Source-specific host response and outcomes in critically ill patients with sepsis: a prospective cohort study

Innate immune response in acute critical illness: a narrative review

BACKGROUND

Activation of innate immunity is a first line of host defense during acute critical illness (ACI) that aims to contain injury and avoid tissue damages. Aberrant activation of innate immunity may also participate in the occurrence of organ failures during critical illness. This review aims to provide a narrative overview of recent advances in the field of innate immunity in critical illness, and to consider future potential therapeutic strategies.

MAIN TEXT

Understanding the underlying biological concepts supporting therapeutic strategies modulating immune response is essential in decision-making. We will develop the multiple facets of innate immune response, especially its cellular aspects, and its interaction with other defense mechanisms. We will first describe the pathophysiological mechanisms of initiation of innate immune response and its implication during ACI. We will then develop the amplification of innate immunity mediated by multiple effectors. Our review will mainly focus on myeloid and lymphoid cellular effectors, the major actors involved in innate immune-mediated organ failure. We will third discuss the interaction and integration of innate immune response in a global view of host defense, thus considering interaction with non-immune cells through immunothrombosis, immunometabolism and long-term reprogramming via trained immunity. The last part of this review will focus on the specificities of the immune response in children and the older population.

CONCLUSIONS

Recent understanding of the innate immune response integrates immunity in a highly dynamic global vision of host response. A better knowledge of the implicated mechanisms and their tissue-compartmentalization allows to characterize the individual immune profile, and one day eventually, to develop individualized bench-to-bedside immunomodulation approaches as an adjuvant resuscitation strategy.

Proteome analysis develops novel plasma proteins classifier in predicting the mortality of COVID-19

COVID-19 has been a global concern for 3 years, however, consecutive plasma protein changes in the disease course are currently unclear. Setting the mortality within 28 days of admission as the main clinical outcome, plasma samples were collected from patients in discovery and independent validation groups at different time points during the disease course. The whole patients were divided into death and survival groups according to their clinical outcomes. Proteomics and pathway/network analyses were used to find the differentially expressed proteins and pathways. Then, we used machine learning to develop a protein classifier which can predict the clinical outcomes of the patients with COVID-19 and help identify the high-risk patients. Finally, a classifier including C-reactive protein, extracellular matrix protein 1, insulin-like growth factor-binding protein complex acid labile subunit, E3 ubiquitin-protein ligase HECW1 and phosphatidylcholine-sterol acyltransferase was determined. The prediction value of the model was verified with an independent patient cohort. This novel model can realize early prediction of 28-day mortality of patients with COVID-19, with the area under curve 0.88 in discovery group and 0.80 in validation group, superior to 4C mortality and E-CURB65 scores. In total, this work revealed a potential protein classifier which can assist in predicting the outcomes of COVID-19 patients and providing new diagnostic directions.

Predictive Value of Multiple Scoring Systems in the Prognosis of Septic Patients with Different Infection Sites: Analysis of the Medical Information Mart for the Intensive Care IV Database

The heterogeneity nature of sepsis is significantly impacted by the site of infection. This study aims to explore the predictive value of multiple scoring systems in assessing the prognosis of septic patients across different infection sites. Data for this retrospective cohort study were extracted from the Medical Information Mart for Intensive Care IV database (MIMIC-IV) (v2.2). Adult patients meeting the criteria for sepsis 3.0 and admitted to the intensive care unit (ICU) were enrolled. Infection sites included were pneumonia, urinary tract infection (UTI), cellulitis, abdominal infection, and bacteremia. The primary outcome assessed was 28-day mortality. The sequential Organ Failure Assessment (SOFA) score, Oxford Acute Severity of Illness Score (OASIS), and Logistic Organ Dysfunction System (LODS) score were compared. Binomial logistic regression analysis was conducted to evaluate the association between these variables and mortality. Additionally, differences in the area under the curve (AUC) of receiver operating characteristic (ROC) among the scoring systems were analyzed. A total of 4721 patients were included in the analysis. The average 28-day mortality rate was 9.4%. Significant differences were observed in LODS, OASIS, and SOFA scores between the 28-day survival and non-survival groups across different infection sites (p < 0.01). In the pneumonia group and abdominal infection group, both the LODS and OASIS scoring systems emerged as independent risk factors for mortality in septic patients (odds ratio [OR]: 1.165, 95% confidence interval [CI]: 1.109-1.224, p < 0.001; OR: 1.047, 95% CI: 1.028-1.065, p < 0.001) (OR: 1.200, 95% CI: 1.091-1.319, p < 0.001; OR: 1.060, 95% CI: 1.025-1.095, p < 0.001). For patients with UTI, the LODS, OASIS, and SOFA scoring systems were identified as independent risk factors for mortality (OR: 1.142, 95% CI: 1.068-1.220, p < 0.001; OR: 1.062, 95% CI: 1.037-1.087, p < 0.001; OR: 1.146, 95% CI: 1.046-1.255, p = 0.004), with the AUC of LODS score and OASIS significantly higher than that of the SOFA score (p = 0.006). Among patients with cellulitis, the OASIS and SOFA scoring systems were identified as independent risk factors for mortality (OR: 1.055, 95% CI: 1.007-1.106, p = 0.025; OR: 1.187, 95% CI: 1.005-1.403, p = 0.044), with no significant difference in prognosis prediction observed (p = 0.243). In the bacteremia group, the LODS scoring system was identified as an independent risk factor for mortality (OR: 1.165, 95% CI: 1.109-1.224, p < 0.001). The findings suggest that LODS scores offer better prognostic accuracy for predicting the mortality risk in septic patients with pneumonia, abdominal infections, bacteremia, and UTI compared to SOFA scores.

Revealing the role of Peg13: A promising therapeutic target for mitigating inflammation in sepsis

To investigate the role of Peg13 in modulating the inflammatory response in sepsis, we established Lipopolysaccharide (LPS)-induced 293T cells and mouse models. Peg13 expression was assessed at various time points after infection using RT-qPCR. The levels of high mobility group box 1 (HMGB1) and interleukin-6 (IL-6) were quantified through ELISA. A total of 44 septic patients and 36 healthy participants were recruited to measure Peg13 and HMGB1 levels in the blood. Peg13 demonstrated significant down-regulation in the supernatant of LPS-induced 293T cells and in the blood of LPS-induced mice. Moreover, the levels of proinflammatory cytokines HMGB1 and IL-6 were elevated in both the supernatant of LPS-induced cell models and blood specimens from LPS-induced murine models, and this elevation could be notably reduced by Peg13 suppression. In a clinical context, Peg13 and HMGB1 levels were higher in septic patients compared to healthy subjects. Peg13 exhibited a negative correlation with HMGB1, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) among septic patients. Peg13 mitigates the inflammatory response by reducing the release of proinflammatory cytokines HMGB1 and IL-6 in sepsis, presenting a potential therapeutic target for alleviating inflammation in sepsis treatment.

Distinct patterns of vital sign and inflammatory marker responses in adults with suspected bloodstream infection

OBJECTIVES

To identify patterns in inflammatory marker and vital sign responses in adult with suspected bloodstream infection (BSI) and define expected trends in normal recovery.

METHODS

We included patients ≥16 y from Oxford University Hospitals with a blood culture taken between 1-January-2016 and 28-June-2021. We used linear and latent class mixed models to estimate trajectories in C-reactive protein (CRP), white blood count, heart rate, respiratory rate and temperature and identify CRP response subgroups. Centile charts for expected CRP responses were constructed via the lambda-mu-sigma method.

RESULTS

In 88,348 suspected BSI episodes; 6908 (7.8%) were culture-positive with a probable pathogen, 4309 (4.9%) contained potential contaminants, and 77,131(87.3%) were culture-negative. CRP levels generally peaked 1-2 days after blood culture collection, with varying responses for different pathogens and infection sources (p < 0.0001). We identified five CRP trajectory subgroups: peak on day 1 (36,091; 46.3%) or 2 (4529; 5.8%), slow recovery (10,666; 13.7%), peak on day 6 (743; 1.0%), and low response (25,928; 33.3%). Centile reference charts tracking normal responses were constructed from those peaking on day 1/2.

CONCLUSIONS

CRP and other infection response markers rise and recover differently depending on clinical syndrome and pathogen involved. However, centile reference charts, that account for these differences, can be used to track if patients are recovering line as expected and to help personalise infection.

Analysis of ceRNA Network and Identification of Potential Treatment Target and Biomarkers of Endothelial Cell Injury in Sepsis

Background: Sepsis is a complex clinical syndrome caused by a dysregulated host immune response to infection. This study aimed to identify a competing endogenous RNA (ceRNA) network that can greatly contribute to understanding the pathophysiological process of sepsis and determining sepsis biomarkers. Methods: The GSE100159, GSE65682, GSE167363, and GSE94717 datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene coexpression network analysis was performed to find modules possibly involved in sepsis. A long noncoding RNA-microRNA-messenger RNA (lncRNA-miRNA-mRNA) network was constructed based on the findings. Single-cell analysis was performed. Human umbilical vein endothelial cells were treated with lipopolysaccharide (LPS) to create an in vitro model of sepsis for network verification. Reverse transcription-polymerase chain reaction, fluorescence in situ hybridization, and luciferase reporter genes were used to verify the bioinformatic analysis. Result: By integrating data from three GEO datasets, we successfully constructed a ceRNA network containing 18 lncRNAs, 7 miRNAs, and 94 mRNAs based on the ceRNA hypothesis. The lncRNA ZFAS1 was found to be highly expressed in LPS-stimulated endothelial cells and may thus play a role in endothelial cell injury. Univariate and multivariate Cox analyses showed that only SLC26A6 was an independent predictor of prognosis in sepsis. Overall, our findings indicated that the ZFAS1/hsa-miR-449c-5p/SLC26A6 ceRNA regulatory axis may play a role in the progression of sepsis. Conclusion: The sepsis ceRNA network, especially the ZFAS1/hsa-miR-449c-5p/SLC26A6 regulatory axis, is expected to reveal potential biomarkers and therapeutic targets for sepsis management.

Monocyte state 1 (MS1) cells in critically ill patients with sepsis or non-infectious conditions: association with disease course and host response

BACKGROUND

Sepsis is a life-threatening condition arising from an aberrant host response to infection. Recent single-cell RNA sequencing investigations identified an immature bone-marrow-derived CD14+ monocyte phenotype with immune suppressive properties termed "monocyte state 1" (MS1) in patients with sepsis. Our objective was to determine the association of MS1 cell profiles with disease presentation, outcomes, and host response characteristics.

METHODS

We used the transcriptome deconvolution method (CIBERSORTx) to estimate the percentage of MS1 cells from blood RNA profiles of patients with sepsis admitted to the intensive care unit (ICU). We compared these profiles to ICU patients without infection and to healthy controls. Host response dysregulation was further studied by gene co-expression network and gene set enrichment analyses of blood leukocytes, and measurement of 15 plasma biomarkers indicative of pathways implicated in sepsis pathogenesis.

RESULTS

Sepsis patients (n = 332) were divided into three equally-sized groups based on their MS1 cell levels (low, intermediate, and high). MS1 groups did not differ in demographics or comorbidities. The intermediate and high MS1 groups presented with higher disease severity and more often had shock. MS1 cell abundance did not differ between survivors and non-survivors, or between patients who did or did not acquire a secondary infection. Higher MS1 cell percentages were associated with downregulation of lymphocyte-related and interferon response genes in blood leukocytes, with concurrent upregulation of inflammatory response pathways, including tumor necrosis factor signaling via nuclear factor-κB. Previously described sepsis host response transcriptomic subtypes showed different MS1 cell abundances, and MS1 cell percentages positively correlated with the "quantitative sepsis response signature" and "molecular degree of perturbation" scores. Plasma biomarker levels, indicative of inflammation, endothelial cell activation, and coagulation activation, were largely similar between MS1 groups. In ICU patients without infection (n = 215), MS1 cell percentages and their relation with disease severity, shock, and host response dysregulation were highly similar to those in sepsis patients.

CONCLUSIONS

High MS1 cell percentages are associated with increased disease severity and shock in critically ill patients with sepsis or a non-infectious condition. High MS1 cell abundance likely indicates broad immune dysregulation, entailing not only immunosuppression but also anomalies reflecting exaggerated inflammatory responses.

Glucocorticoid use in acute respiratory failure from pulmonary causes and association with early changes in the systemic host immune response

BACKGROUND

Glucocorticoids are commonly used in patients with or at-risk for acute respiratory distress syndrome (ARDS), but optimal use remains unclear despite well-conducted clinical trials. We performed a secondary analysis in patients previously enrolled in the Acute Lung Injury and Biospecimen Repository at the University of Pittsburgh. The primary aim of our study was to investigate early changes in host response biomarkers in response to real-world use of glucocorticoids in patients with acute respiratory failure due to ARDS or at-risk due to a pulmonary insult. Participants had baseline plasma samples obtained on study enrollment and on follow-up 3 to 5 days later to measure markers of innate immunity (IL-6, IL-8, IL-10, TNFr1, ST2, fractalkine), epithelial injury (sRAGE), endothelial injury (angiopoietin-2), and host response to bacterial infections (procalcitonin, pentraxin-3). In our primary analyses, we investigated the effect of receiving glucocorticoids between baseline and follow-up samples on host response biomarkers measured at follow-up by doubly robust inverse probability weighting analysis. In exploratory analyses, we examined associations between glucocorticoid use and previously characterized host response subphenotypes (hyperinflammatory and hypoinflammatory).

RESULTS

67 of 148 participants (45%) received glucocorticoids between baseline and follow-up samples. Dose and type of glucocorticoids varied. Regimens that used hydrocortisone alone were most common (37%), and median daily dose was equivalent to 40 mg methylprednisolone (interquartile range: 21, 67). Participants who received glucocorticoids were more likely to be female, to be on immunosuppressive therapy at baseline, and to have higher baseline levels of ST-2, fractalkine, IL-10, pentraxin-3, sRAGE, and TNFr1. Glucocorticoid use was associated with decreases in IL-6 and increases in fractalkine. In exploratory analyses, glucocorticoid use was more frequent in participants in the hyperinflammatory subphenotype (58% vs 40%, p = 0.05), and was not associated with subphenotype classification at the follow-up time point (p = 0.16).

CONCLUSIONS

Glucocorticoid use varied in a cohort of patients with or at-risk for ARDS and was associated with early changes in the systemic host immune response.

Appropriateness of antibiotic prescribing for patients with sepsis in rural hospital emergency departments

DESIGN/PARTICIPANTS

This was a multicentre retrospective cohort study of adult patients (≥18 years) presenting with a process associated International Classification of Diseases code (ICD-AM-10) pertaining to sepsis between January 2017 and July 2020 to rural Emergency Departments.

MAIN OUTCOME MEASURES

Our primary outcome was antibiotic appropriateness as defined by the Australian Therapeutic Guidelines (for antibiotic selection relative to infecting source) and the National Antimicrobial Prescribing Survey tool. Our secondary outcome was in-hospital mortality.

METHODS

Relevant clinical and non-clinical, physiological and laboratory data were collected retrospectively. Multivariate logistic regression was used to estimate the odds of both inappropriate antibiotic prescribing and in-hospital mortality based on clinical and non-clinical factors.

RESULTS

A total of 378 patients were included who primarily presented with sepsis of unknown origin (36.8%), a genitourinary (22.22%) or respiratory (18.78%) source. Antibiotics were appropriately prescribed in 59% of patients. A positive Quick Sequential Organ Failure Assessment score (qSOFA) (odds ratio [OR] = 0.49; 95% confidence interval [CI], 0.29-0.83), a respiratory infection source (OR = 0.5; 95% CI, 0.29-0.86) and documented allergy (OR = 0.42; 95% CI, 0.25-0.72) were associated with a lower risk of appropriate prescribing in multivariate analysis. Forty-one percent of patients received antibiotics within 1 h of presentation. Inappropriate antibiotic prescribing was not associated with in-hospital mortality.

CONCLUSION

The rates of appropriate antibiotic prescribing in rural Emergency Departments for patients presenting with sepsis is low, but comparable to other referral metropolitan centres.

Determining the Association Between the Origin of Sepsis and the Severity of Sepsis in Intensive Care Unit (ICU) Patients Using Acute Physiology and Chronic Health Evaluation (APACHE) IV

Objective The objective of this study is to compare the outcomes of hospital mortality, the requirement of invasive ventilation, vasopressor requirement, duration of vasopressor requirement, and duration of intensive care unit (ICU) stay among the different causes of sepsis and to determine which cause of sepsis had the most severe outcomes. Methods A retrospective chart review was done in critically ill adult patients who were admitted with sepsis to the ICU from July 2017 until July 2019. Acute Physiology and Chronic Health Evaluation (APACHE) IV scores were calculated on patients admitted to ICU on day one of ICU admission. Each patient was then evaluated for outcomes of hospital mortality, need for invasive ventilation, requirement of vasopressors, duration of vasopressors, and duration of ICU stay. The outcomes were then compared between the different sources of sepsis to determine which source of sepsis had the highest severity. Results In total, 176 patients were included in the study. Ninety-three patients were admitted with respiratory sepsis, 26 patients were admitted with gastrointestinal sepsis, 31 patients were admitted with urosepsis, and 26 patients were admitted with other miscellaneous causes of sepsis. The hospital mortality was highest in the respiratory sepsis group at 32%, with a trend towards statistical significance with a P value of 0.057. ICU stay duration was highest in patients with respiratory sepsis at six days, with a statistically significant P value of < 0.001. The need for invasive ventilation was highest in patients with respiratory sepsis at 64%, with a statistically significant P value of < 0.001. The requirement of vasopressor support was highest in patients with respiratory sepsis at 47% and the duration of vasopressors was highest in both respiratory and gastrointestinal sepsis at three days, however, there was no statistical significance. Conclusion Among the different origins of sepsis, the patients with respiratory sepsis had the most severe outcomes, with the highest need for invasive ventilation and the highest ICU stay duration.

An early warning model to predict acute kidney injury in sepsis patients with prior hypertension

Background

In the context of sepsis patients, hypertension has a significant impact on the likelihood of developing sepsis-associated acute kidney injury (S-AKI), leading to a considerable burden. Moreover, sepsis is responsible for over 50 % of cases of acute kidney injuries (AKI) and is linked to an increased likelihood of death during hospitalization. The objective of this research is to develop a dependable and strong nomogram framework, utilizing the variables accessible within the first 24 h of admission, for the anticipation of S-AKI in sepsis patients who have hypertension.

Methods

In this study that looked back, a total of 462 patients with sepsis and high blood pressure were identified from Nanfang Hospital. These patients were then split into a training set (consisting of 347 patients) and a validation set (consisting of 115 patients). A multivariate logistic regression analysis and a univariate logistic regression analysis were performed to identify the factors that independently predict S-AKI. Based on these independent predictors, the model was constructed. To evaluate the efficacy of the designed nomogram, several analyses were conducted, including calibration curves, receiver operating characteristics curves, and decision curve analysis.

Results

The findings of this research indicated that diabetes, prothrombin time activity (PTA), thrombin time (TT), cystatin C, creatinine (Cr), and procalcitonin (PCT) were autonomous prognosticators for S-AKI in sepsis individuals with hypertension. The nomogram model, built using these predictors, demonstrated satisfactory discrimination in both the training (AUC = 0.823) and validation (AUC = 0.929) groups. The S-AKI nomogram demonstrated superior predictive ability in assessing S-AKI within the hypertension grade I (AUC = 0.901) set, surpassing the hypertension grade II (AUC = 0.816) and III (AUC = 0.810) sets. The nomogram exhibited satisfactory calibration and clinical utility based on the calibration curve and decision curve analysis.

Conclusion

In patients with sepsis and high blood pressure, the nomogram that was created offers a dependable and strong evaluation for predicting S-AKI. This evaluation provides valuable insights to enhance individualized treatment, ultimately resulting in improved clinical outcomes.

Comprehensive analysis of immune cell landscapes revealed that immune cell ratio eosinophil/B.cell.memory is predictive of survival in sepsis

BACKGROUND

Immune dysregulation is a feature of sepsis. However, a comprehensive analysis of the immune landscapes in septic patients has not been conducted.

OBJECTIVES

This study aims to explore the abundance ratios of immune cells in sepsis and investigate their clinical value.

METHODS

Sepsis transcriptome data sets were downloaded from the NCBI GEO database. The immunedeconv R package was employed to analyze the abundance of immune cells in sepsis patients and calculate the ratios of different immune cell types. Differential analysis of immune cell ratios was performed using the t test. The Spearman rank correlation coefficient was utilized to find the relationships between immune cell abundance and pathways. The prognostic significance of immune cell ratios for patient survival probability was assessed using the log-rank test. In addition, differential gene expression was performed using the limma package, and gene co-expression analysis was executed using the WGCNA package.

RESULTS

We found significant changes in immune cell ratios between sepsis patients and healthy controls. Some of these ratios were associated with 28-day survival. Certain pathways showed significant correlations with immune cell ratios. Notably, six immune cell ratios demonstrated discriminative ability for patients with systemic inflammatory response syndrome (SIRS), bacterial sepsis, and viral sepsis, with an Area Under the Curve (AUC) larger than 0.84. Patients with a high eosinophil/B.cell.memory ratio exhibited poor survival outcomes. A total of 774 differential genes were identified in sepsis patients with a high eosinophil/B.cell.memory ratio compared to those with a low ratio. These genes were organized into seven co-expression modules associated with relevant pathways, including interferon signaling, T-cell receptor signaling, and specific granule pathways.

CONCLUSIONS

Immune cell ratios eosinophil/B.cell.memory and NK.cell.activated/NK.cell.resting in sepsis patients can be utilized for disease subtyping, prognosis, and diagnosis. The proposed cell ratios may have higher prognostic values than the neutrophil-to-lymphocyte ratio (NLR).

Trends in mortality after a sepsis hospitalization: a nationwide prospective registry study from 2008 to 2021

BACKGROUND

Few studies have reported on mortality beyond one year after sepsis. We aim to describe trends in short- and long-term mortality among patients admitted with sepsis, and to describe the association between clinical characteristics and mortality for improved monitoring, treatment and prognosis.

METHODS

Patients ≥ 18 years admitted to all Norwegian hospitals (2008-2021) with a first sepsis episode were identified using Norwegian Patient Registry and International Classification of Diseases 10th Revision codes. Sepsis was classified as implicit (known infection site plus organ dysfunction), explicit (unknown infection site), or COVID-19-related sepsis. The outcome was all-cause mortality. We describe age-standardized 30-day, 90-day, 1-, 5- and 10-year mortality for each admission year and estimated the annual percentage change with 95% confidence interval (CI). The association between clinical characteristics and all-cause mortality is reported as hazard ratios (HRs) adjusted for age, sex and calendar year in Cox regression.

RESULTS

The study included 222,832 patients, of whom 127,059 (57.1%) had implicit, 92,928 (41.7%) had explicit, and 2,845 (1.3%) had COVID-19-related sepsis (data from 2020 and 2021). Trends in overall age-standardized 30-day, 90-day, 1- and 5-year mortality decreased by 0.29 (95% CI - 0.39 to - 0.19), 0.43 (95% CI - 0.56 to - 0.29), 0.61 (95% CI - 0.73 to - 0.49) and 0.66 (95% CI - 0.84 to - 0.48) percent per year, respectively. The decrease was observed for all infections sites but was largest among patients with respiratory tract infections. Implicit, explicit and COVID-19-related sepsis had largely similar overall mortality, with explicit sepsis having an adjusted HR of 0.980 (95% CI 0.969 to 0.991) and COVID-19-related sepsis an adjusted HR of 0.916 (95% CI 0.836 to 1.003) compared to implicit sepsis. Patients with respiratory tract infections have somewhat higher mortality than those with other infection sites. Number of comorbidities was positively associated with mortality, but mortality varied considerably between different comorbidities. Similarly, number of acute organ dysfunctions was strongly associated with mortality, whereas the risk varied for each type of organ dysfunction.

CONCLUSION

Overall mortality has declined over the past 14 years among patients with a first sepsis admission. Comorbidity, site of infection, and acute organ dysfunction are patient characteristics that are associated with mortality. This could inform health care workers and raise the awareness toward subgroups of patients that needs particular attention to improve long-term mortality.

Patterns of Circulating Cytokines and Vascular Markers' Response in the Presence of COVID-19 in Kidney Transplant Recipients Compared with Non-Transplanted Patients

COVID-19's severity has been associated with a possible imbalance in the cross-regulation of cytokines and vascular mediators. Since the beginning of the pandemic, kidney transplant recipients (KTRs) have been identified as patients of high vulnerability to more severe diseases. Thus, aiming to describe the patterns of cytokines and vascular mediators and to trace patients' differences according to their KTR status, this prospective study enrolled 67 COVID-19 patients (20 KTRs) and 29 non-COVID-19 controls before vaccination. A panel comprising 17 circulating cytokines and vascular mediators was run on samples collected at different time points. The cytokine and mediator patterns were investigated via principal component analysis (PCA) and correlation-based network (CBN). In both groups, compared to their respective controls, COVID-19 was associated with higher levels of cytokines and vascular mediators. Differentiating between the KTRs and non-KTRs, the number of correlations was much higher in the non-KTRs (44 vs. 14), and the node analysis showed the highest interactions of NGAL and sVCAM-1 in the non-KTRs and KTRs (9 vs. 4), respectively. In the PCA, while the non-KTRs with COVID-19 were differentiated from their controls in their IL-10, IFN-α, and TNF-α, this pattern was marked in the NGAL, sVCAM-1, and IL-8 of the KTRs.

Sepsis heterogeneity

BACKGROUND

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, with extremely high mortality. Notably, sepsis is a heterogeneous syndrome characterized by a vast, multidimensional array of clinical and biologic features, which has hindered advances in the therapeutic field beyond the current standards.

DATA SOURCES

We used PubMed to search the subject-related medical literature by searching for the following single and/or combination keywords: sepsis, heterogeneity, personalized treatment, host response, infection, epidemiology, mortality, incidence, age, children, sex, comorbidities, gene susceptibility, infection sites, bacteria, fungi, virus, host response, organ dysfunction and management.

RESULTS

We found that host factors (age, biological sex, comorbidities, and genetics), infection etiology, host response dysregulation and multiple organ dysfunctions can all result in different disease manifestations, progression, and response to treatment, which make it difficult to effectively treat and manage sepsis patients.

CONCLUSIONS

Herein, we have summarized contributing factors to sepsis heterogeneity, including host factors, infection etiology, host response dysregulation, and multiple organ dysfunctions, from the key elements of pathogenesis of sepsis. An in-depth understanding of the factors that contribute to the heterogeneity of sepsis will help clinicians understand the complexity of sepsis and enable researchers to conduct more personalized clinical studies for homogenous patients.

Changes of Serum Pyruvate Kinase M2 Level in Patients with Sepsis and Its Clinical Value

Purpose

The glucose metabolic reprogramming is an important pathological mechanism in sepsis, which involves a series of enzymes including Pyruvate kinase M2 (PKM2). The purpose of this study is to explore the diagnostic and prognostic value of serum PKM2 in sepsis patients.

Patients and Methods

This study recruited 143 sepsis patients, 91 non-sepsis patients, and 65 physical examiners, divided into sepsis group, non-sepsis group, and control group. Measure the serum PKM2 concentration of subjects, collect and analyze clinical and laboratory indicators of all subjects. Independent risk factors were selected by Logistic regression analysis. The area under curve (AUC) was calculated by plotting the receiver operating characteristic (ROC) curve to determine the diagnostic and prognostic value of biomarkers.

Results

Compared with non-sepsis and control groups, the serum PKM2 levels in the sepsis group were significantly increased (both P<0.001). PKM2 was an independent risk factor for sepsis and had the best diagnostic efficacy when combined with procalcitonin, with the AUC value of 0.9352. Patients with high levels of PKM2 were more likely to experience organ damage and had a higher incidence of septic shock. On the 1st and 3rd days of admission, the serum PKM2 levels in the septic shock group were higher than those in the sepsis group (both P<0.05), with AUC values of 0.7296 and 0.6247, respectively. On the 3rd and 7th days of admission, the serum PKM2 levels in the non-survival group were significantly higher than those in the survival group (both P<0.001), with AUC values of 0.7033 and 0.8732, respectively.

Conclusion

The serum PKM2 levels in sepsis patients are significantly increased and correlated with disease severity and clinical outcomes. PKM2 may be a new diagnostic and prognostic biomarker for sepsis.

An Individualized Nomogram for Predicting Mortality Risk of Septic Shock Patients During Hospitalization: A ten Years Retrospective Analysis

Purpose

We intend to develop a nomogram for predicting the mortality risk of hospitalized septic shock patients.

Patients and Methods

Data were collected from patients hospitalized with septic shock in Affiliated Dongyang Hospital of Wenzhou Medical University in China, over 10 years between January 2013 and January 2023. The eligible study participants were divided into modeling and validation groups. Factors independently related to the mortality in the modeling group were obtained by stepwise regression analysis. A logistic regression model and a nomogram were built. The model was evaluated based on the discrimination power (the area under the curve of the receiver operating characteristic, AUC), the calibration degree and decision curve analysis. In the validation group, the discrimination powers of the logistic regression model, the sequential organ failure assessment (SOFA) scoring model and machine learning model were compared.

Results

A total of 1253 patients, including 878 patients in the modeling group and 375 patients in the validation group, were included in this study. Age, respiratory failure, serum cholinesterase, lactic acid, blood phosphorus, blood magnesium, total bilirubin, and pH were independent risk factors related to the mortality risk of septic shock. The AUCs of the prediction model for the modeling and validation groups were 0.881 and 0.868, respectively. The models had a good calibration degree and clinical applicability. The AUC of the SOFA model for the validation population was 0.799, significantly lower than that of our model. The AUCs of the random forest and ensemble models were 0.865 and 0.863, respectively, comparable to that of our logistical prediction model.

Conclusion

The model established in this study can effectively predict the mortality risk in patients hospitalized with septic shock. Thus, the model could be used clinically to determine the best therapy or management for patients with septic shock.

PATHWAYS ASSOCIATED WITH POSITIVE SEPSIS SURVIVAL OUTCOMES IN AFRICAN AMERICAN/BLACK AND NON-HISPANIC WHITE PATIENTS WITH URINARY TRACT INFECTION

ABSTRACT

Urinary tract infections (UTIs) are a common cause of sepsis worldwide. Annually, more than 60,000 US deaths can be attributed to sepsis secondary to UTIs, and African American/Black adults have higher incidence and case-fatality rates than non-Hispanic White adults. Molecular-level factors that may help partially explain differences in sepsis survival outcomes between African American/Black and Non-Hispanic White adults are not clear. In this study, patient samples (N = 166) from the Protocolized Care for Early Septic Shock cohort were analyzed using discovery-based plasma proteomics. Patients had sepsis secondary to UTIs and were stratified according to self-identified racial background and sepsis survival outcomes. Proteomics results suggest patient heterogeneity across mechanisms driving survival from sepsis secondary to UTIs. Differentially expressed proteins (n = 122, false discovery rate-adjusted P < 0.05) in Non-Hispanic White sepsis survivors were primarily in immune system pathways, while differentially expressed proteins (n = 47, false discovery rate-adjusted P < 0.05) in African American/Black patients were mostly in metabolic pathways. However, in all patients, regardless of racial background, there were 16 differentially expressed proteins in sepsis survivors involved in translation initiation and shutdown pathways. These pathways are potential targets for prognostic intervention. Overall, this study provides information about molecular factors that may help explain disparities in sepsis survival outcomes among African American/Black and Non-Hispanic White patients with primary UTIs.

Haemoadsorption Combined with Continuous Renal Replacement Therapy in Abdominal Sepsis: Case Report Series

In recent decades, multiple efforts have been made to identify targets and therapeutic measures in the host response to infection. Haemoadsorption, under the attractive theoretical premise of inflammatory response modulation through the adsorption of soluble inflammatory mediators, could have a place as an adjuvant therapy in septic patients. The development of new devices and the recent COVID-19 pandemic has renewed interest in this therapy. The aim of this report is to describe our experience in patients with abdominal sepsis for whom haemoadsorption with a neutral microporous resin column was added to conventional treatment and to describe its performance through patient cases in the absence of large randomised trials with this device. We present five patients with abdominal sepsis admitted to a Spanish intensive care unit in which haemoadsorption was used as adjuvant treatment. The key practical aspects of the treatment protocol have been used as a guide for conducting a multicentric study. Based on the experience gathered in these five cases, the potential benefit of haemoadsorption as adjuvant therapy in patients with abdominal sepsis with multiple organ failure after control of the source of infection and adequate treatment should be investigated. Likewise, it must be defined which patients can benefit from the therapy, the most appropriate biomarkers to guide the therapy, the ideal time of initiation and discontinuation, its potential side effects, and the interaction with other therapies, especially how such treatment affects the antibiotics levels.

CLINICAL CHARACTERISTICS AND PREDICTORS OF MORTALITY DIFFER BETWEEN PULMONARY AND ABDOMINAL SEPSIS

ABSTRACT

Background: Pulmonary sepsis and abdominal sepsis have pathophysiologically distinct phenotypes. This study aimed to compare their clinical characteristics and predictors of mortality. Methods: In this multicenter retrospective trial, 1,359 adult patients who fulfilled the Sepsis-3 criteria were enrolled and classified into the pulmonary sepsis or abdominal sepsis groups. Plasma presepsin was measured, and the scores of Acute Physiology and Chronic Health Evaluation (APACHE) II, Mortality in Emergency Department Sepsis (MEDS), and Simplified Acute Physiology Score (SAPS) II were calculated at enrollment. Data on 28-day mortality were collected for all patients. Results: Compared with patients with abdominal sepsis (n = 464), patients with pulmonary sepsis (n = 895) had higher 28-day mortality rate, illness severity scores, incidence of shock and acute kidney injury, and hospitalization costs. Lactate level and APACHE II and MEDS scores were independently associated with 28-day mortality in both sepsis types. Independent predictors of 28-day mortality included Pa o2 /F io2 ratio (hazard ratio [HR], 0.998; P < 0.001) and acute kidney injury (HR, 1.312; P = 0.039) in pulmonary sepsis, and SAPS II (HR, 1.037; P = 0.017) in abdominal sepsis. A model that combined APACHE II score, lactate, and MEDS score or SAPS II score had the best area under the receiver operating characteristic curve in predicting mortality in patients with pulmonary sepsis or abdominal sepsis, respectively. Interaction term analysis confirmed the association between 28-day mortality and lactate, APACHE II score, MEDS score, SAPS II score, and shock according to the sepsis subgroups. The mortality of patients with pulmonary sepsis was higher than that of patients with abdominal sepsis among patients without shock (32.9% vs. 8.8%; P < 0.001) but not among patients with shock (63.7 vs. 48.4%; P = 0.118). Conclusions: Patients with pulmonary sepsis had higher 28-day mortality than patients with abdominal sepsis. The study identified sepsis subgroup-specific mortality predictors. Shock had a larger effect on mortality in patients with abdominal sepsis than in those with pulmonary sepsis.

Time to treatment and mortality for clinical sepsis subtypes

BACKGROUND

Sepsis is common, deadly, and heterogenous. Prior analyses of patients with sepsis and septic shock in New York State showed a risk-adjusted association between more rapid antibiotic administration and bundled care completion, but not an intravenous fluid bolus, with reduced in-hospital mortality. However, it is unknown if clinically identifiable sepsis subtypes modify these associations.

METHODS

Secondary analysis of patients with sepsis and septic shock enrolled in the New York State Department of Health cohort from January 1, 2015 to December 31, 2016. Patients were classified as clinical sepsis subtypes (α, β, γ, δ-types) using the Sepsis ENdotyping in Emergency CAre (SENECA) approach. Exposure variables included time to 3-h sepsis bundle completion, antibiotic administration, and intravenous fluid bolus completion. Then logistic regression models evaluated the interaction between exposures, clinical sepsis subtypes, and in-hospital mortality.

RESULTS

55,169 hospitalizations from 155 hospitals were included (34% α, 30% β, 19% γ, 17% δ). The α-subtype had the lowest (N = 1,905, 10%) and δ-subtype had the highest (N = 3,776, 41%) in-hospital mortality. Each hour to completion of the 3-h bundle (aOR, 1.04 [95%CI, 1.02-1.05]) and antibiotic initiation (aOR, 1.03 [95%CI, 1.02-1.04]) was associated with increased risk-adjusted in-hospital mortality. The association differed across subtypes (p-interactions < 0.05). For example, the outcome association for the time to completion of the 3-h bundle was greater in the δ-subtype (aOR, 1.07 [95%CI, 1.05-1.10]) compared to α-subtype (aOR, 1.02 [95%CI, 0.99-1.04]). Time to intravenous fluid bolus completion was not associated with risk-adjusted in-hospital mortality (aOR, 0.99 [95%CI, 0.97-1.01]) and did not differ among subtypes (p-interaction = 0.41).

CONCLUSION

Timely completion of a 3-h sepsis bundle and antibiotic initiation was associated with reduced risk-adjusted in-hospital mortality, an association modified by clinically identifiable sepsis subtype.

Safety of megadose meropenem in the empirical treatment of nosocomial sepsis: a pilot randomized clinical trial

Objective: To evaluate the safety of megadose meropenem as empirical treatment of nosocomial sepsis. Materials & methods: Critically ill patients diagnosed with sepsis received either high-dose (2 g every 8 h) or megadose (4 g every 8 h) meropenem as an intravenous infusion over 3 h. Results: A total of 23 patients with nosocomial sepsis were eligible and included in the megadose (n = 11) or high-dose (n = 12) group. No treatment-related adverse events were observed during a 14-day follow-up. Clinical response was also comparable between the groups. Conclusion: Megadose meropenem may be considered for empirical treatment of nosocomial sepsis without serious concern regarding its safety.

Integrated analysis of multi-omics data reveals T cell exhaustion in sepsis

Background

Sepsis is a heterogeneous disease, therefore the single-gene-based biomarker is not sufficient to fully understand the disease. Higher-level biomarkers need to be explored to identify important pathways related to sepsis and evaluate their clinical significance.

Methods

Gene Set Enrichment Analysis (GSEA) was used to analyze the sepsis transcriptome to obtain the pathway-level expression. Limma was used to identify differentially expressed pathways. Tumor IMmune Estimation Resource (TIMER) was applied to estimate immune cell abundance. The Spearman correlation coefficient was used to find the relationships between pathways and immune cell abundance. Methylation and single-cell transcriptome data were also employed to identify important pathway genes. Log-rank test was performed to test the prognostic significance of pathways for patient survival probability. DSigDB was used to mine candidate drugs based on pathways. PyMol was used for 3-D structure visualization. LigPlot was used to plot the 2-D pose view for receptor-ligand interaction.

Results

Eighty-four KEGG pathways were differentially expressed in sepsis patients compared to healthy controls. Of those, 10 pathways were associated with 28-day survival. Some pathways were significantly correlated with immune cell abundance and five pathways could be used to distinguish between systemic inflammatory response syndrome (SIRS), bacterial sepsis, and viral sepsis with Area Under the Curve (AUC) above 0.80. Seven related drugs were screened using survival-related pathways.

Conclusion

Sepsis-related pathways can be utilized for disease subtyping, diagnosis, prognosis, and drug screening.

CLINICAL PHENOTYPES OF SEPSIS-ASSOCIATED ENCEPHALOPATHY: A RETROSPECTIVE COHORT STUDY

ABSTRACT

Background: Sepsis-associated encephalopathy (SAE) is a dysfunction of the central nervous system experienced during sepsis with variable clinical and pathophysiologic features. We sought to identify distinct SAE phenotypes in relation to clinical outcomes. Methods: The Medical Information Mart for Intensive Care IV (MIMIC-IV) database and the eICU database were used to conduct a retrospective cohort study. Adult sepsis patients were included and SAE was defined as having a Glasgow Coma Scale (GCS) score ˂15 or delirium. The following our clinical phenotypes were defined as: ischemic-hypoxic, metabolic, mixed (ischemic-hypoxic and metabolic), and unclassified. The primary outcome was in-hospital mortality. Results: The study enrolled 4,120 sepsis patients, 2,239 from MIMIC-IV (including 1,489 patients with SAE, 67%), and 1,881 from eICU (1,291, 69%). For the SAE cohort, 2,780 patients in total were enrolled (median age, 67 years; interquartile range, 56-76.8; 1,589 (57%) were male; median GCS score was 12 [8-14]; median Sequential Organ Failure Assessment score was 6 [4-9]). The SAE phenotype distributions between the MIMIC-IV and eICU cohorts were as follows (39% vs. 35% ischemic-hypoxic, P = 0.043; 38% vs. 40% metabolic, P = 0.239; 15% vs. 15% mixed, P = 0.972; 38% vs. 40% unclassified, P = 0.471). For the overall cohort, the in-hospital mortality for patients with ischemic-hypoxic, metabolic, mixed, or unclassified phenotypes was 33.9% (95% confidence interval, 0.3-0.37), 28.4% (0.26-0.31), 41.5% (0.37-0.46), and 14.2% (0.12-0.16), respectively. In the multivariable logistic analysis, the mixed phenotype was associated with the highest risk of in-hospital mortality after adjusting for age, sex, GCS, and modified Sequential Organ Failure Assessment score (adjusted odds ratio, 2.11; 95% confidence interval, 1.67-2.67; P < 0.001). Conclusions: Four SAE phenotypes had different clinical outcomes. The mixed phenotype had the worst outcomes. Further understanding of these phenotypes in sepsis may improve trial design and targeted SAE management.

Leveraging transcriptomics for precision diagnosis: Lessons learned from cancer and sepsis

Diagnostics require precision and predictive ability to be clinically useful. Integration of multi-omic with clinical data is crucial to our understanding of disease pathogenesis and diagnosis. However, interpretation of overwhelming amounts of information at the individual level requires sophisticated computational tools for extraction of clinically meaningful outputs. Moreover, evolution of technical and analytical methods often outpaces standardisation strategies. RNA is the most dynamic component of all -omics technologies carrying an abundance of regulatory information that is least harnessed for use in clinical diagnostics. Gene expression-based tests capture genetic and non-genetic heterogeneity and have been implemented in certain diseases. For example patients with early breast cancer are spared toxic unnecessary treatments with scores based on the expression of a set of genes (e.g., Oncotype DX). The ability of transcriptomics to portray the transcriptional status at a moment in time has also been used in diagnosis of dynamic diseases such as sepsis. Gene expression profiles identify endotypes in sepsis patients with prognostic value and a potential to discriminate between viral and bacterial infection. The application of transcriptomics for patient stratification in clinical environments and clinical trials thus holds promise. In this review, we discuss the current clinical application in the fields of cancer and infection. We use these paradigms to highlight the impediments in identifying useful diagnostic and prognostic biomarkers and propose approaches to overcome them and aid efforts towards clinical implementation.

Identification of potential diagnostic and prognostic biomarkers for sepsis based on machine learning

Background

To identify potential diagnostic and prognostic biomarkers of the early stage of sepsis.

Methods

The differentially expressed genes (DEGs) between sepsis and control transcriptomes were screened from GSE65682 and GSE134347 datasets. The candidate biomarkers were identified by the least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE) analyses. The diagnostic and prognostic abilities of the markers were evaluated by plotting receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were performed to further elucidate the molecular mechanisms and immune-related processes. Finally, the potential biomarkers were validated in a septic mouse model by qRT-PCR and western blotting.

Results

Eleven DEGs were identified between the sepsis and control samples, including YOD1, GADD45A, BCL11B, IL1R2, UGCG, TLR5, S100A12, ITK, HP, CCR7 and C19orf59 (all AUC>0.9). Furthermore, the survival analysis identified YOD1, GADD45A, BCL11B and IL1R2 as the prognostic biomarkers of sepsis. According to GSEA, four DEGs were significantly associated with immune-related processes. In addition, ssGSEA demonstrated a significant difference in the enriched immune cell populations between the sepsis and control groups (all P < 0.05). Moreover, YOD1, GADD45A and IL1R2 were upregulated, and BCL11B was downregulated in the heart, liver, lungs, and kidneys of the septic mice model.

Conclusions

We identified four potential immune-releated diagnostic and prognostic gene markers for sepsis that offer new insights into its underlying mechanisms.

Characterization of Mortality by Sepsis Source in Patients Admitted to the Surgical Intensive Care Unit

INTRODUCTION

The impact of infectious source on sepsis outcomes for surgical patients is unclear. The objective of this study was to evaluate the association between sepsis sources and cumulative 90-d mortality in patients admitted to the surgical intensive care unit (SICU) with sepsis.

METHODS

All patients admitted to the SICU at an academic institution who met sepsis criteria (2014-2019, n = 1296) were retrospectively reviewed. Classification of source was accomplished through a chart review and included respiratory (RT, n = 144), intra-abdominal (IA, n = 859), skin and soft tissue (SST, n = 215), and urologic (UR, n = 78). Demographics, comorbidities, and clinical presentation were compared. Outcomes included 90-d mortality, respiratory and renal failure, length of stay, and discharge disposition. Cox-proportional regression was used to model predictors of mortality; P < 0.05 was significant.

RESULTS

Patients with SST were younger, more likely to be diabetic and obese, but had the lowest total comorbidities. Median admission sequential organ failure assessment scores were highest for IA and STT and lowest in urologic infections. Cumulative 90-d mortality was highest for IA and RT (35% and 33%, respectively) and lowest for SST (20%) and UR (8%) (P < 0.005). Compared to the other categories, UR infections had the lowest SICU length of stay and the highest discharge-to-home (57%, P < 0.0005). Urologic infections remained an independent negative predictor of 90-d mortality (odds ratio 0.14, 95% confidence interval: 0.1-0.4), after controlling for sequential organ failure assessment.

CONCLUSIONS

Urologic infections remained an independent negative predictor of 90-d mortality when compared to other sources of sepsis. Characterization of sepsis source revealed distinct populations and clinical courses, highlighting the importance of understanding different sepsis phenotypes.

T cell activation profiles can distinguish gram negative/positive bacterial sepsis and are associated with ICU discharge

Introduction

Sepsis is a life-threatening complication resulting from a dysregulated host response to a serious infection, of which bacteria are the most common cause. A rapid differentiation of the gram negative (G^-)/gram positive (G⁺) pathogens facilitates antibiotic treatment, which in turn improves patients' survival.

Methods

We performed a prospective, observational study of adult patients in intensive care unit (ICU) unit and underwent the analysis of peripheral blood lymphocyte subsets, cytokines and other clinical indexes. The enrolled 94 patients were divided into no infection group (n=28) and bacterial sepsis group (n=66), and the latter group was subdivided into G^- (n=46) and G⁺ (n=20) sepsis subgroups.

Results

The best immune biomarker which differentiated the diagnosis of G^- sepsis from G⁺ sepsis, included activation markers of CD69, human leukocyte antigen DR (HLA-DR) on CD3⁺CD8⁺T subset. The ratio of CD3⁺CD4⁺CD69⁺T/CD3⁺CD8⁺CD69⁺T (odds ratio (OR): 0.078(0.012,0.506), P = 0.008), PCT>0.53 ng/ml (OR: 9.31(1.36,63.58), P = 0.023), and CO₂CP<26.5 mmol/l (OR: 10.99(1.29, 93.36), P = 0.028) were predictive of G^- sepsis (versus G⁺ sepsis), and the area under the curve (AUC) was 0.947. Additionally, the ratio of CD3⁺CD4⁺CD69⁺T/CD3⁺CD8⁺CD69⁺T ≤ 0.2697 was an independent risk factor for poor ICU discharge in G^- sepsis patients (HR: 0.34 (0.13, 0.88), P=0.026).

Conclusion

We conclude that enhanced activation of T cells may regulate the excessive inflammatory response of G^- bacterial sepsis, and that T cell activation profiles can rapidly distinguish G^- sepsis from G⁺ sepsis and are associated with ICU discharge.

Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis

Background

Sepsis is a heterogeneous syndrome with high morbidity and mortality. Optimal and effective classifications are in urgent need and to be developed.

Methods and results

A total of 1,936 patients (sepsis samples, n=1,692; normal samples, n=244) in 7 discovery datasets were included to conduct weighted gene co-expression network analysis (WGCNA) to filter out candidate genes related to sepsis. Then, two subtypes of sepsis were classified in the training sepsis set (n=1,692), the Adaptive and Inflammatory, using K-means clustering analysis on 90 sepsis-related features. We validated these subtypes using 617 samples in 5 independent datasets and the merged 5 sets. Cibersort method revealed the Adaptive subtype was related to high infiltration levels of T cells and natural killer (NK) cells and a better clinical outcome. Immune features were validated by single-cell RNA sequencing (scRNA-seq) analysis. The Inflammatory subtype was associated with high infiltration of macrophages and a disadvantageous prognosis. Based on functional analysis, upregulation of the Toll-like receptor signaling pathway was obtained in Inflammatory subtype and NK cell-mediated cytotoxicity and T cell receptor signaling pathway were upregulated in Adaptive group. To quantify the cluster findings, a scoring system, called, risk score, was established using four datasets (n=980) in the discovery cohorts based on least absolute shrinkage and selection operator (LASSO) and logistic regression and validated in external sets (n=760). Multivariate logistic regression analysis revealed the risk score was an independent predictor of outcomes of sepsis patients (OR [odds ratio], 2.752, 95% confidence interval [CI], 2.234-3.389, P<0.001), when adjusted by age and gender. In addition, the validation sets confirmed the performance (OR, 1.638, 95% CI, 1.309-2.048, P<0.001). Finally, nomograms demonstrated great discriminatory potential than that of risk score, age and gender (training set: AUC=0.682, 95% CI, 0.643-0.719; validation set: AUC=0.624, 95% CI, 0.576-0.664). Decision curve analysis (DCA) demonstrated that the nomograms were clinically useful and had better discriminative performance to recognize patients at high risk than the age, gender and risk score, respectively.

Conclusions

In-depth analysis of a comprehensive landscape of the transcriptome characteristics of sepsis might contribute to personalized treatments and prediction of clinical outcomes.

Immune Modulation in Sepsis, ARDS, and Covid-19 - The Road Traveled and the Road Ahead

Immune Modulation in Sepsis, ARDS, and Covid-19Leligdowicz et al. consider the history and future of immunomodulating therapies in sepsis and ARDS, including ARDS due to Covid-19, and remark on the larger challenge of clinical research on therapies for syndromes with profound clinical and biologic heterogeneity.

Host response dysregulations amongst adults hospitalized by influenza A H1N1 virus pneumonia: A prospective multicenter cohort study

BACKGROUND

Limited knowledge exists on how early host response impacts outcomes in influenza pneumonia.

METHODS

This study assessed what was the contribution of host immune response at the emergency department on hospital mortality amongst adults with influenza A H1N1pdm09 pneumonia and whether early stratification by immune host response anticipates the risk of death. This is a secondary analysis from a prospective, observational, multicenter cohort comparing 75 adults requiring intensive care with 38 hospitalized in medical wards. Different immune response biomarkers within 24 h of hospitalization and their association with hospital mortality were assessed.

RESULTS

Fifty-three were discharged alive. Non-survivors were associated (p&lt;0.05) with lower lymphocytes (751 vs. 387), monocytes (450 vs. 220) expression of HLA-DR (1,662 vs. 962) and higher IgM levels (178 vs. 152;p&lt;0.01). Lymphocyte subpopulations amongst non-survivors showed a significantly (p&lt;0.05) lower number of TCD3+ (247.2 vs. 520.8), TCD4+ (150.3 vs. 323.6), TCD8+ (95.3 vs. 151.4) and NKCD56+ (21.9 vs. 91.4). Number of lymphocytes, monocytes and NKCD56+ predicted hospital mortality (AUC 0.854). Hospital mortality was independently associated with low HLA-DR values, low number of NKCD56+ cells, and high IgM levels, in a Cox-proportional hazard analysis. A second model, documented that hospital mortality was independently associated with a phenotype combining immunoparalysis with hyperinflammation (HR 5.53; 95%CI 2.16-14.14), after adjusting by predicted mortality.

CONCLUSIONS

We conclude that amongst influenza pneumonia, presence of immunoparalysis was a major mortality driver. Influenza heterogeneity was partly explained by early specific host response dysregulations which should be considered to design personalized approaches of adjunctive therapy.

Immune checkpoint inhibitors for the treatment of sepsis:insights from preclinical and clinical development

INTRODUCTION

Sepsis represents one-fifth of all deaths worldwide and is associated with huge costs. Regarding disease progression, it is now well established that sepsis induces a state of acquired immunosuppression, with an increased risk of secondary infections that contributes to patients' worsening. Thus, tackling sepsis-induced immunosuppression represents a promising perspective.

AREAS COVERED

Of mechanisms responsible for sepsis-induced immunosuppression, the increased expression of co-inhibitory receptors (aka immune checkpoint) such as PD-1, CTLA4, TIM-3, LAG-3 or BTLA and their ligands recently received considerable interest since their inhibition, thanks to the so-called checkpoint inhibitors (CPI), provided astonishing results in cancer by rebooting immune functions. This review reports on the first landmarks of these molecules in sepsis. We introduce them in terms of basic immunology in line with sepsis pathophysiology both in experimental models and observational works and assess the first human clinical studies.

EXPERT OPINION

Preclinical results are positive and the first human clinical trials, although currently limited to the early phase, showed a beneficial effect on immunological functions and/or markers and suggested that tolerance of CPIs side effects, mainly auto-immune disorders, is acceptable in sepsis. Elsewhere, in some specific infections leading to ICU admission (or occurring during ICU stay), such as fungal infections, preliminary convincing case reports have been published. Overall, the first results regarding CPIs in sepsis appear encouraging. However, further efforts are warranted, especially in defining the right patients to be treated (i.e., in an individualized approach) and establishing the optimal time to start an immune restoration. Larger trials are now mandatory to confirm CPIs' potential in sepsis.

Clinical and biochemical endpoints and predictors of response to plasma exchange in septic shock: results from a randomized controlled trial

Background

Recently, a randomized controlled trial (RCT) demonstrated rapid but individually variable hemodynamic improvement with therapeutic plasma exchange (TPE) in patients with septic shock. Prediction of clinical efficacy in specific sepsis treatments is fundamental for individualized sepsis therapy.

Methods

In the original RCT, patients with septic shock of < 24 h duration and norepinephrine (NE) requirement ≥ 0.4 μg/kg/min received standard of care (SOC) or SOC + one single TPE. Here, we report all clinical and biological endpoints of this study. Multivariate mixed-effects modeling of NE reduction was performed to investigate characteristics that could be associated with clinical response to TPE.

Results

A continuous effect of TPE on the reduction in NE doses over the initial 24 h was observed (SOC group: estimated NE dose reduction of 0.005 µg/kg/min per hour; TPE group: 0.018 µg/kg/min per hour, p = 0.004). Similarly, under TPE, serum lactate levels, continuously decreased over the initial 24 h in the TPE group, whereas lactate levels increased under SOC (p = 0.001). A reduction in biomarkers and disease mediators (such as PCT (p = 0.037), vWF:Ag (p < 0.001), Angpt-2 (p = 0.009), sTie-2 (p = 0.005)) along with a repletion of exhausted protective factors (such as AT-III (p = 0.026), Protein C (p = 0.012), ADAMTS-13 (p = 0.008)) could be observed in the TPE but not in the SOC group. In a multivariate mixed effects model, increasing baseline lactate levels led to greater NE dose reduction effects with TPE as opposed to SOC (p = 0.004).

Conclusions

Adjunctive TPE is associated with the removal of injurious mediators and repletion of consumed protective factors altogether leading to preserved hemodynamic stabilization in refractory septic shock. We identified that baseline lactate concentration as a potential response predictor might guide future designing of large RCTs that will further evaluate TPE with regard to hard endpoints.

Trial registration Retrospectively registered 18th January 2020 at clinicaltrials.gov (Identifier: NCT04231994).

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-04003-2.

Coagulation factor protein abundance in the pre-septic state predicts coagulopathic activities that arise during late-stage murine sepsis

BACKGROUND

Although sepsis accounts for 1 in 5 deaths globally, few molecular therapies exist for this condition. The development of effective biomarkers and treatments for sepsis requires a more complete understanding of host responses and pathogenic mechanisms at early stages of disease to minimize host-driven pathology.

METHODS

An alternative to the current symptom-based approach used to diagnose sepsis is a precise assessment of blood proteomic changes during the onset and progression of Salmonella Typhimurium (ST) murine sepsis.

FINDINGS

A distinct pattern of coagulation factor protein abundance was identified in the pre-septic state- prior to overt disease symptoms or bacteremia- that was predictive of the dysregulation of fibrinolytic and anti-coagulant activities and resultant consumptive coagulopathy during ST murine sepsis. Moreover, the changes in protein abundance observed generally have the same directionality (increased or decreased abundance) reported for human sepsis. Significant overlap of ST coagulopathic activities was observed in Gram-negative Escherichia coli- but not in Gram-positive staphylococcal or pneumococcal murine sepsis models. Treatment with matrix metalloprotease inhibitors prevented aberrant inflammatory and coagulopathic activities post-ST infection and increased survival. Antibiotic treatment regimens initiated after specific changes arise in the plasma proteome post-ST infection were predictive of an increase in disease relapse and death after cessation of antibiotic treatment.

INTERPRETATION

Altered blood proteomics provides a platform to develop rapid and easy-to-perform tests to predict sepsis for early intervention via biomarker incorporation into existing blood tests prompted by patient presentation with general malaise, and to stratify Gram-negative and Gram-positive infections for appropriate treatment. Antibiotics are less effective in microbial clearance when initiated after the onset of altered blood proteomics as evidenced by increased disease relapse and death after termination of antibiotic therapy. Treatment failure is potentially due to altered bacterial / host-responses and associated increased host-driven pathology, providing insight into why delays in antibiotic administration in human sepsis are associated with increased risk for death. Delayed treatment may thus require prolonged therapy for microbial clearance despite the prevailing notion of antibiotic de-escalation and shortened courses of antibiotics to improve drug stewardship.

FUNDING

National Institutes of Health, U.S. Army.

Multidimensional analysis of the host response reveals prognostic and pathogen-driven immune subtypes among adults with sepsis in Uganda

Background

The global burden of sepsis is concentrated in sub-Saharan Africa, where severe infections disproportionately affect young, HIV-infected adults and high-burden pathogens are unique. In this context, poor understanding of sepsis immunopathology represents a crucial barrier to development of locally-effective treatment strategies. We sought to determine inter-individual immunologic heterogeneity among adults hospitalized with sepsis in a sub-Saharan African setting, and characterize associations between immune subtypes, infecting pathogens, and clinical outcomes.

Methods

Among a prospective observational cohort of 288 adults hospitalized with suspected sepsis in Uganda, we applied machine learning methods to 14 soluble host immune mediators, reflective of key domains of sepsis immunopathology (innate and adaptive immune activation, endothelial dysfunction, fibrinolysis), to identify immune subtypes in randomly-split discovery (N = 201) and internal validation (N = 87) sub-cohorts. In parallel, we applied similar methods to whole-blood RNA-sequencing data from a consecutive subset of patients (N = 128) to identify transcriptional subtypes, which we characterized using biological pathway and immune cell-type deconvolution analyses.

Results

Unsupervised clustering consistently identified two immune subtypes defined by differential activation of pro-inflammatory innate and adaptive immune pathways, with transcriptional evidence of concomitant CD56(-)/CD16( +) NK-cell expansion, T-cell exhaustion, and oxidative-stress and hypoxia-induced metabolic and cell-cycle reprogramming in the hyperinflammatory subtype. Immune subtypes defined by greater pro-inflammatory immune activation, T-cell exhaustion, and metabolic reprogramming were consistently associated with a high-prevalence of severe and often disseminated HIV-associated tuberculosis, as well as more extensive organ dysfunction, worse functional outcomes, and higher 30-day mortality.

Conclusions

Our results highlight unique host- and pathogen-driven features of sepsis immunopathology in sub-Saharan Africa, including the importance of severe HIV-associated tuberculosis, and reinforce the need to develop more biologically-informed treatment strategies in the region, particularly those incorporating immunomodulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13054-022-03907-3.