (ROC) analysis. Sensitivity (Sn%), specificity (Sp%), positive and negative likelihood ratios were calculated for the identified cut-off values. Patients with bacterial sepsis were older than patients with viral sepsis (p < 0.001), with no differences regarding gender. Subsequently to ROC analysis, procalcitonin had excellent discriminative ability for bacterial sepsis diagnosis with an area under the curve (AUC) of 0.92 (cut-off value of >1.49 ng/mL; Sn = 76.6%, Sp = 94.2%), followed by RDW% with an AUC = 0.87 (cut-off value >14.8%; Sn = 80.7%, Sp = 85.5%). Leukocytes, monocytes and neutrophils had good discriminative ability with AUCs between 0.76-0.78 (p < 0.001), while other hematological parameters had fair or no discriminative ability. Lastly, procalcitonin value was strongly correlated with disease severity in both types of sepsis (p < 0.001). Procalcitonin and RDW% had the best discriminative ability between bacterial and viral sepsis, followed by leukocytes, monocytes and neutrophils. Procalcitonin is a marker of disease severity regardless of sepsis type.

Systemic immune activation profiles in streptococcal necrotizing soft tissue infections: A prospective multicenter study

OBJECTIVE

Early stages with streptococcal necrotizing soft tissue infections (NSTIs) are often difficult to discern from cellulitis. Increased insight into inflammatory responses in streptococcal disease may guide correct interventions and discovery of novel diagnostic targets.

METHODS

Plasma levels of 37 mediators, leucocytes and CRP from 102 patients with β-hemolytic streptococcal NSTI derived from a prospective Scandinavian multicentre study were compared to those of 23 cases of streptococcal cellulitis. Hierarchical cluster analyses were also performed.

RESULTS

Differences in mediator levels between NSTI and cellulitis cases were revealed, in particular for IL-1β, TNFα and CXCL8 (AUC >0.90). Across streptococcal NSTI etiologies, eight biomarkers separated cases with septic shock from those without, and four mediators predicted a severe outcome.

CONCLUSION

Several inflammatory mediators and wider profiles were identified as potential biomarkers of NSTI. Associations of biomarker levels to type of infection and outcomes may be utilized to improve patient care and outcomes.

Recent Advances in Monoclonal Antibody-Based Approaches in the Management of Bacterial Sepsis

Sepsis is a life-threatening condition characterized by an uncontrolled inflammatory response to an infectious agent and its antigens. Immune cell activation against the antigens causes severe distress that mediates a strong inflammatory response in vital organs. Sepsis is responsible for a high rate of morbidity and mortality in immunosuppressed patients. Monoclonal antibody (mAb)-based therapeutic strategies are now being explored as a viable therapy option for severe sepsis and septic shock. Monoclonal antibodies may provide benefits through two major strategies: (a) monoclonal antibodies targeting the pathogen and its components, and (b) mAbs targeting inflammatory signaling may directly suppress the production of inflammatory mediators. The major focus of mAb therapies has been bacterial endotoxin (lipopolysaccharide), although other surface antigens are also being investigated for mAb therapy. Several promising candidates for mAbs are undergoing clinical trials at present. Despite several failures and the investigation of novel targets, mAb therapy provides a glimmer of hope for the treatment of severe bacterial sepsis and septic shock. In this review, mAb candidates, their efficacy against controlling infection, with special emphasis on potential roadblocks, and prospects are discussed.

The evolving value of older biomarkers in the clinical diagnosis of pediatric sepsis

Sepsis remains the leading cause of childhood mortality worldwide. The evolving definition of pediatric sepsis is extrapolated from adult studies. Although lacking formal validation in the pediatric population, this working definition has historically proven its clinical utility. Prompt identification of pediatric sepsis is challenging as clinical picture is often variable. Timely intervention is crucial for optimal outcome, thus biomarkers are utilized to aid in immediate, yet judicious, diagnosis of sepsis. Over time, their use in sepsis has expanded with discovery of newer biomarkers that include genomic bio-signatures. Despite recent scientific advances, there is no biomarker that can accurately diagnose sepsis. Furthermore, older biomarkers are readily available in most institutions while newer biomarkers are not. Hence, the latter's clinical value in pediatric sepsis remains theoretical. Albeit promising, scarce data on newer biomarkers have been extracted from research settings making their clinical value unclear. As interest in newer biomarkers continue to proliferate despite their ambiguous clinical use, the literature on older biomarkers in clinical settings continue to diminish. Thus, revisiting the evolving value of these earliest biomarkers in optimizing pediatric sepsis diagnosis is warranted. This review focuses on the four most readily available biomarkers to bedside clinicians in diagnosing pediatric sepsis. IMPACT: The definition of pediatric sepsis remains an extrapolation from adult studies. Older biomarkers that include C-reactive protein, procalcitonin, ferritin, and lactate are the most readily available biomarkers in most pediatric institutions to aid in the diagnosis of pediatric sepsis. Older biomarkers, although in varying levels of reliability, remain to be useful clinical adjuncts in the diagnosis of pediatric sepsis if used in the appropriate clinical context. C-reactive protein and procalcitonin are more sensitive and specific among these older biomarkers in diagnosing pediatric sepsis although evidence varies in different age groups and clinical scenarios.

Predictors of outcomes in emergency department patients with suspected infections and without fulfillment of the sepsis criteria

BACKGROUND

Data on patient characteristics and determinants of serious outcomes for acutely admitted patients with infections who do not fulfill the sepsis criteria are sparse. The study aimed to characterize acutely admitted emergency department (ED) patients with infections and a composite outcome of in-hospital mortality or transfer to the intensive care unit without fulfilling the criteria for sepsis and to examine predictors of the composite outcome.

METHODS

This was a secondary analysis of data from a prospective observational study of patients with suspected bacterial infection admitted to the ED between October 1, 2017 and March 31, 2018. A National Early Warning Score 2 (NEWS2) ≥ 5 within the first 4 h in the ED was assumed to represent a sepsis-like condition with a high risk for the composite endpoint. Patients who achieved the composite outcome were grouped according to fulfillment of the NEWS2 ≥ 5 criteria. We used logistic regression analysis to estimate the unadjusted and adjusted odds ratio (OR) for the composite endpoint among patients with either NEWS2  < 5 (NEWS2-) or NEWS2  ≥ 5 (NEWS2+).

RESULTS

A total of 2055 patients with a median age of 73 years were included. Of these, 198 (9.6%) achieved the composite endpoint, including 59 (29.8%) NEWS2- and 139 (70.2%) NEWS2+ patients, respectively. Diabetes (OR 2.23;1.23-4.0), a Sequential Organ Failure Assessment (SOFA) score ≥ 2 (OR 2.57;1.37-4.79), and a Do-not-attempt-cardiopulmonary-resuscitation order (DNACPR) on admission (OR 3.70;1.75-7.79) were independent predictive variables for the composite endpoint in NEWS2- patients (goodness-of-fit test P = 0.291; area under the receiver operating characteristic curve for the model (AUROC) = 0.72). The regression model for NEWS2+ patients revealed that a SOFA score ≥ 2 (OR 2.79; 1.59-4.91), hypothermia (OR 2.48;1.30-4.75), and DNACPR order on admission were predictive variables for the composite endpoint (goodness-of-fit test P = 0.62; AUROC for the model = 0.70).

CONCLUSION

Approximately one-third of the patients with infections and serious outcomes during hospitalization did not meet the NEWS2 threshold for likely sepsis. Our study identified factors with independent predictive values for the development of serious outcomes that should be tested in future prediction models.

Systemic inflammation as a biomarker of seizure propensity and a target for treatment to reduce seizure propensity

People with diabetes can wear a device that measures blood glucose and delivers just the amount of insulin needed to return the glucose level to within bounds. Currently, people with epilepsy do not have access to an equivalent wearable device that measures a systemic indicator of an impending seizure and delivers a rapidly acting medication or other intervention (e.g., an electrical stimulus) to terminate or prevent a seizure. Given that seizure susceptibility is reliably increased in systemic inflammatory states, we propose a novel closed-loop device where release of a fast-acting therapy is governed by sensors that quantify the magnitude of systemic inflammation. Here, we review the evidence that patients with epilepsy have raised levels of systemic indicators of inflammation than controls, and that some anti-inflammatory drugs have reduced seizure occurrence in animals and humans. We then consider the options of what might be incorporated into a responsive anti-seizure system.

Application of Digital Holographic Microscopy to Analyze Changes in T-Cell Morphology in Response to Bacterial Challenge

Quantitative phase imaging (QPI) is a non-invasive, label-free technique used to detect aberrant cell morphologies caused by disease, thus providing a useful diagnostic approach. Here, we evaluated the potential of QPI to differentiate specific morphological changes in human primary T-cells exposed to various bacterial species and strains. Cells were challenged with sterile bacterial determinants, i.e., membrane vesicles or culture supernatants, derived from different Gram-positive and Gram-negative bacteria. Timelapse QPI by digital holographic microscopy (DHM) was applied to capture changes in T-cell morphology over time. After numerical reconstruction and image segmentation, we calculated single cell area, circularity and mean phase contrast. Upon bacterial challenge, T-cells underwent rapid morphological changes such as cell shrinkage, alterations of mean phase contrast and loss of cell integrity. Time course and intensity of this response varied between both different species and strains. The strongest effect was observed for treatment with S. aureus-derived culture supernatants that led to complete lysis of the cells. Furthermore, cell shrinkage and loss of circular shape was stronger in Gram-negative than in Gram-positive bacteria. Additionally, T-cell response to bacterial virulence factors was concentration-dependent, as decreases in cellular area and circularity were enhanced with increasing concentrations of bacterial determinants. Our findings clearly indicate that T-cell response to bacterial stress depends on the causative pathogen, and specific morphological alterations can be detected using DHM.

Developing a machine learning prediction algorithm for early differentiation of urosepsis from urinary tract infection

OBJECTIVES

Early recognition and timely intervention for urosepsis are key to reducing morbidity and mortality. Blood culture has low sensitivity, and a long turnaround time makes meeting the needs of clinical diagnosis difficult. This study aimed to use biomarkers to build a machine learning model for early prediction of urosepsis.

METHODS

Through retrospective analysis, we screened 157 patients with urosepsis and 417 patients with urinary tract infection. Laboratory data of the study participants were collected, including data on biomarkers, such as procalcitonin, D-dimer, and C-reactive protein. We split the data into training (80%) and validation datasets (20%) and determined the average model prediction accuracy through cross-validation.

RESULTS

In total, 26 variables were initially screened and 18 were statistically significant. The influence of the 18 variables was sorted using three ranking methods to further determine the best combination of variables. The Gini importance ranking method was found to be suitable for variable filtering. The accuracy rates of the six machine learning models in predicting urosepsis were all higher than 80%, and the performance of the artificial neural network (ANN) was the best among all. When the ANN included the eight biomarkers with the highest influence ranking, its model had the best prediction performance, with an accuracy rate of 92.9% and an area under the receiver operating characteristic curve of 0.946.

CONCLUSIONS

Urosepsis can be predicted using only the top eight biomarkers determined by the ranking method. This data-driven predictive model will enable clinicians to make quick and accurate diagnoses.

Biomarkers as Prognostic Predictors and Therapeutic Guide in Critically Ill Patients: Clinical Evidence

A biomarker is a molecule that can be measured in a biological sample in an objective, systematic, and precise way, whose levels indicate whether a process is normal or pathological. Knowing the most important biomarkers and their characteristics is the key to precision medicine in intensive and perioperative care. Biomarkers can be used to diagnose, in assessment of disease severity, to stratify risk, to predict and guide clinical decisions, and to guide treatments and response to them. In this review, we will analyze what characteristics a biomarker should have and how to ensure its usefulness, and we will review the biomarkers that in our opinion can make their knowledge more useful to the reader in their clinical practice, with a future perspective. These biomarkers, in our opinion, are lactate, C-Reactive Protein, Troponins T and I, Brain Natriuretic Peptides, Procalcitonin, MR-ProAdrenomedullin and BioAdrenomedullin, Neutrophil/lymphocyte ratio and lymphopenia, Proenkephalin, NefroCheck, Neutrophil gelatinase-associated lipocalin (NGAL), Interleukin 6, Urokinase-type soluble plasminogen activator receptor (suPAR), Presepsin, Pancreatic Stone Protein (PSP), and Dipeptidyl peptidase 3 (DPP3). Finally, we propose an approach to the perioperative evaluation of high-risk patients and critically ill patients in the Intensive Care Unit (ICU) based on biomarkers.

Organism-Wide Analysis of Sepsis Reveals Mechanisms of Systemic Inflammation

Sepsis is a systemic response to infection with life-threatening consequences. Our understanding of the impact of sepsis across organs of the body is rudimentary. Here, using mouse models of sepsis, we generate a dynamic, organism-wide map of the pathogenesis of the disease, revealing the spatiotemporal patterns of the effects of sepsis across tissues. These data revealed two interorgan mechanisms key in sepsis. First, we discover a simplifying principle in the systemic behavior of the cytokine network during sepsis, whereby a hierarchical cytokine circuit arising from the pairwise effects of TNF plus IL-18, IFN-γ, or IL-1β explains half of all the cellular effects of sepsis on 195 cell types across 9 organs. Second, we find that the secreted phospholipase PLA2G5 mediates hemolysis in blood, contributing to organ failure during sepsis. These results provide fundamental insights to help build a unifying mechanistic framework for the pathophysiological effects of sepsis on the body.

How to use biomarkers of infection or sepsis at the bedside: guide to clinicians

Sepsis is defined as a life-threatening organ dysfunction caused by a dysregulated host response to infection. In this context, biomarkers could be considered as indicators of either infection or dysregulated host response or response to treatment and/or aid clinicians to prognosticate patient risk. More than 250 biomarkers have been identified and evaluated over the last few decades, but no biomarker accurately differentiates between sepsis and sepsis-like syndrome. Published data support the use of biomarkers for pathogen identification, clinical diagnosis, and optimization of antibiotic treatment. In this narrative review, we highlight how clinicians could improve the use of pathogen-specific and of the most used host-response biomarkers, procalcitonin and C-reactive protein, to improve the clinical care of patients with sepsis. Biomarker kinetics are more useful than single values in predicting sepsis, when making the diagnosis and assessing the response to antibiotic therapy. Finally, integrated biomarker-guided algorithms may hold promise to improve both the diagnosis and prognosis of sepsis. Herein, we provide current data on the clinical utility of pathogen-specific and host-response biomarkers, offer guidance on how to optimize their use, and propose the needs for future research.

Association Between Hypocholesterolemia and Mortality in Critically Ill Patients With Sepsis: A Systematic Review and Meta-Analysis

To ascertain the association between cholesterol and triglyceride levels on ICU admission and mortality in patients with sepsis.

DATA SOURCES

Systematic review and meta-analysis of published studies on PubMed and Embase.

STUDY SELECTION

All observational studies reporting ICU admission cholesterol and triglyceride levels in critically ill patients with sepsis were included. Authors were contacted for further data.

DATA EXTRACTION

Eighteen observational studies were identified, including 1,283 patients with a crude overall mortality of 33.3%. Data were assessed using Revman (Version 5.1, Cochrane Collaboration, Oxford, United Kingdom) and presented as mean difference (MD) with 95% CIs, p values, and I 2 values.

DATA SYNTHESIS

Admission levels of total cholesterol (17 studies, 1,204 patients; MD = 0.52 mmol/L [0.27-0.77 mmol/L]; p < 0.001; I 2 = 91%), high-density lipoprotein (HDL)-cholesterol (14 studies, 991 patients; MD = 0.08 mmol/L [0.01-0.15 mmol/L]; p = 0.02; I 2 = 61%), and low-density lipoprotein (LDL)-cholesterol (15 studies, 1,017 patients; MD = 0.18 mmol/L [0.04-0.32 mmol/L]; p = 0.01; I 2 = 71%) were significantly lower in eventual nonsurvivors compared with survivors. No association was seen between admission triglyceride levels and mortality (15 studies, 1,070 patients; MD = 0.00 mmol/L [-0.16 to 0.15 mmol/L]; p = -0.95; I 2 = 79%).

CONCLUSIONS

Mortality was associated with lower levels of total cholesterol, HDL-cholesterol, and LDL-cholesterol, but not triglyceride levels, in patients admitted to ICU with sepsis. The impact of cholesterol replacement on patient outcomes in sepsis, particularly in at-risk groups, merits investigation.

Monocyte Distribution Width (MDW) as a biomarker of sepsis: An evidenced-based laboratory medicine approach

Monocyte Distribution Width (MDW) is a new generation cell blood count parameter providing a measure of monocyte anisocytosis. In the last decades, it has emerged as a reliable biomarker of sepsis in the acute setting, especially emergency department, and intensive care unit. MDW has several advantages over commonly used sepsis biomarkers, including low-cost, ease and speed of measurement. The clinical usefulness of MDW has been established in several studies and some clinical laboratory medicines have already implemented it in their routine. In this article, we describe the analytical and clinical features of MDW to guide its appropriate use in clinical practice by integrating the research evidence with real-world laboratory experience. The proper use of a biomarker is critical for improving patients' care and outcome as well as ensuring healthcare quality.

Diagnostic value of procalcitonin, hypersensitive C-reactive protein and neutrophil-to-lymphocyte ratio for bloodstream infections in pediatric tumor patients

OBJECTIVES

Bloodstream infection (BSI) is one of the major causes of death in pediatric tumor patients. Blood samples are relatively easy to obtain and thus provide a ready source of infection-related biological markers for the prompt evaluation of infection risk.

METHODS

A total of 259 pediatric tumor patients were included from May 2019 to March 2022. Patients were divided into BSI group (n=70) and control group (n=189). Clinical and biological data were collected using electronic medical records. Differences in biological markers between BSI group and control group and differences before and during infection in BSI group were analyzed.

RESULTS

The infected group showed higher levels of procalcitonin (PCT) and hypersensitive C-reactive-protein (hsCRP), and lower prealbumin (PA) than the uninfected group. Area under the receiver-operating curve (ROC) curves (AUC) of PCT, hsCRP and NLR (absolute neutrophil count to the absolute lymphocyte count) were 0.756, 0.617 and 0.612. The AUC of other biomarkers was ≤0.6. In addition, PCT, hsCRP, NLR and fibrinogen (Fg) were significantly increased during infection, while PA and lymphocyte (LYM) were significantly decreased. Antibiotic resistant of Gram-positive bacteria to CHL, SXT, OXA and PEN was lower than that of Coagulase-negative Staphylococcus. Resistant of Gram-positive bacteria to CHL was lower, while to SXT was higher than that of Gram-negative bacteria.

CONCLUSIONS

This study explored the utility of biomarkers to assist in diagnosis and found that the PCT had the greatest predictive value for infection in pediatric tumor patients with BSI. Additionally, the PCT, hsCRP, NLR, PA, LYM and Fg were changed by BSI.

Developing an Interpretable Machine Learning Model to Predict in-Hospital Mortality in Sepsis Patients: A Retrospective Temporal Validation Study

BACKGROUND

Risk stratification plays an essential role in the decision making for sepsis management, as existing approaches can hardly satisfy the need to assess this heterogeneous population. We aimed to develop and validate a machine learning model to predict in-hospital mortality in critically ill patients with sepsis.

METHODS

Adult patients fulfilling the definition of Sepsis-3 were included at a large tertiary medical center. Relevant clinical features were extracted within the first 24 h in ICU, re-classified into different genres, and utilized for model development under three strategies: "Basic + Lab", "Basic + Intervention", and "Whole" feature sets. Extreme gradient boosting (XGBoost) was compared with logistic regression (LR) and established severity scores. Temporal validation was conducted using admissions from 2017 to 2019.

RESULTS

The final cohort included 24,272 patients, of which 4013 patients formed the test cohort for temporal validation. The trained and fine-tuned XGBoost model with the whole feature set showed the best discriminatory ability in the test cohort with AUROC as 0.85, significantly higher than the XGBoost "Basic + Lab" model (0.83), the LR "Whole" model (0.82), SOFA (0.63), SAPS-II (0.73), and LODS score (0.74). The performance in varying subgroups remained robust, and predictors, such as increased urine output and supplemental oxygen therapy, were crucially correlated with improved survival when interpretability was explored.

CONCLUSIONS

We developed and validated a novel XGBoost-based model and demonstrated significantly improved performance to LR and other scores in predicting the mortality risks of sepsis patients in the hospital using features in the first 24 h.

Heparin-binding protein as a biomarker of severe sepsis in the pediatric intensive care unit: A multicenter, prospective study

OBJECTIVES

The aim of this study is to assess Heparin-binding protein (HBP) as a diagnostic and prognostic biomarker of severe sepsis in the pediatric intensive care unit (PICU).

METHODS

A multicenter, prospective study was conducted among children with sepsis in nine PICUs in China from October 2019 to June 2021. Plasma levels of HBP, procalcitonin (PCT), C-reactive protein (CRP), lactate, and white blood cell (WBC) count were determined at enrollment and 72 h after enrollment.

RESULTS

Of 355 included patients, 132 patients were diagnosed with non-severe sepsis (referred to as sepsis), 223 patients had severe sepsis. Patients with severe sepsis had significantly elevated levels of HBP compared with sepsis (median 170.5 vs. 74.1 ng/mL, P < 0.001). Adding HBP to a diagnostic model with PCT and lactate could significantly improve the diagnostic capability for severe sepsis. The plasma levels of HBP correlated positively with the number of dysfunctional organs. After adjusting for confounding factors, the declined levels of HBP at 72 h had a significant association with decreased in-hospital mortality (adjusted odds ratio (aOR) 0.242, P < 0.001). The levels of HBP showed weak positive correlations with PCT, CRP, WBC, and no correlation to lactate.

CONCLUSIONS

HBP at enrollment can be an independent indicator for severe sepsis and the dynamic changes at 72 h can be a predictor for in-hospital mortality in PICU.

Distinct patterns of serum and urine macrophage migration inhibitory factor kinetics predict death in sepsis: a prospective, observational clinical study

Macrophage migration inhibitory factor (MIF) has been considered as a biomarker in sepsis, however the predictive value of the pattern of its kinetics in the serum and in the urine has remained unclarified. It is also unclear whether the kinetics of MIF are different between males and females. We conducted a single-center prospective, observational study with repeated measurements of MIF in serum and urine on days 0, 2, and 4 from admission to the intensive care unit (ICU) in 50 adult septic patients. We found that in patients who died within 90 days, there was an increase in serum MIF level from day 0 to 4, whereas in the survivors there was rather a decrease (p = 0.018). The kinetics were sex-dependent as the same difference in the pattern was present in males (p = 0.014), but not in females (p = 0.418). We also found that urine MIF was markedly lower in patients who died than in survivors of sepsis (p < 0.050). Urine MIF levels did not show temporal changes: there was no meaningful difference between day 0 and 4. These results suggest that kinetics of serum MIF during the initial days from ICU admission can predict death, especially in male patients. Additionally, lower urine MIF levels can also indicate death without showing meaningful temporal kinetics.

[Diagnostic Approach in Sepsis]

Sepsis occurs both community acquired and as a complication of hospital treatment. The symptoms are usually nonspecific and there is no diagnostic gold standard. The diagnostic differentiation from other clinical pictures is difficult. Therefore, the (early) diagnosis of sepsis is still a major challenge for the clinician. Despite multiple biomarkers described in the scientific literature sepsis is still primarily a clinical diagnosis. qSOFA can be a helpful screening tool.

Finding and treating the focus of infection is a crucial part of sepsis therapy. Chest X-ray and sonography have limited sensitivity for this purpose. A CT-scan with contrast should be done at least in all patients where the focus of infection is still unclear. An MRI is necessary if spondylodiscitis is suspected, a transesophageal echocardiography if endocarditis is a possible focus. Biomarkers are helpful in guiding therapy but are not part of the initial diagnosis criteria. Blood cultures and microbiological samples from the suspected foci of infection should be taken in all sepsis patients. An initial lactate measurement is also part of the diagnostic workup and necessary for the diagnosis of septic shock.

Consistently low levels of histidine-rich glycoprotein as a new prognostic biomarker for sepsis: A multicenter prospective observational study

BACKGROUND

Few sepsis biomarkers accurately predict severity and mortality. Previously, we had reported that first-day histidine-rich glycoprotein (HRG) levels were significantly lower in patients with sepsis and were associated with mortality. Since the time trends of HRG are unknown, this study focused on the time course of HRG in patients with sepsis and evaluated the differences between survivors and non-survivors.

METHODS

A multicenter prospective observational study was conducted involving 200 patients with sepsis in 16 Japanese hospitals. Blood samples were collected on days 1, 3, 5, and 7, and 28-day mortality was used for survival analysis. Plasma HRG levels were determined using a modified quantitative sandwich enzyme-linked immunosorbent assay.

RESULTS

First-day HRG levels in non-survivors were significantly lower than those in survivors (mean, 15.7 [95% confidence interval (CI), 13.4-18.1] vs 20.7 [19.5-21.9] μg/mL; P = 0.006). Although there was no time × survivors/non-survivors interaction in the time courses of HRG (P = 0.34), the main effect of generalized linear mixed models was significant (P < 0.001). In a univariate Cox proportional hazards model with each variable as a time-dependent covariate, higher HRG levels were significantly associated with a lower risk of mortality (hazard ratio, 0.85 [95% CI, 0.78-0.92]; P < 0.001). Furthermore, presepsin levels (P = 0.02) and Sequential Organ Function Assessment scores (P < 0.001) were significantly associated with mortality. Harrell's C-index values for the 28-day mortality effect of HRG, presepsin, procalcitonin, and C-reactive protein were 0.72, 0.70, 0.63, and 0.59, respectively.

CONCLUSIONS

HRG levels in non-survivors were consistently lower than those in survivors during the first seven days of sepsis. Repeatedly measured HRG levels were significantly associated with mortality. Furthermore, the predictive power of HRG for mortality may be superior to that of other singular biomarkers, including presepsin, procalcitonin, and C-reactive protein.

Association between age and the host response in critically ill patients with sepsis

BACKGROUND

The association of ageing with increased sepsis mortality is well established. Nonetheless, current investigations on the influence of age on host response aberrations are largely limited to plasma cytokine levels while neglecting other pathophysiological sepsis domains like endothelial cell activation and function, and coagulation activation. The primary objective of this study was to gain insight into the association of ageing with aberrations in key host response pathways and blood transcriptomes in sepsis.

METHODS

We analysed the clinical outcome (n = 1952), 16 plasma biomarkers providing insight in deregulation of specific pathophysiological domains (n = 899), and blood leukocyte transcriptomes (n = 488) of sepsis patients stratified according to age decades. Blood transcriptome results were validated in an independent sepsis cohort and compared with healthy individuals.

RESULTS

Older age was associated with increased mortality independent of comorbidities and disease severity. Ageing was associated with lower endothelial cell activation and dysfunction, and similar inflammation and coagulation activation, despite higher disease severity scores. Blood leukocytes of patients ≥ 70 years, compared to patients < 50 years, showed decreased expression of genes involved in cytokine signaling, and innate and adaptive immunity, and increased expression of genes involved in hemostasis and endothelial cell activation. The diminished expression of gene pathways related to innate immunity and cytokine signaling in subjects ≥ 70 years was sepsis-induced, as healthy subjects ≥ 70 years showed enhanced expression of these pathways compared to healthy individuals < 50 years.

CONCLUSIONS

This study provides novel evidence that older age is associated with relatively mitigated sepsis-induced endothelial cell activation and dysfunction, and a blood leukocyte transcriptome signature indicating impaired innate immune and cytokine signaling. These data suggest that age should be considered in patient selection in future sepsis trials targeting the immune system and/or the endothelial cell response.

Timing and Spectrum of Antibiotic Treatment for Suspected Sepsis and Septic Shock: Why so Controversial?

Sepsis guidelines and mandates encourage increasingly aggressive time-to-antibiotic targets for broad-spectrum antimicrobials for suspected sepsis and septic shock. This has caused considerable controversy due to weaknesses in the underlying evidence and fear that overly strict antibiotic deadlines may harm patients by perpetuating or escalating overtreatment. Indeed, a third or more of patients currently treated for sepsis and septic shock have noninfectious or nonbacterial conditions. These patients risk all the potential harms of antibiotics without their possible benefits. Updated Surviving Sepsis Campaign guidelines now emphasize the importance of tailoring antibiotics to each patient's likelihood of infection, risk for drug-resistant pathogens, and severity-of-illness.

Gaps and opportunities in sepsis translational research

Infection initiates sepsis, but the clinical disease arises through the innate immune response of the host. A rapidly evolving understanding of the biology of that response has not been paralleled by the development of successful new treatment. The COVID-19 pandemic has begun to change this revealing the promise of distinct therapeutic approaches and the feasibility of new approaches to evaluate them. We review the history of mediator-targeted therapy for sepsis and explore the conceptual, biological, technological, and organizational challenges that must be addressed to enable the development of effective treatments for a leading cause of global morbidity and mortality.

A Robust and Generalizable Immune-Related Signature for Sepsis Diagnostics

High-throughput sequencing can detect tens of thousands of genes in parallel, providing opportunities for improving the diagnostic accuracy of multiple diseases including sepsis, which is an aggressive inflammatory response to infection that can cause organ failure and death. Early screening of sepsis is essential in clinic, but no effective diagnostic biomarkers are available yet. Here, we present a novel method, Recurrent Logistic Regression, to identify diagnostic biomarkers for sepsis from the blood transcriptome data. A panel including five immune-related genes, LRRN3, IL2RB, FCER1A, TLR5, and S100A12, are determined as diagnostic biomarkers (LIFTS) for sepsis. LIFTS discriminates patients with sepsis from normal controls in high accuracy (AUROC = 0.9959 on average; IC = [0.9722-1.0]) on nine validation cohorts across three independent platforms, which outperforms existing markers. Our analysis determined an accurate prediction model and reproducible transcriptome biomarkers that can lay a foundation for clinical diagnostic tests and biological mechanistic studies.

Evidence-based updates to the 2021 Surviving Sepsis Campaign guidelines: Part 1: Background, pathophysiology, and emerging treatments

ABSTRACT

Sepsis identification and treatment has changed significantly over the last few decades. Despite this, sepsis is still associated with significant morbidity and mortality. This first of a two-part series reviews the history of modern sepsis and presents new research in pathophysiology, treatment, and postsepsis care.

On the Move-Sensitive Fluorescent Aptassay on Board Catalytic Micromotors for the Determination of Interleukin-6 in Ultra-Low Serum Volumes for Neonatal Sepsis Diagnostics

A graphene oxide/nickel/platinum nanoparticle micromotor (MM)-based fluorescent aptassay is proposed to determine interleukin-6 (IL-6) in serum samples from low-birth-weight infants (gestational age of less than 32 weeks and birthweight below 1000 g) with sepsis suspicion. In this kind of patients, IL-6 has demonstrated good sensitivity and specificity for the diagnosis of sepsis, both for early and late onset sepsis. The approach was based on the adsorption of the aptamer for IL-6 tagged with 6-FAM as a fluorescent label (Apt_IL-6, λ_em = 520 nm) on the graphene oxide external layer (MM_GO-Apt_IL-6) inducing fluorescence quenching (OFF state) and a subsequent on-the-move affinity recognition of IL-6 from Apt_IL-6 (IL-6-Apt_IL-6 complex) recovering the fluorescence (ON state). An aptamer against IL-6 was selected and developed by the systematic evolution of ligands by exponential enrichment technology. This approach displayed a suitable linear range of 0.07-1000 pg mL^-1 (r = 0.995) covering the cut-off and clinical practice levels, allowing direct determination without any dilution and simplifying the analysis as well as exhibiting an excellent sensitivity (LOD = 0.02 pg mL^-1) in ultralow volumes of diagnostic clinical samples (2 μL). A high agreement between IL-6 levels obtained from our MM-based approach and the method used by the Hospital was obtained (relative error < 3%). The MM-based aptassay is competitive in comparison with that of the Hospital, in terms of a significant reduction of the sample volume (15 times less) and enhanced sensitivity, employing similar analysis times. These results position MM technology with enough potential to achieve high sensitivities in low sample volumes, opening new avenues in diagnosis based on low sample volumes.

DIAGNOSTIC ACCURACY AND ADDED VALUE OF INFECTION BIOMARKERS IN PATIENTS WITH POSSIBLE SEPSIS IN THE EMERGENCY DEPARTMENT

ABSTRACT

Background: Biomarkers for early recognition of infection are warranted. The hypothesis of this study was that calprotectin, C-reactive protein (CRP), IL-6 and procalcitonin (PCT), alone or in combination, provide clinically useful information to the clinicians for early identification of infection in patients with possible sepsis in the emergency department (ED). Biomarker dynamics in the first week of hospitalization were explored. Methods: Adult patients in rapid response teams in the ED were included in a prospective observational study (n = 391). Patients who received antibiotics after biomarker availability were excluded. The ED clinician (EDC) decision whether to start antibiotics was registered. Calprotectin, CRP, IL-6, and PCT were analyzed in blood samples drawn within 15 min after ED arrival and in a subgroup for 1 week. Infection likelihood was evaluated post hoc . Results: In identifying patients with infection, CRP (area under the receiver operating characteristic curve [AUC], 0.913) and IL-6 (AUC, 0.895) were superior to calprotectin (AUC, 0.777) and PCT (AUC, 0.838). The best regression model predicting infections included EDC, CRP, and IL-6. Using optimal cutoff values, CRP and IL-6 in combination reached 95% positive and 90% negative predictive values for infection. The EDC undertreated or overtreated 65 of 391 patients (17%), and CRP and IL-6 optimal cutoff values could correct this in 32 of 65 patients (49%). Longitudinal samples revealed that IL-6 peaked in the ED, whereas CRP and PCT peaked later. Conclusion: C-reactive protein and IL-6 were superior to calprotectin and PCT for recognizing infection in patients with possible sepsis in the ED. Combining these two biomarkers with different dynamics improved recognition of infection and could aid clinical management in rapid response teams in the ED.

Red blood cell distribution width as prognostic factor in sepsis: A new use for a classical parameter

PURPOSE

To evaluate Red blood cell distribution width (RDW) as a sepsis prognostic biomarker.

METHODS

203 septic patients admitted to the ICU. Analysis of RDW dynamics, hospital mortality discrimination ability and the added value when incorporated to the SOFA, LODS, SAPS-II and APACHE-II scores using the AUC-ROC.

RESULTS

Non-survivors presented higher RDW values during the first week after ICU admission (p = 0.048). Only SOFA and RDW were independently associated with mortality when adjusted by Charlson, immunosuppression, nosocomial infection, NEWS2, SAPS-II, septic shock and haemoglobin (p < 0.05). After adjustment, AUC-ROC was 0.827, 0.822, 0.824, 0.834 and 0.812 for each model including admission, 24, 48 and 72-h and 7-days RDW, respectively. When added to the scores, 24-h RDW and admission RDW improved their discrimination ability (SOFA AUC-ROC = 0.772 vs 0.812 SOFA + admission RDW, p = 0.041; LODS AUC-ROC = 0.687 vs 0.710, p = 0.002; SAPS-II AUC-ROC = 0.734 vs 0.785, p = 0.021; APACHE-II AUC-ROC = 0.672 vs 0.755, p = 0.003). Admission RDW with SOFA presented the better discrimination ability for mortality.

CONCLUSION

RDW is an independent prognostic marker of death in septic patients admitted in the ICU that improves SOFA, LODS, APACHE-II and SAPS-II discrimination ability. This parameter could be incorporated to the prognostic scores as a marker of systemic dysfunction and dysregulated inflammatory response.

The role of proteomics and metabolomics in severe infections

PURPOSE OF REVIEW

Severe infections are a common cause of ICU admission, with a high morbidity and mortality. Omics, namely proteomics and metabolomics, aim to identify, characterize, and quantify biological molecules to achieve a systems-level understanding of disease. The aim of this review is to provide a clear overview of the current evidence of the role of proteomics and metabolomics in severe infections.

RECENT FINDINGS

Proteomics and metabolomics are technologies that are being used to explore new markers of diagnosis and prognosis, clarify mechanisms of disease, and consequently discover potential targets of therapy and finally of a better disease phenotyping. These technologies are starting to be used but not yet in clinical use.

SUMMARY

Our traditional way of approaching the disease as sepsis is believing that a process can be broken into its parts and that the whole can be explained by the sum of each part. This approach is highly reductionist and does not take the system complexity nor the nonlinear dynamics of the processes. Proteomics and metabolomics allow the analysis of several proteins and metabolites simultaneously, thereby generating diagnostic and prognostic signatures. An exciting future prospect for proteomics and metabolomics is their employment towards precision medicine.

Biomarkers for the Prediction and Judgement of Sepsis and Sepsis Complications: A Step towards precision medicine?

Sepsis and septic shock are a major public health concern and are still associated with high rates of morbidity and mortality. Whilst there is growing understanding of different phenotypes and endotypes of sepsis, all too often treatment strategies still only employ a “one-size-fits-all” approach. Biomarkers offer a unique opportunity to close this gap to more precise treatment approaches by providing insight into clinically hidden, yet complex, pathophysiology, or by individualizing treatment pathways. Predicting and evaluating systemic inflammation, sepsis or septic shock are essential to improve outcomes for these patients. Besides opportunities to improve patient care, employing biomarkers offers a unique opportunity to improve clinical research in patients with sepsis. The high rate of negative clinical trials in this field may partly be explained by a high degree of heterogeneity in patient cohorts and a lack of understanding of specific endotypes or phenotypes. Moving forward, biomarkers can support the selection of more homogeneous cohorts, thereby potentially improving study conditions of clinical trials. This may finally pave the way to a precision medicine approach to sepsis, septic shock and complication of sepsis in the future.

A cytokine/PTX3 prognostic index as a predictor of mortality in sepsis

Background

Early prognostic stratification of patients with sepsis is a difficult clinical challenge. Aim of this study was to evaluate novel molecules in association with clinical parameters as predictors of 90-days mortality in patients admitted with sepsis at Humanitas Research Hospital.

Methods

Plasma samples were collected from 178 patients, diagnosed based on Sepsis-3 criteria, at admission to the Emergency Department and after 5 days of hospitalization. Levels of pentraxin 3 (PTX3), soluble IL-1 type 2 receptor (sIL-1R2), and of a panel of pro- and anti-inflammatory cytokines were measured by ELISA. Cox proportional-hazard models were used to evaluate predictors of 90-days mortality.

Results

Circulating levels of PTX3, sIL-1R2, IL-1β, IL-6, IL-8, IL-10, IL-18, IL-1ra, TNF-α increased significantly in sepsis patients on admission, with the highest levels measured in shock patients, and correlated with SOFA score (PTX3: r=0.44, p&lt;0.0001; sIL-1R2: r=0.35, p&lt;0.0001), as well as with 90-days mortality. After 5 days of hospitalization, PTX3 and cytokines, but not sIL-1R2 levels, decreased significantly, in parallel with a general improvement of clinical parameters. The combination of age, blood urea nitrogen, PTX3, IL-6 and IL-18, defined a prognostic index predicting 90-days mortality in Sepsis-3 patients and showing better apparent discrimination capacity than the SOFA score (AUC=0.863, 95% CI: 0.780−0.945 vs. AUC=0.727, 95% CI: 0.613-0.840; p=0.021 respectively).

Conclusion

These data suggest that a prognostic index based on selected cytokines, PTX3 and clinical parameters, and hence easily adoptable in clinical practice, performs in predicting 90-days mortality better than SOFA. An independent validation is required.

Association of Procalcitonin with the Patient’s Infection Characteristics and Prognosis after Hematopoietic Stem Cell Transplantation

Objective

To study whether procalcitonin (PCT) is an important indicator of infection with or without agranulocytosis and to reveal whether PCT can distinguish between infected sites and affect prognosis after hematopoietic stem cell transplantation (HSCT).

Method

In the present study, 682 patients with HSCT were enrolled, and their clinical characteristics were noted. Their blood culture and inflammatory and biochemical indicators were studied. The patients were divided into respective groups according to the degree of agranulocytosis, type of bacterial infection, infected sites, and prognosis.

Results

The PCT, CRP, and D-dimer levels were significantly improved in patients with positive blood culture results compared to the case for those with negative blood culture results. The PCT level was the highest in the gram-negative group. The levels of PCT and D-dimer were significantly elevated in patients with infection and agranulocytosis after HSCT compared to those in the nonagranulocytosis cohort. Interestingly, no significant difference in the PCT level was observed among any of the eight foci. Lower PCT levels were associated with higher survival in patients with infection after HSCT.

Conclusion

Among patients that underwent HSCT, PCT levels were significantly elevated in those with infection and agranulocytosis, with the levels being specifically high in the gram-negative group. Moreover, lower PCT levels were associated with higher survival in patients with infection after HSCT.

The End of “One Size Fits All” Sepsis Therapies: Toward an Individualized Approach

Sepsis, defined as life-threatening organ dysfunction caused by a dysregulated host response to an infection, remains a major challenge for clinicians and trialists. Despite decades of research and multiple randomized clinical trials, a specific therapeutic for sepsis is not available. The evaluation of therapeutics targeting components of host response anomalies in patients with sepsis has been complicated by the inability to identify those in this very heterogeneous population who are more likely to benefit from a specific intervention. Additionally, multiple and diverse host response aberrations often co-exist in sepsis, and knowledge of which dysregulated biological organ system or pathway drives sepsis-induced pathology in an individual patient is limited, further complicating the development of effective therapies. Here, we discuss the drawbacks of previous attempts to develop sepsis therapeutics and delineate a future wherein interventions will be based on the host response profile of a patient.

Prevalence and Long-Term Prognosis of Post-Intensive Care Syndrome after Sepsis: A Single-Center Prospective Observational Study

Post-intensive care syndrome (PICS) comprises physical, mental, and cognitive disorders following a severe illness. The impact of PICS on long-term prognosis has not been fully investigated. This study aimed to: (1) clarify the frequency and clinical characteristics of PICS in sepsis patients and (2) explore the relationship between PICS occurrence and 2-year survival. Patients with sepsis admitted to intensive care unit were enrolled. Data on patient background; clinical information since admission; physical, mental, and cognitive impairments at 3-, 6-, and 12-months post-sepsis onset; 2-year survival; and cause of death were obtained from electronic medical records and telephonic interviews with patients and their families. At 3 months, comparisons of variables were undertaken in the PICS group and the non-PICS group. Among the 77 participants, the in-hospital mortality rate was 11% and the 2-year mortality rate was 52%. The frequencies of PICS at 3, 6, and 12 months were 70%, 60%, and 35%, respectively. The 2-year survival was lower in the PICS group than in the non-PICS group (54% vs. 94%, p < 0.01). More than half of the survivors had PICS at 3 and 6 months after sepsis. Among survivors with sepsis, those who developed PICS after 3 months had a lower 2-year survival.

Expression of SOCS1 Protein in Endotoxin-Tolerant Mouse Model and Its Regulation Mechanism by mir-150

In order to investigate the expression of Suppressor of Cytokine Signaling 1 (SOCS1) and its regulatory mechanism by mir-150 in a lipopolysaccharide (LPS) tolerant mouse model of endotoxin, a total of 60 male BALB/C mice were randomly divided into 2 groups. The LPS is used to construct the endotoxin resistant mouse model and the mice are included in the model group (n = 30), 0.9% sodium chloride injection is used to construct the normal control group (n = 30). And tumor necrosis factor-α (TNF-α) is determined by Elisa to determine whether the model was successfully constructed. The correlation between SOCS1 protein and mir-150 is analyzed by the Pearson correlation coefficient. In the experiments, the results show that the expression of TNF-α in the macrophage fluid of the model group is significantly decreased (P < 0.05), indicating that the endotoxin tolerance mouse model is successfully constructed, so the secretion of TNF-α is reduced.

Designing electrochemical microfluidic multiplexed biosensors for on-site applications

Clinical assessment based on a single biomarker is in many circumstances not sufficient for adequate diagnosis of a disease or for monitoring its therapy. Multiplexing, the measurement of multiple analytes from one sample and/or of the same target from different samples simultaneously, could enhance the accuracy of the diagnosis of diseases and their therapy success. Thus, there is a great and urgent demand for multiplexed biosensors allowing a low-cost, easy-to-use, and rapid on-site testing. In this work, we present a simple, flexible, and highly scalable strategy for implementing microfluidic multiplexed electrochemical biosensors (BiosensorX). Our technology is able to detect 4, 6, or 8 (different) analytes or samples simultaneously using a sequential design concept: multiple immobilization areas, where the assay components are adsorbed, followed by their individual electrochemical cells, where the amperometric signal readout takes place, within a single microfluidic channel. Here, first we compare vertical and horizontal designs of BiosensorX chips using a model assay. Owing to its easier handling and superior fluidic behavior, the vertical format is chosen as the final multiplexed chip design. Consequently, the feasibility of the BiosensorX for multiplexed on-site testing is successfully demonstrated by measuring meropenem antibiotics via an antibody-free β-lactam assay. The multiplexed biosensor platform introduced can be further extended for the simultaneous detection of other anti-infective agents and/or biomarkers (such as renal or inflammation biomarkers) as well as different (invasive and non-invasive) sample types, which would be a major step towards sepsis management and beyond.

Hepcidin discriminates sepsis from other critical illness at admission to intensive care

Initial differential diagnosis and prognosis for patients admitted to intensive care with suspected sepsis remain arduous. Hepcidin has emerged as a potential biomarker for sepsis. Here we report data on the relevance of levels of hepcidin versus other biomarkers as a diagnostic and prognostic tool for sepsis. 164 adult patients admitted to the intensive care unit (ICU) within 24 h upon arrival to the hospital were included. Blood samples collected daily for seven consecutive days and hepcidin levels, heparin binding protein (HBP) levels and standard biomarkers were determined. Blood cultures were initiated at inclusion. Clinical scores were evaluated daily and mortality after 28- and 180-days was recorded. One hundred of the patients were found to fulfil the criteria for sepsis whereas 64 did not. Hepcidin levels at admission were significantly higher in the septic than in the non-septic patients. In septic patients hepcidin levels declined significantly already at 24 h followed by a steady decline. A significant negative correlation was observed between hepcidin levels and SAPS 3 in patients with sepsis. Hepcidin levels at inclusion were significantly higher among septic patients that survived 180-days and predicted mortality. Our data show that hepcidin levels are indicative of sepsis in patients admitted to the ICU and has a prognostic value for mortality.

Vascular Proteome Responses Precede Organ Dysfunction in a Murine Model of Staphylococcus aureus Bacteremia

Vascular dysfunction and organ failure are two distinct, albeit highly interconnected, clinical outcomes linked to morbidity and mortality in human sepsis. The mechanisms driving vascular and parenchymal damage are dynamic and display significant molecular cross talk between organs and tissues. Therefore, assessing their individual contribution to disease progression is technically challenging. Here, we hypothesize that dysregulated vascular responses predispose the organism to organ failure. To address this hypothesis, we have evaluated four major organs in a murine model of Staphylococcus aureus sepsis by combining in vivo labeling of the endothelial cell surface proteome, data-independent acquisition (DIA) mass spectrometry, and an integrative computational pipeline. The data reveal, with unprecedented depth and throughput, that a septic insult evokes organ-specific proteome responses that are highly compartmentalized, synchronously coordinated, and significantly correlated with the progression of the disease. These responses include abundant vascular shedding, dysregulation of the intrinsic pathway of coagulation, compartmentalization of the acute phase response, and abundant upregulation of glycocalyx components. Vascular cell surface proteome changes were also found to precede bacterial invasion and leukocyte infiltration into the organs, as well as to precede changes in various well-established cellular and biochemical correlates of systemic coagulopathy and tissue dysfunction. Importantly, our data suggest a potential role for the vascular proteome as a determinant of the susceptibility of the organs to undergo failure during sepsis. IMPORTANCE Sepsis is a life-threatening response to infection that results in immune dysregulation, vascular dysfunction, and organ failure. New methods are needed for the identification of diagnostic and therapeutic targets. Here, we took a systems-wide approach using data-independent acquisition (DIA) mass spectrometry to track the progression of bacterial sepsis in the vasculature leading to organ failure. Using a murine model of S. aureus sepsis, we were able to quantify thousands of proteins across the plasma and parenchymal and vascular compartments of multiple organs in a time-resolved fashion. We showcase the profound proteome remodeling triggered by sepsis over time and across these compartments. Importantly, many vascular proteome alterations precede changes in traditional correlates of organ dysfunction, opening a molecular window for the discovery of early markers of sepsis progression.

Cervical sympathetic trunk transection alleviates acute lung injury caused by intestinal obstruction via inhibition of phospholipase A2 in rats

Background

Intestinal obstruction can result in inflammatory injury to distant organs, especially the lungs. Stellate ganglion block (SGB) provides sympathetic nervous homeostasis and inhibits the systemic inflammatory response. This study aimed to investigate whether SGB can alleviate acute lung injury by inhibiting phospholipase A₂ expression in rats.

Methods

Thirty healthy male Sprague–Dawley rats were divided into three groups: C group (sham-operated); CLP group (cecal ligation and puncture with intestinal obstruction), and cervical sympathetic trunk transection (CSTT) group (transection of the cervical sympathetic trunk following CLP).Arterial blood samples were obtained to determine the ratio of partial arterial pressure of oxygen (PaO₂) to fraction of oxygen in inspired air (FiO₂). Venous blood samples were used to evaluate the serum concentrations of chemokines, tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-10 using enzyme-linked immunosorbent assays. Following euthanasia, the lungs were isolated to estimate the wet/dry lung weight (W/D) ratio, evaluate the pathological damage to lung tissues on microscopy, and determine secretory-type phospholipase A₂ (sPLA₂) expression using western blotting.

Results

Rats in the CLP group showed increased fatigue, decreased activity levels, and coarse, gray hair. The levels of chemokines, TNF-α, and IL-6 in the CLP and CSTT groups were higher than those in the C group. However, the levels were lower in the CSTT group than those in the CLP group. IL-10 levels in the CLP group were higher and lower than those in the C and CSTT groups, respectively. W/D ratios and PaO₂/FiO₂ in the CLP and CSTT groups were higher than those in the C group, whereas these ratios in the CSTT group were lower than those in the CLP group. No lung injury was noted in group C, and the lung injury scores were lower in the CSTT group than those in the CLP group. sPLA₂ expression levels in the CLP group were higher than those in the C group, whereas these levels in the CSTT group were lower than those in the CLP group.

Conclusions

sPLA₂ overexpression in the lungs may be a pathogenic factor in acute lung injury. CSTT alleviated acute lung injury by inhibiting sPLA₂ expression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12871-022-01814-2.

Platelet-to-Lymphocyte Ratio (PLR) Is Not a Predicting Marker of Severity but of Mortality in COVID-19 Patients Admitted to the Emergency Department: A Retrospective Multicenter Study

(1) Introduction: In the present study, we investigate the prognostic value of platelet-to-lymphocyte ratio (PLR) as a marker of severity and mortality in COVID-19 infection. (2) Methods: Between 1 March and 30 April 2020, we conducted a multicenter, retrospective cohort study of patients with moderate to severe coronavirus 19 (COVID-19), all of whom were hospitalized after being admitted to the emergency department (ED). (3) Results: A total of 1035 patients were included in our study. Neither lymphocytes, platelets or PLR were associated with disease severity. Lymphocyte count was significantly lower and PLR values were significantly higher in the group of patients who died, and both were associated with mortality in the univariate analysis (OR: 0.524, 95% CI: (0.336−0.815), p = 0.004) and (OR: 1.001, 95% CI: (1.000−1.001), p = 0.042), respectively. However, the only biological parameter significantly associated with mortality in the multivariate analysis was platelet count (OR: 0.996, 95% CI: (0.996−1.000), p = 0.027). The best PLR value for predicting mortality in COVID-19 was 356.6 (OR: 3.793, 95% CI: (1.946−7.394), p < 0.001). (4) Conclusion: A high PLR value is however associated with excess mortality.

Modes of action and diagnostic value of miRNAs in sepsis

Sepsis is a clinical syndrome defined as a dysregulated host response to infection resulting in life-threatening organ dysfunction. Sepsis is a major public health concern associated with one in five deaths worldwide. Sepsis is characterized by unbalanced inflammation and profound and sustained immunosuppression, increasing patient susceptibility to secondary infections and mortality. microRNAs (miRNAs) play a central role in the control of many biological processes, and deregulation of their expression has been linked to the development of oncological, cardiovascular, neurodegenerative and metabolic diseases. In this review, we discuss the role of miRNAs in sepsis pathophysiology. Overall, miRNAs are seen as promising biomarkers, and it has been proposed to develop miRNA-based therapies for sepsis. Yet, the picture is not so straightforward because of the versatile and dynamic features of miRNAs. Clearly, more research is needed to clarify the expression and role of miRNAs in sepsis, and to promote the use of miRNAs for sepsis management.

Delta-like canonical Notch ligand 1 is predictive for sepsis and acute kidney injury in surgical intensive care patients

The early identification of sepsis in surgical intensive care patients is challenging due to the physiological postoperative alterations of vital signs and inflammatory biomarkers. Soluble Delta-like protein 1 (sDLL1) may be a potential discriminatory biomarker for this purpose. For this reason, this study aimed to evaluate sDLL1 for the identification of sepsis in a cohort of surgical intensive care patients. This study comprises a secondary analysis of a prospective observational study including 80 consecutive patients. The study groups included 20 septic shock patients, 20 patients each undergoing major abdominal surgery (MAS) and cardiac artery bypass surgery (CABG), and 20 matched control subjects (CTRL). The surveillance period was 72 h. The plasma concentration of sDLL1 was measured with ELISA. The plasma levels of sDLL1 were significantly elevated in septic patients compared to both surgical cohorts (septic vs. all postoperative time points, data are shown as median and interquartile range [IQR]; septic shock: 17,363 [12,053–27,299] ng/mL, CABG 10,904 [8692–16,250] ng/mL; MAS 6485 [4615–9068] ng/mL; CTRL 5751 [3743–7109] ng/mL; septic shock vs. CABG: p < 0.001; septic shock vs. MAS: p < 0.001). ROC analysis showed a sufficient prediction of sepsis with limited specificity (AUCROC 0.82 [0.75–0.82], sensitivity 84%, specificity 68%). The plasma levels of sDLL correlated closely with renal parameters (creatinine: correlation coefficient = 0.60, r² = 0.37, p < 0.0001; urea: correlation coefficient = 0.52, r² = 0.26, p < 0.0001), resulting in a good predictive performance of sDLL1 for the identification of acute kidney injury (AKI; AUCROC 0.9 [0.82–0.9], sensitivity 83%, specificity 91%). By quantifying the plasma concentration of sDLL1, sepsis can be discriminated from the physiological postsurgical inflammatory response in abdominal and cardiac surgical patients. However, sDLL1 has only limited specificity for the detection of sepsis in cardiac surgical patients, which may be explained by impaired renal function. Based on these findings, this study identifies the predictive value of sDLL1 for the detection of AKI, making it a potential biomarker for surgical intensive care patients.

Trial registration DRKS00013584, Internet Portal of the German Clinical Trials Register (DRKS), registration date 11.07.2018, https://www.drks.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00013584.

Dysregulated autophagy-related genes in septic cardiomyopathy: Comprehensive bioinformatics analysis based on the human transcriptomes and experimental validation

Septic cardiomyopathy (SCM) is severe organ dysfunction caused by sepsis that is associated with poor prognosis, and its pathobiological mechanisms remain unclear. Autophagy is a biological process that has recently been focused on SCM, yet the current understanding of the role of dysregulated autophagy in the pathogenesis of SCM remains limited and uncertain. Exploring the molecular mechanisms of disease based on the transcriptomes of human pathological samples may bring the closest insights. In this study, we analyzed the differential expression of autophagy-related genes in SCM based on the transcriptomes of human septic hearts, and further explored their potential crosstalk and functional pathways. Key functional module and hub genes were identified by constructing a protein–protein interaction network. Eight key genes (CCL2, MYC, TP53, SOD2, HIF1A, CTNNB1, CAT, and ADIPOQ) that regulate autophagy in SCM were identified after validation in a lipopolysaccharide (LPS)-induced H9c2 cardiomyoblast injury model, as well as the autophagic characteristic features. Furthermore, we found that key genes were associated with abnormal immune infiltration in septic hearts and have the potential to serve as biomarkers. Finally, we predicted drugs that may play a protective role in SCM by regulating autophagy based on our results. Our study provides evidence and new insights into the role of autophagy in SCM based on human septic heart transcriptomes, which would be of great benefit to reveal the molecular pathological mechanisms and explore the diagnostic and therapeutic targets for SCM.