Biomarkers of sepsis: time for a reappraisal

Single-cell RNA sequencing and transcriptomic analysis reveal key genes and regulatory mechanisms in sepsis

The pathogenesis of sepsis, with a high mortality rate and often poor prognosis, has not been fully elucidated. Therefore, an in-depth study on the pathogenesis of sepsis at the molecular level is essential to identify key sepsis-related genes. The aim of this study was to explore the key genes and potential molecular mechanisms of sepsis using a bioinformatics approach. In addition, key genes with miRNA network correlation analysis and immune infiltration correlation analysis were investigated. The scRNA dataset (GSE167363) and RNA-seq dataset (GSE65682, GSE134347) from GEO database were used for screening out differentially expressed genes using single-cell sequencing and transcriptome sequencing. The analysis of immune infiltration was evaluated by the CIBERSORT method. Key genes and possible mechanisms were identified by WGCNA analysis, GSVA analysis, GSEA enrichment analysis and regulatory network analysis, and miRNA networks associated with key genes were constructed. Nine key genes associated with the development of sepsis, namely IL7R, CD3D, IL32, GPR183, HLA-DPB1, CD81, PEBP1, NCL, and ETS1 were screened, and the specific signaling mechanisms associated with the key genes causing sepsis were predicted. Immune profiling showed immune heterogeneity between control and sepsis samples. A regulatory network of 82 miRNAs, 266 pairs of mRNA-miRNA relationship pairs was also constructed. These nine key genes have the potential to become biomarkers for the diagnosis of sepsis and provide new targets and research directions for the treatment of sepsis.

Mortality prediction model from combined serial lactate, procalcitonin and calprotectin levels in critically ill patients with sepsis: A retrospective study according to Sepsis-3 definition

OBJECTIVE

1) To evaluate the ability of baseline and on 24 h serum calprotectin, in comparison to canonical biomarkers (lactate and procalcitonin), for prognosis of 28-day mortality in critically ill septic patients; and 2) To develop a predictive model combining the three biomarkers.

DESIGN

A single-center, retrospective study.

SETTING

Intensive Care Unit of a university hospital.

PATIENTS OR PARTICIPANTS

One hundred and seventy three septic pacientes were included.

INTERVENTIONS

Measurement of baseline lactate, procalcitonin and calprotectin level and procalcitonin and calprotectin levels on 24 h.

MAIN VARIABLES OF INTEREST

Demographics and comorbidities, SOFA score on ICU admission, baseline lactate, procalcitonin and calprotectin on admission and on 24 h and 28-day mortality.

RESULTS

1) On ICU admission, lactate was the only biomarker achieving a significant accuracy (AUC: 0.698); 2) On 24 h, no differences were found on procalcitonin and calprotectin levels. Procalcitonin and calprotectin clearances were significantly lower in non-survivors and both achieved a moderate performance (AUCs: 0.668 and 0.664, respectively); 3) A biomarker based-model achieved a significant accuracy (AUC: 0.766), trending to increase (AUC: 0.829) to SOFA score alone; y 4) Baseline lactate levels and procalcitonin and calprotectin clearance were independent predictors for the outcome.

CONCLUSIONS

1) Baseline and on 24 h calprotectina and procalcitonin levels lacked ability in predicting 28-day mortality; 2) Accuracy of clearance of both biomarkers was moderate; and 3) Combination of SOFA score and the predictive biomarker based-model showed a high prognostic accuracy.

Early detection of neonatal sepsis and reduction of overall antibiotic exposure: Towards precision medicine

Infections claim the lives of over half a million newborns annually and expose survivors to the risk of lifelong disability. The challenge to clinicians is to identify newborns with invasive infections rapidly, promptly initiate antimicrobial treatment, and take measures to prevent and treat organ dysfunction. Moreover, excessive antibiotic use is a global public health problem. Despite considerable research on clinical and laboratory markers of neonatal sepsis, the effective translation into clinical practice remains limited. There is no single clinical or laboratory marker, nor any combination of markers that definitively confirms or rules out neonatal sepsis. The interpretation of these markers should take into account their diagnostic value for a given patient, along with their added value to the clinical decision-making process. The digitalization of health care systems, combined with increased computational power and advances in machine learning, offers the possibility of developing accurate predictive algorithms for early detection of neonatal sepsis.

Identification of TRIM52 as a potential biomarker in mortality risk assessment in patients with sepsis

INTRODUCTION

Sepsis is one of the most common causes of death among hospitalized patients in the intensive care unit (ICU). It is particularly difficult to diagnose in this setting because of the multiple comorbidities and underlying diseases that these patients present. In the clinical diagnosis, the current recommendation for identifying both sepsis and septic shock is the use of the SOFA score (sequential organ failure assessment score). SOFA is a system, which uses accessible parameters in daily clinical practice to identify dysfunction or failure of the key organs as a result of sepsis. This tools cannot be used alone, more abundant clinical assessment data should be complemented. The aim of this study was to analyze the clinical value of tripartite motif protein 52 (TRIM52) as a potential biomarker for predicting the risk of death in septic patients.

MATERIALS AND METHODS

A case-control study was conducted on sepsis patients and healthy volunteers admitted to the First affiliated hospital of Chongqing Medical University. Sepsis patients that met the Sepsis-3 diagnostic criteria were included in the septic patient group. The levels of TRIM52 in the samples were detected by enzyme-linked immunosorbent assay. The area under the receiver operating characteristic (ROC) curve of TRIM52, SOFA score, APACHEII score, PCT, CRP, WBC and Creatinine for 28-day survival was used to evaluate the ability of TRIM52 in predicting the mortality of sepsis.

RESULTS

The level of TRIM52 in patients with sepsis was significantly higher than that in healthy group (p < 0.05). Meanwhile, TRIM52 levels in non-surviving septic patients was higher than that in survivors (p < 0.05). The ROC curve analysis indicated that TRIM52 showed a better prediction of 28-day mortality risk in ICU sepsis patients compared to other indicators such as SOFA score, APACHEII score, PCT, CRP, and WBC, with AUC values, respectively (p < 0.05).

CONCLUSIONS

TRIM52 level in septic patients has an important value in predicting the 28-day mortality risk of septic patients, and may be a novel potential early clinical detecting indicator.

Rapid and Robust Identification of Sepsis Using SeptiCyte RAPID in a Heterogeneous Patient Population

Background/Objective: SeptiCyte RAPID is a transcriptional host response assay that discriminates between sepsis and non-infectious systemic inflammation (SIRS) with a one-hour turnaround time. The overall performance of this test in a cohort of 419 patients has recently been described [Balk et al., J Clin Med 2024, 13, 1194]. In this study, we present the results from a detailed stratification analysis in which SeptiCyte RAPID performance was evaluated in the same cohort across patient groups and subgroups encompassing different demographics, comorbidities and disease, sources and types of pathogens, interventional treatments, and clinically defined phenotypes. The aims were to identify variables that might affect the ability of SeptiCyte RAPID to discriminate between sepsis and SIRS and to determine if any patient subgroups appeared to present a diagnostic challenge for the test. Methods: (1) Subgroup analysis, with subgroups defined by individual demographic or clinical variables, using conventional statistical comparison tests. (2) Principal component analysis and k-means clustering analysis to investigate phenotypic subgroups defined by unique combinations of demographic and clinical variables. Results: No significant differences in SeptiCyte RAPID performance were observed between most groups and subgroups. One notable exception involved an enhanced SeptiCyte RAPID performance for a phenotypic subgroup defined by a combination of clinical variables suggesting a septic shock response. Conclusions: We conclude that for this patient cohort, SeptiCyte RAPID performance was largely unaffected by key variables associated with heterogeneity in patients suspected of sepsis.

EFFICACY OF A SEPSIS CLINICAL DECISION SUPPORT SYSTEM IN IDENTIFYING PATIENTS WITH SEPSIS IN THE EMERGENCY DEPARTMENT

ABSTRACT

Background: Early prediction of sepsis onset is crucial for reducing mortality and the overall cost burden of sepsis treatment. Currently, few effective and accurate prediction tools are available for sepsis. Hence, in this study, we developed an effective sepsis clinical decision support system (S-CDSS) to assist emergency physicians to predict sepsis. Methods: This study included patients who had visited the emergency department (ED) of Taipei Tzu Chi Hospital, Taiwan, between January 1, 2020, and June 31, 2022. The patients were divided into a derivation cohort (n = 70,758) and a validation cohort (n = 27,545). The derivation cohort was subjected to 6-fold stratified cross-validation, reserving 20% of the data (n = 11,793) for model testing. The primary study outcome was a sepsis prediction ( International Classification of Diseases , Tenth Revision , Clinical Modification ) before discharge from the ED. The S-CDSS incorporated the LightGBM algorithm to ensure timely and accurate prediction of sepsis. The validation cohort was subjected to multivariate logistic regression to identify the associations of S-CDSS-based high- and medium-risk alerts with clinical outcomes in the overall patient cohort. For each clinical outcome in high- and medium-risk patients, we calculated the sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and accuracy of S-CDSS-based predictions. Results: The S-CDSS was integrated into our hospital information system. The system featured three risk warning labels (red, yellow, and white, indicating high, medium, and low risks, respectively) to alert emergency physicians. The sensitivity and specificity of the S-CDSS in the derivation cohort were 86.9% and 92.5%, respectively. In the validation cohort, high- and medium-risk alerts were significantly associated with all clinical outcomes, exhibiting high prediction specificity for intubation, general ward admission, intensive care unit admission, ED mortality, and in-hospital mortality (93.29%, 97.32%, 94.03%, 93.04%, and 93.97%, respectively). Conclusion: Our findings suggest that the S-CDSS can effectively identify patients with suspected sepsis in the ED. Furthermore, S-CDSS-based predictions appear to be strongly associated with clinical outcomes in patients with sepsis.

Measurement of Pancreatic Stone Protein Compared with C-Reactive Protein and Procalcitonin in the Diagnosis of Sepsis in an Intensive Care Unit: A Systematic Review

Sepsis remains a significant challenge in the intensive care unit (ICU), with prompt diagnosis and management being critical to improving patient outcomes. Biomarkers have emerged as valuable tools for identifying and predicting sepsis outcomes, with pancreatic stone protein (PSP), procalcitonin (PCT) and C-reactive protein (CRP) as three promising candidates. This systematic review aimed to analyse and compare the diagnostic accuracy of PSP, PCT and CRP regarding sepsis in the ICU. A review of the literature on the diagnostic performance of the three biomarkers was performed using PubMed Central, PubMed, ScienceDirect, Oxford Academic, SpringerLink and Cochrane Library. Data regarding the diagnostic accuracy of the three biomarkers were extracted, compared, and represented as the area under the curve (AUC) receiver operating characteristics (ROC). Three studies examining PSP, PCT and CRP biomarkers in 858 adult patients admitted to the ICU were included in this review. Compared with PCT and CRP, the PSP biomarker, with its unique applications and properties that may potentially benefit patients, doctors and hospitals, performed well and proved reliable in diagnosing sepsis in adult patients. PSP demonstrated reliability in sepsis diagnosis. Further analysis should be conducted to establish a formal, appropriate indication, as well as to determine a suspected sepsis patient's condition when testing each biomarker.

Novel biomarkers to identify complicated course of febrile neutropenia in hematological patients receiving intensive chemotherapy

Febrile neutropenia (FN) is a common consequence of intensive chemotherapy in hematological patients. More than 90% of the patients with acute myeloid leukemia (AML) develop FN, and 5%-10% of them die from subsequent sepsis. FN is very common also in autologous stem cell transplant recipients, but the risk of death is lower than in AML patients. In this review, we discuss biomarkers that have been evaluated for diagnostic and prognostic purposes in hematological patients with FN. In general, novel biomarkers have provided little benefit over traditional inflammatory biomarkers, such as C-reactive protein and procalcitonin. The utility of most biomarkers in hematological patients with FN has been evaluated in only a few small studies. Although some of them appear promising, much more data is needed before they can be implemented in the clinical evaluation of FN patients. Currently, close patient follow-up is key to detect complicated course of FN and the need for further interventions such as intensive care unit admission. Scoring systems such as q-SOFA (Quick Sequential Organ Failure Assessment) or NEWS (National Early Warning Sign) combined with traditional and/or novel biomarkers may provide added value in the clinical evaluation of FN patients.

Elevations in presepsin, PCT, hs-CRP, and IL-6 levels predict mortality among septic patients in the ICU

This study aimed to investigate whether changes in presepsin, procalcitonin, high-sensitivity C-reactive protein, and interleukin 6 levels predict mortality in septic patients in the intensive care unit. This study enrolled septic patients between November 2020 and December 2021. Levels of presepsin, procalcitonin, high-sensitivity C-reactive protein, and interleukin 6 were measured on the first (PSEP_0, PCT_0, hsCRP_0, IL-6_0) and third days (PSEP_3, PCT_3, hsCRP_3, IL-6_3). Follow-up was performed on days 3, 7, 14, 21, and 28 after enrollment. The outcome was all-cause death. The study included 119 participants, and the mortality was 18.5%. In univariable Cox proportional hazards regression analysis, ΔPSEP (= PSEP_3 - PSEP_0) > 211.49 pg/mL (hazard ratio, 2.70; 95% confidence interval, 1.17-6.22), ΔPCT (= PCT_3 - PCT_0) > -0.13 ng/mL (hazard ratio, 7.31; 95% confidence interval, 2.68-19.80), ΔhsCRP (= hsCRP_3 - hsCRP_0) > -19.29 mg/L (hazard ratio, 6.89; 95% confidence interval, 1.61-29.40), and ΔIL-6 (= IL-6_3 - IL-6_0) > 1.00 pg/mL (hazard ratio, 3.13; 95% confidence interval, 1.35-7.24) indicated an increased risk of mortality. The composite concordance index for alterations in all 4 distinct biomarkers was highest (concordance index, 0.83; 95% confidence interval, 0.76-0.91), suggesting the optimal performance of this panel in mortality prediction. In decision curve analysis, compared with the Acute Physiology and Chronic Health Evaluation II and Sequential (sepsis-related) Organ Failure Assessment scores, the combination of the 4 biomarkers had a larger net benefit. Interestingly, interleukin 6 was predominantly produced by monocytes upon lipopolysaccharide stimulation in peripheral blood mononuclear cells. ΔPSEP, ΔPCT, ΔhsCRP, and ΔIL-6 are reliable biomarkers for predicting mortality in septic patients in the intensive care unit, and their combination has the best performance.

ACE2 alleviates sepsis-induced cardiomyopathy through inhibiting M1 macrophage via NF-κB/STAT1 signals

Angiotensin-converting enzyme 2 (ACE2), a crucial element of the renin-angiotensin system (RAS), metabolizes angiotensin II into Ang (1-7), which then combines with the Mas receptor (MasR) to fulfill its protective role in various diseases. Nevertheless, the involvement of ACE2 in sepsis-induced cardiomyopathy (SIC) is still unexplored. In this study, our results revealed that CLP surgery dramatically impaired cardiac function accompanied with disruption of the balance between ACE2-Ang (1-7) and ACE-Ang II axis in septic heart tissues. Moreover, ACE2 knockin markedly alleviated sepsis induced RAS disorder, cardiac dysfunction and improved survival rate in mice, while ACE2 knockout significantly exacerbates these outcomes. Adoptive transfer of bone marrow cells and in vitro experiments showed the positive role of myeloid ACE2 by mitigating oxidative stress, inflammatory response, macrophage polarization and cardiomyocyte apoptosis by blocking NF-κB and STAT1 signals. However, the beneficial impacts were nullified by MasR antagonist A779. Collectively, these findings showed that ACE2 alleviated SIC by inhibiting M1 macrophage via activating the Ang (1-7)-MasR axis, highlight that ACE2 might be a promising target for the management of sepsis and SIC patients.

Screening and identification of the hub genes in severe acute pancreatitis and sepsis

Background

Severe acute pancreatitis (SAP) is accompanied with acute onset, rapid progression, and complicated condition. Sepsis is a common complication of SAP with a high mortality rate. This research aimed to identify the shared hub genes and key pathways of SAP and sepsis, and to explore their functions, molecular mechanism, and clinical value.

Methods

We obtained SAP and sepsis datasets from the Gene Expression Omnibus (GEO) database and employed differential expression analysis and weighted gene co-expression network analysis (WGCNA) to identify the shared differentially expressed genes (DEGs). Functional enrichment analysis and protein-protein interaction (PPI) was used on shared DEGs to reveal underlying mechanisms in SAP-associated sepsis. Machine learning methods including random forest (RF), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) were adopted for screening hub genes. Then, receiver operating characteristic (ROC) curve and nomogram were applied to evaluate the diagnostic performance. Finally, immune cell infiltration analysis was conducted to go deeply into the immunological landscape of sepsis.

Result

We obtained a total of 123 DEGs through cross analysis between Differential expression analysis and WGCNA important module. The Gene Ontology (GO) analysis uncovered the shared genes exhibited a significant enrichment in regulation of inflammatory response. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the shared genes were primarily involved in immunoregulation by conducting NOD-like receptor (NLR) signaling pathway. Three machine learning results revealed that two overlapping genes (ARG1, HP) were identified as shared hub genes for SAP and sepsis. The immune infiltration results showed that immune cells played crucial part in the pathogenesis of sepsis and the two hub genes were substantially associated with immune cells, which may be a therapy target.

Conclusion

ARG1 and HP may affect SAP and sepsis by regulating inflammation and immune responses, shedding light on potential future diagnostic and therapeutic approaches for SAP-associated sepsis.

Association between red blood cell distribution width and 30-day mortality in critically ill septic patients: a propensity score-matched study

BACKGROUND

Sepsis is the leading cause of death worldwide, and a number of biomarkers have been developed for early mortality risk stratification. Red blood cell distribution width (RDW) is a routinely available hematological data and has been found to be associated with mortality in a number of diseases; therefore, we aim to address the association between RDW and mortality in critically ill patients with sepsis.

METHODS

We analyzed data of critically ill adult patients with sepsis on the TriNetX platform, excluding those with hematologic malignancies, thalassemia, and iron deficiency anemia. Propensity score-matching (PSM) (1:1) was used to mitigate confounding effects, and hazard ratio (HR) with 95% confidence (CI) was calculated to determine the association between RDW and 30-day mortality. We further conducted sensitivity analyses through using distinct cut-points of RDW and severities of sepsis.

RESULTS

A total of 256,387 critically ill septic patients were included in the analysis, and 40.0% of them had RDW equal to or higher than 16%. After PSM, we found that high RDW was associated with an increased 30-day mortality rate (HR: 1.887, 95% CI 1.847-1.928). The associations were consistent using distinct cut-points of RDW, with the strength of association using cut-points of 12%, 14%, 16%, 18% and 20% were 2.098, 2.204, 1.887, 1.809 and 1.932, respectively. Furthermore, we found consistent associations among critically ill septic patients with distinct severities, with the association among those with shock, receiving mechanical ventilation, bacteremia and requirement of hemodialysis being 1.731, 1.735, 2.380 and 1.979, respectively.

CONCLUSION

We found that RDW was associated with 30-day mortality in critically ill septic patients, underscoring the potential as a prognostic marker in sepsis. More studies are needed to explore the underlying mechanisms.

Inflammatory biomarker-based clinical practice in patients with pneumonia: A systematic review of randomized controlled trials

Objectives: Biomarker-based clinical practice is currently gaining ground and increasingly affects decision making. A variety of biomarkers have been studied through the years and some of them have already an established role in modern medicine, such as procalcitonin (PCT) which has been proposed to reduce antibiotic exposure. We purposed to systematically review all biomarkers examined for guiding the clinical practice in patients with pneumonia.

METHODS

A systematic review on PubMed was performed on April 2023 by two independent researchers using the PRISMA guidelines. Randomized trials which enrolled patients with pneumonia and compared biomarker-guided strategies to standard of care were included.

RESULTS

1242 studies were recorded, from whom 16 were eligible for this study. 14 studies investigated PCT as a biomarker. From these, 8 studies reported on community acquired pneumonia (CAP), 2 on ventilator associated pneumonia (VAP), 1 on aspiration pneumonia, 1 on hospital acquired pneumonia (HAP) and 2 on exacerbation of chronic obstructive pulmonary disease (ECOPD). There was 1 study, referred to VAP, that investigated interleukin-1β (IL-1β) and interleukin-8 (IL-8) and 1 study that reported the role of C-reactive protein (CRP) in ECOPD. In a total of 4751 patients in 15 studies, the biomarker-based approach did not lead to increased mortality [OR: 0.998 (95%CI: 0.74-1.34, p value: 0.991). I2:19%]. Among different types of pneumonia and time-points of assessment, biomarker-guided practice appeared to improve antibiotic-related outcomes, such as rate of antibiotic prescription, duration of antibiotic therapy and rate of antibiotic exposure, while 5 studies reported a possible decrease in antibiotic-related adverse effects. Biomarker-guided practice did not seem to lead in an increase in other adverse outcomes such as need for hospitalization and duration of hospitalization. However, the included studies have high risk of bias mainly due to improper blinding of participants/personnel and outcome assessors.

CONCLUSION

Biomarker-guided clinical practice improves provided healthcare, in terms of reduced antibiotic consumption with no inferiority to mortality, relapses and exacerbations in patients with different types of pneumonia. Thus, such approaches should be further evaluated to achieve personalized medicine.

EXPLORING THE PROGNOSTIC NECROPTOSIS-RELATED GENES AND UNDERLYING MECHANISM IN SEPSIS USING BIOINFORMATICS

ABSTRACT

Sepsis is a life-threatening disease due to a dysregulated host response to infection, with an unknown regulatory mechanism for prognostic necroptosis-related genes (NRGs). Using GEO datasets GSE65682 and GSE134347, we identified six NRG biomarkers ( ATRX , TSC1 , CD40 , BACH2 , BCL2 , and LEF1 ) with survival and diagnostic significance through Kaplan-Meier (KM) and receiver operating characteristic (ROC) analyses. Afterward, the ingenuity pathway analysis (IPA) highlighted enrichment in hepatic fibrosis pathways and BEX2 protein. Moreover, we examined their regulatory targets and functional links with necroptotic signaling molecules via miRDB, TargetScan, Network analyst, and GeneMANIA. The molecular regulatory network displayed that hsa-miR-5195-3p and hsa-miR-145-5p regulated ATRX, BACH2, and CD40, while YY1 showed strong connectivity, concurrently controlling LEF1, ATRX, BCL2, BACH2, and CD40. CD40 exhibited similar expression patterns to RIPK3 and MLKL, and LEF1 was functionally associated with MLKL. Additionally, DrugBank analysis identified paclitaxel, docetaxel, and rasagiline as potential BCL2-targeting sepsis treatments. Finally, real-time quantitative PCR confirmed ATRX, TSC1, and LEF1 downregulation in sepsis samples, contrasting CD40's increased expression in CTL samples. In conclusion, ATRX , TSC1 , CD40 , BACH2 , BCL2 , and LEF1 may be critical regulatory targets of necroptosis in sepsis, providing a basis for further necroptosis-related studies in sepsis.

Towards improved point-of-care (POC) testing for patients with suspected sepsis: POC tests for host biomarkers and possible microbial pathogens

INTRODUCTION

Sepsis is a heterogeneous syndrome often misdiagnosed. Point-of-care (POC) diagnostic tests are commonly used to guide decision and include host biomarkers and molecular diagnostics.

AREAS COVERED

The diagnostic and prognostic accuracy of established and emerging biomarkers for sepsis, including procalcitonin (PCT) soluble urokinase plasminogen activator receptor (suPAR), presepsin, TRAIL/IP-10/CRP, MxA, and MxA-CRP, are analyzed in this review. The clinical utility of the two prevalent molecular techniques for pathogens identification using polymerase chain reaction (PCR) assays is also presented: FILMARRAY and QIAstat-Dx RP.

EXPERT OPINION

The rising benefits of the combined use of POC biomarkers with molecular diagnostics in daily clinical routine appear to outperform conventional practices in terms of reduced turnaround time, timely diagnosis, and prompt administration of the appropriate treatment. Yet, this must be further demonstrated in future investigations. However, the cost-effectiveness of POC tests and the high rate of false positive and negative results, indicate the need for a comprehensive clinical evaluation.

EVALUATION OF VASOPRESSOR INFLECTION POINT FOR SHORT-TERM PROGNOSIS OF PATIENTS WITH SEPTIC SHOCK

ABSTRACT

Objective: The goal of this study is to investigate the clinical value of vasopressor inflection points in the evaluation of short-term prognosis among individuals afflicted with septic shock. Methods: A retrospective analysis was conducted on a cohort comprising 56 patients diagnosed with septic shock and receiving treatment at the department of critical care medicine of the hospital between January 2021 and March 2023. These patients were divided into two groups based on the prognostic outcome: a survival group consisting of 34 patients and a death group consisting of 22 patients. The determination of vasopressor inflection time and procalcitonin (PCT) inflection time of each patient was undertaken with the initiation of vasopressor therapy serving as the reference point. The vasopressor inflection point was defined as the time when the dosage of vasopressors commenced decreasing, while the PCT inflection point denoted the time when PCT levels began to decline. The incidence of patients reaching the vasopressor and PCT inflection points on the 2nd, 3rd, and 4th days following the initiation of vasopressor therapy was tabulated for both groups. The comparison of inflection points between the two groups at each time point was conducted using Fisher's exact test. Furthermore, logistic regression analysis was employed for univariate prognostic assessment. The diagnostic performance of vasopressor and PCT inflection point was assessed using the four-table method. The discrepancy and consistency between the two methods were evaluated through paired chi-squared test and Kappa consistency test. Results: The vasopressor inflection point demonstrates promising utility in the assessment of short-term prognosis among patients with septic shock, exhibiting sensitivities of 76.4%, 88.2%, and 100%, specificities of 90.9%, 90.9%, and 86.4%, positive predictive values of 92.9%, 93.8%, and 91.9%, and negative predictive values of 71.4% on the 2nd, 3rd, and 4th day, respectively. Correspondingly, the Youden indices were calculated as 0.673, 0.791, and 0.864 on these respective days. Notably, all metrics at comparable intervals surpassed those of the PCT inflection point. Conclusion : The vasopressor inflection point presents as a robust prognostic tool for the short-term outcomes in patients with septic shock and exhibits superiority over PCT in prognostic assessment.

Identification of potential biomarkers for sepsis based on neutrophil extracellular trap-related genes

Sepsis is a highly lethal disease that poses a serious threat to human health. Increasing evidence indicates that neutrophil extracellular traps (NETs) are key factors in the pathological progression of sepsis. This study aims to screen potential biomarkers for sepsis and delve into their regulatory function in the pathogenesis. We downloaded 6 microarray datasets from the Gene Expression Omnibus (GEO) database, with 4 as the training sets and 2 as the validation sets. NETs-related genes (NRGs) were obtained from relevant literature. Differential expression analysis was performed on four training sets separately. We intersected differentially expressed genes (DEGs) from the four training sets and NRGs, finally resulting in 19 NETs-related sepsis genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) unearthed that NETs-related sepsis genes were majorly abundant in functions and pathways such as defense response to bacterium and Neutrophil extracellular trap formation. Using the PPI network, the MCC algorithm, and the MCODE algorithm in the CytoHubba plugin, 7 sepsis hub genes (ELANE, TLR4, MPO, PADI4, CTSG, MMP9, S100A12) were identified. ROC curve for each Hub gene in the training and validation sets were plotted, which revealed that the Area Under Curve (AUC) values are all greater than 0.6, indicating good classification ability. A total of 349 miRNAs targeting Hub genes were predicted in the mirDIP database, and 620 lncRNAs targeting miRNAs were predicted in the ENCORI database. The ceRNA regulatory network was constructed using Cytoscape software. Finally, we employed the cMAP database to predict small molecular complexes as potentially effective drugs for the treatment of sepsis, such as chloroquine, harpagoside, and PD-123319. In conclusion, this project successfully identified 7 core genes, which may serve as promising candidates for novel sepsis biomarkers. Meanwhile, we constructed a related ceRNA network and predicted potential targeted drugs, providing potential therapeutic targets and treatment strategies for sepsis patients.

Early identification and diagnosis, pathophysiology, and treatment of sepsis-related acute lung injury: a narrative review

Background and Objective

Sepsis is a life-threatening organ dysfunction, and the most common and vulnerable organ is the lungs, with sepsis-related acute respiratory distress syndrome (ARDS) increasing mortality. In recent years, an increasing number of studies have improved our understanding of sepsis-related ARDS in terms of epidemiology, risk factors, pathophysiology, prognosis, and other aspects, as well as our ability to prevent, detect, and treat sepsis-related ARDS. However, sepsis-related lung injury remains an important issue and clinical burden. Therefore, a literature review was conducted on sepsis-related lung injury in order to further guide clinical practice in reducing the acute and chronic consequences of this condition.

Methods

This study conducted a search of the MEDLINE and PubMed databases, among others for literature published from 1991 to 2023 using the following keywords: definition of sepsis, acute lung injury, sepsis-related acute lung injury, epidemiology, risk factors, early diagnosis of sepsis-related acute lung injury, sepsis, ARDS, pathology and physiology, inflammatory imbalance caused by sepsis, congenital immune response, and treatment.

Key Content and Findings

This review explored the risk factors of sepsis, sepsis-related ARDS, early screening and diagnosis, pathophysiology, and treatment and found that in view of the high mortality rate of ARDS associated with sepsis. In response to the high mortality rate of sepsis-related ARDS, some progress has been made, such as rapid identification of sepsis and effective antibiotic treatment, early fluid resuscitation, lung-protective ventilation, etc.

Conclusions

Sepsis remains a common and challenging critical illness to cure. In response to the high mortality rate of sepsis-related ARDS, progress has been made in rapid sepsis identification, effective antibiotic treatment, early fluid resuscitation, and lung-protective ventilation. However, further research is needed regarding long-term effects such as lung recruitment, prone ventilation, and the application of neuromuscular blocking agents and extracorporeal membrane oxygenation.

Exploring the Effects and Potential Mechanisms of Hesperidin for the Treatment of CPT-11-Induced Diarrhea: Network Pharmacology, Molecular Docking, and Experimental Validation

Chemotherapy-induced diarrhea (CID) is a potentially serious side effect that often occurs during anticancer therapy and is caused by the toxic effects of chemotherapeutic drugs on the gastrointestinal tract, resulting in increased frequency of bowel movements and fluid contents. Among these agents, irinotecan (CPT-11) is most commonly associated with CID. Hesperidin (HPD), a flavonoid glycoside found predominantly in citrus fruits, has anti-oxidation properties and anti-inflammation properties that may benefit CID management. Nevertheless, its potential mechanism is still uncertain. In this study, we firstly evaluated the pharmacodynamics of HPD for the treatment of CID in a mouse model, then used network pharmacology and molecular docking methods to excavate the mechanism of HPD in relieving CID, and finally further proved the predicted mechanism through molecular biology experiments. The results demonstrate that HPD significantly alleviated diarrhea, weight loss, colonic pathological damage, oxidative stress, and inflammation in CID mice. In addition, 74 potential targets for HPD intervention in CID were verified by network pharmacology, with the top 10 key targets being AKT1, CASP3, ALB, EGFR, HSP90AA1, MMP9, ESR1, ANXA5, PPARG, and IGF1. The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed that the PI3K-Akt pathway, FoxO pathway, MAPK pathway, TNF pathway, and Ras pathway were most relevant to the HPD potential treatment of CID genes. The molecular docking results showed that HPD had good binding to seven apoptosis-related targets, including AKT1, ANXA5, CASP3, HSP90AA1, IGF1, MMP9, and PPARG. Moreover, we verified apoptosis by TdT-mediated dUTP nick-end labeling (TUNEL) staining and immunohistochemistry, and the hypothesis about the proteins above was further verified by Western blotting in vivo experiments. Overall, this study elucidates the potential and underlying mechanisms of HPD in alleviating CID.

Sepsis Biomarkers: Advancements and Clinical Applications-A Narrative Review

Sepsis is now defined as a life-threatening syndrome of organ dysfunction triggered by a dysregulated host response to infection, posing significant challenges in critical care. The main objective of this review is to evaluate the potential of emerging biomarkers for early diagnosis and accurate prognosis in sepsis management, which are pivotal for enhancing patient outcomes. Despite advances in supportive care, traditional biomarkers like C-reactive protein and procalcitonin have limitations, and recent studies have identified novel biomarkers with increased sensitivity and specificity, including circular RNAs, HOXA distal transcript antisense RNA, microRNA-486-5p, protein C, triiodothyronine, and prokineticin 2. These emerging biomarkers hold promising potential for the early detection and prognostication of sepsis. They play a crucial role not only in diagnosis but also in guiding antibiotic therapy and evaluating treatment effectiveness. The introduction of point-of-care testing technologies has brought about a paradigm shift in biomarker application, enabling swift and real-time patient evaluation. Despite these advancements, challenges persist, notably concerning biomarker variability and the lack of standardized thresholds. This review summarizes the latest advancements in sepsis biomarker research, spotlighting the progress and clinical implications. It emphasizes the significance of multi-biomarker strategies and the feasibility of personalized medicine in sepsis management. Further verification of biomarkers on a large scale and their integration into clinical practice are advocated to maximize their efficacy in future sepsis treatment.

Biomarkers in sepsis

Sepsis is a life-threatening condition characterized by dysregulated host response to infection leading to organ dysfunction. Despite advances in understanding its pathology, sepsis remains a global health concern and remains a major contributor to mortality. Timely identification is crucial for improving clinical outcomes, as delayed treatment significantly impacts survival. Accordingly, biomarkers play a pivotal role in diagnosis, risk stratification, and management. This review comprehensively discusses various biomarkers in sepsis and their potential application in antimicrobial stewardship and risk assessment. Biomarkers such as white blood cell count, neutrophil to lymphocyte ratio, erythrocyte sedimentation rate, C-reactive protein, interleukin-6, presepsin, and procalcitonin have been extensively studied for their diagnostic and prognostic value as well as in guiding antimicrobial therapy. Furthermore, this review explores the role of biomarkers in risk stratification, emphasizing the importance of identifying high-risk patients who may benefit from specific therapeutic interventions. Moreover, the review discusses the emerging field of transcriptional diagnostics and metagenomic sequencing. Advances in sequencing have enabled the identification of host response signatures and microbial genomes, offering insight into disease pathology and aiding species identification. In conclusion, this review provides a comprehensive overview of the current understanding and future directions of biomarker-based approaches in sepsis diagnosis, management, and personalized therapy.

The potential role of heparin-binding protein in neonatal sepsis: research progress

Neonatal sepsis is a major global health challenge, leading to significant morbidity and mortality in newborns. The search for precise biomarkers for its early prediction in clinical settings has been ongoing, with heparin-binding protein (HBP) emerging as a promising candidate. Originating from granules in neutrophils, HBP is released into the bloodstream in response to infection and plays a pivotal role in the body's inflammatory response. Its significance extends beyond its inflammatory origins; research indicates dynamic changes in HBP levels are strongly linked to reduce in-hospital mortality, offering a prognostic advantage over existing biomarkers. Furthermore, HBP has demonstrated considerable clinical utility in the early diagnosis and stratification of neonatal sepsis, suggesting its potential as a reliable blood marker for early prediction of the disease and its severity. Its application may extend to guiding the judicious use of antibiotics in treating newborns, addressing a critical aspect of neonatal care. Despite these encouraging results, the precise clinical utility of HBP for diagnosing and treating sepsis in neonates still demands further clarification through extensive research. This review delves into the current scientific understanding of HBP's contribution to diagnosing, prognosticating, and treating neonatal sepsis, while considering its future clinical applications.

Protective effects of DcR3-SUMO on lipopolysaccharide-induced inflammatory cells and septic mice

Despite the high mortality rate associated with sepsis, no specific drugs are available. Decoy receptor 3 (DcR3) is now considered a valuable biomarker and therapeutic target for managing inflammatory conditions. DcR3-SUMO, an analog of DcR3, has a simple production process and high yield. However, its precise underlying mechanisms in sepsis remain unclear. This study investigated the protective effects of DcR3-SUMO on lipopolysaccharide (LPS)-induced inflammatory cells and septic mice. We evaluated the effects of DcR3 intervention and overexpression on intracellular inflammatory cytokine levels in vitro. DcR3-SUMO significantly reduced cytokine levels within inflammatory cells, and notably increased DcR3 protein and mRNA levels in LPS-induced septic mice, confirming its anti-inflammatory efficacy. Our in vitro and in vivo results demonstrated comparable anti-inflammatory effects between DcR3-SUMO and native DcR3. DcR3-SUMO protein administration in septic mice notably enhanced tissue morphology, decreased sepsis scores, and elevated survival rates. Furthermore, DcR3-SUMO treatment effectively lowered inflammatory cytokine levels in the serum, liver, and lung tissues, and mitigated the extent of tissue damage. AlphaFold3 structural predictions indicated that DcR3-SUMO, similar to DcR3, effectively interacts with the three pro-apoptotic ligands, namely TL1A, LIGHT, and FasL. Collectively, DcR3-SUMO and DcR3 exhibit comparable anti-inflammatory effects, making DcR3-SUMO a promising therapeutic agent for sepsis.

Recent trends in septic shock management: a narrative review of current evidence and recommendations

Septic shock stands for a group of manifestations that will cause a severe hemodynamic and metabolic dysfunction, which leads to a significant increase in the risk of death by a massive response of the immune system to any sort of infection that ends up with refractory hypotension making it responsible for escalating the numbers of hospitalized patients mortality rate, Organisms that are isolated most of the time are Escherichia coli, Klebsiella, Pseudomonas aeruginosa, and Staph aureus. The WHO considers sepsis to be a worldwide health concern; the incidence of sepsis and septic shock have been increasing over the years while being considered to be under-reported at the same time. This review is a quick informative recap of the recent studies regarding diagnostic approaches using lactic acid (Lac), procalcitonin (PCT), Sequential Organ Failure Assessment (SOFA) score, acute physiology and chronic health evaluation II (APACHE II) score, as well as management recommendations for using vasopressors, fluid resuscitation, corticosteroids and antibiotics that should be considered when dealing with such type of shock.

Serial Trend of Neutrophil CD64, C-reactive Protein, and Procalcitonin as a Prognostic Marker in Critically Ill Patients with Sepsis/Septic Shock: A Prospective Observational Study from a Tertiary Care ICU

Aim and background

Neutrophil CD64 (nCD64) is evolving as a prognostic biomarker in sepsis. The primary objective of this study was to evaluate whether serial trend of nCD64, procalcitonin (PCT), and C-reactive protein (CRP) predict 28-day mortality in patients with sepsis/septic shock, as per Sepsis-3 criteria.

Materials and methods

This prospective, observational single-center cohort study included 60 adult patients (age ≥18 years) with sepsis. Serial biomarker levels with SOFA score were measured at admission (day 0), on day 4, and on day 8.

Results

Of the 60 patients, 42 (70%) had septic shock. Biomarker levels at admission did not differ between patients with sepsis and septic shock. Thirty-seven patients survived and 23 were non-survivors by day 28. There was a significant fall in serial trend of all three biomarkers from admission till day 8 (Friedman p < 0.001) in survivors compared to a non-significant change in non-survivors. On multivariate analysis, SOFA score at admission (OR 1.731), more days with vasopressor support (OR 1.077), rise in CD64 from day 0 to day 8 (OR 1.074), and rise in CRP from day 0 to 8 (OR 1.245) were the significant predictors of 28-day mortality (p < 0.05). The highest area under the ROC curve was obtained for more days of vasopressor therapy (0.857), followed by a rise in CD64 from day 0 to day 8 (0.798).

Conclusion

Serial trend of biomarkers has prognostic utility. The rise in CD64 from day 0 to day 8 was a good predictor of mortality compared to the trend of other biomarkers.

How to cite this article

Patnaik R, Azim A, Singh K, Agarwal V, Mishra P, Poddar B, et al. Serial Trend of Neutrophil CD64, C-reactive Protein, and Procalcitonin as a Prognostic Marker in Critically Ill Patients with Sepsis/Septic Shock: A Prospective Observational Study from a Tertiary Care ICU. Indian J Crit Care Med 2024;28(8):777-784.

Fracture related infection and sepsis in orthopedic trauma: A review

Trauma is a leading cause of death in the United States for people under 45. Amongst trauma-related injuries, orthopedic injuries represent a significant component of trauma-related morbidity. In addition to the potential morbidity and mortality secondary to the specific traumatic injury or injuries sustained, sepsis is a significant cause of morbidity and mortality in trauma patients as well, and infection related to orthopedic trauma can be especially devastating. Therefore, infection prevention and early recognition of infections is crucial to lowering morbidity and mortality in trauma. Risk factors for fracture-related infection include obesity, tobacco use, open fracture, and need for flap coverage, as well as fracture of the tibia and the degree of contamination. Timely administration of prophylactic antibiotics for patients presenting with open fractures has been shown to decrease the risk of fracture-related infection, and in patients that do experience sepsis from an orthopedic injury, prompt source control is critical, which may include the removal of implanted hardware in infections that occur more than 6 weeks from operative fixation. Given that orthopedic injury constitutes a significant proportion of traumatic injuries, and will likely continue to increase in number in the future, surgeons caring for patients with orthopedic trauma must be able to promptly recognize and manage sepsis secondary to orthopedic injury.

The performance of a combination of heparin-binding protein with other biomarkers for sepsis diagnosis: an observational cohort study

BACKGROUND

HBP, a novel biomarker released from neutrophils, may induce inflammatory responses and exacerbate vascular permeability, representing the pathophysiological characteristics of sepsis and septic shock. However, it remains uncertain whether the combination of HBP with other biomarkers yields enhanced diagnostic capacity for sepsis. We hypothesized that measurements included IL-6·IL-8·HBP, IL-6·IL-8·HBP/ALB and HBP/ALB which based on HBP will improve its diagnostic efficacy and even better than the traditional infection biomarkers.

METHODS

Between July 2021 and June 2022, we carried out a comprehensive, multi-center, observational cohort study spanning six leading tertiary hospitals located in Heilongjiang Province, China. Patients were stratified into three categories based on the severity of infection: non-sepsis, sepsis, and septic shock. We collected clinical and laboratory data, along with infection and inflammation biomarkers, for analysis.

RESULTS

A total of 195 patients were enrolled. Among the three groups, patients with septic shock (n = 75, 38.5%) had significantly higher baseline levels of HBP, WBC, Lac, CRP, PCT, IL-6, IL-8, and IL-10 compared to non-sepsis patients (n = 43, 22.0%) and sepsis patients (n = 77, 39.5%), with statistically significant differences (p < 0.05) observed for all parameters. When compared to SOFA score and traditional markers of CRP, PCT, IL-6 and IL-8, the combined indexes of IL-6·IL-8·HBP and IL-6·IL-8·HBP/ALB demonstrated significantly improved diagnostic performance for sepsis and septic shock (AUC 0.911 and 0.902 respectively, p < 0.001).

CONCLUSIONS

The combined measurements of IL-6·IL-8·HBP and IL-6·IL-8·HBP/ALB can augment the diagnostic capacity of HBP for sepsis, and offer reliable early supplementary indicators to traditional biomarkers for assessing disease severity in patients with infection.

Development and validation of a machine learning-based interpretable model for predicting sepsis by complete blood cell parameters

Background

Sepsis, a severe infectious disease, carries a high mortality rate. Early detection and prompt treatment are crucial for reducing mortality and improving prognosis. The aim of this research is to develop a clinical prediction model using machine learning algorithms, leveraging complete blood cell (CBC) parameters, to detect sepsis at an early stage.

Methods

The study involved 572 patients admitted to West China Hospital of Sichuan University between July 2020 and September 2021. Among them, 215 were diagnosed with sepsis, while 357 had local infections. Demographic information was collected, and 57 CBC parameters were analyzed to identify potential predictors using techniques such as the Least Absolute Shrinkage and Selection Operator (LASSO), Random Forest (RF), Support Vector Machine (SVM), and eXtreme Gradient Boosting (XGBoost). The prediction model was built using Logistic Regression and evaluated for diagnostic specificity, discrimination, and clinical applicability including metrics such as the area under the curve (AUC), calibration curve, clinical impact curve, and clinical decision curve. Additionally, the model's diagnostic performance was assessed on a separate validation cohort. Shapley's additive explanations (SHAP), and breakdown (BD) profiles were used to explain the contribution of each variable in predicting the outcome.

Results

Among all the machine learning methods' prediction models, the LASSO-based model (λ = min) demonstrated the highest diagnostic performance in both the discovery cohort (AUC = 0.9446, P < 0.001) and the validation cohort (AUC = 0.9001, P < 0.001). Furthermore, upon local analysis and interpretation of the model, we demonstrated that LY-Z, MO-Z, and PLT-I had the most significant impact on the outcome.

Conclusions

The predictive model based on CBC parameters can be utilized as an effective approach for the early detection of sepsis.

The predictive value of peripheral blood cell mitochondrial gene expression in identifying the prognosis in pediatric sepsis at preschool age

Background

Sepsis represents a severe manifestation of infection often accompanied by metabolic disorders and mitochondrial dysfunction. Notably, mitochondrial DNA copy number (mtDNA-CN) and the expression of specific mitochondrial genes have emerged as sensitive indicators of mitochondrial function. To investigate the utility of mitochondrial gene expression in peripheral blood cells for distinguishing severe infections and predicting associated outcomes, we conducted a prospective cohort study.

Methods

We established a prospective cohort comprising 74 patients with non-sepsis pneumonia and 67 cases of sepsis induced by respiratory infections, aging from 2 to 6 years old. We documented corresponding clinical data and laboratory information and collected blood samples upon initial hospital admission. Peripheral blood cells were promptly isolated, and both total DNA and RNA were extracted. We utilized absolute quantification PCR to assess mtDNA-CN, as well as the expression levels of mt-CO1, mt-ND1, and mt-ATP6. Subsequently, we extended these comparisons to include survivors and non-survivors among patients with sepsis using univariate and multivariate analyses. Receiver operating characteristic (ROC) curves were constructed to assess the diagnostic potential.

Results

The mtDNA-CN in peripheral blood cells was significantly lower in the sepsis group. Univariate analysis revealed a significant reduction in the expression of mt-CO1, mt-ND1, and mt-ATP6 in patients with sepsis. However, multivariate analysis did not support the use of mitochondrial function in peripheral blood cells for sepsis diagnosis. In the comparison between pediatric sepsis survivors and non-survivors, univariate analysis indicated a substantial reduction in the expression of mt-CO1, mt-ND1, and mt-ATP6 among non-survivors. Notably, total bilirubin (TB), mt-CO1, mt-ND1, and mt-ATP6 levels were identified as independent risk factors for sepsis-induced mortality. ROC curves were then established for these independent risk factors, revealing areas under the curve (AUCs) of 0.753 for TB (95% CI 0.596-0.910), 0.870 for mt-CO1 (95% CI 0.775-0.965), 0.987 for mt-ND1 (95% CI 0.964-1.000), and 0.877 for mt-ATP6 (95% CI 0.793-0.962).

Conclusion

MtDNA-CN and mitochondrial gene expression are closely linked to the severity and clinical outcomes of infectious diseases. Severe infections lead to impaired mitochondrial function in peripheral blood cells. Notably, when compared to other laboratory parameters, the expression levels of mt-CO1, mt-ND1, and mt-ATP6 demonstrate promising potential for assessing the prognosis of pediatric sepsis.

Machine Learning Screening and Validation of PANoptosis-Related Gene Signatures in Sepsis

Background

Sepsis is a syndrome marked by life-threatening organ dysfunction and a disrupted host immune response to infection. PANoptosis is a recent conceptual development, which emphasises the interconnectedness among multiple programmed cell deaths in various diseases. Nevertheless, the role of PANoptosis in sepsis is still unclear.

Methods

We utilized the GSE65682 dataset to identify PANoptosis-related genes (PRGs) and associated immune characteristics in sepsis, classified sepsis samples based on PRGs using the ConsensusClusterPlus method and applied the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to identify cluster-specific hub genes. Based on PANoptosis -specific DEGs, we compared results from machine learning models and the best-performing model was selected. Predictive efficiency was validated through external dataset, nomogram, survival analysis, quantitative real-time PCR, and western blot.

Results

The expression levels of PRGs were generally dysregulated in sepsis patients compared with normal samples, and higher PRGs expression correlated with increased immune cell infiltration. In addition, two distinct PANoptosis-related clusters were defined, and functional analysis indicated that DEGs associated with these clusters were primarily linked to immune-related pathways. The SVM model was selected as best-performing model, with lower residuals and the highest area under the curve (AUC = 0.967), which was then validated in an external dataset (AUC = 0.989) and through in vivo experiments. Additional validation through nomogram and survival analysis further confirmed its substantial predictive efficacy.

Conclusion

Our findings exposed the intricate association between PANoptosis and sepsis, offering important insights on sepsis diagnosis and potential therapeutic targets.

Enhancing sepsis biomarker development: key considerations from public and private perspectives

Implementation of biomarkers in sepsis and septic shock in emergency situations, remains highly challenging. This viewpoint arose from a public-private 3-day workshop aiming to facilitate the transition of sepsis biomarkers into clinical practice. The authors consist of international academic researchers and clinician-scientists and industry experts who gathered (i) to identify current obstacles impeding biomarker research in sepsis, (ii) to outline the important milestones of the critical path of biomarker development and (iii) to discuss novel avenues in biomarker discovery and implementation. To define more appropriately the potential place of biomarkers in sepsis, a better understanding of sepsis pathophysiology is mandatory, in particular the sepsis patient's trajectory from the early inflammatory onset to the late persisting immunosuppression phase. This time-varying host response urges to develop time-resolved test to characterize persistence of immunological dysfunctions. Furthermore, age-related difference has to be considered between adult and paediatric septic patients. In this context, numerous barriers to biomarker adoption in practice, such as lack of consensus about diagnostic performances, the absence of strict recommendations for sepsis biomarker development, cost and resources implications, methodological validation challenges or limited awareness and education have been identified. Biomarker-guided interventions for sepsis to identify patients that would benefit more from therapy, such as sTREM-1-guided Nangibotide treatment or Adrenomedullin-guided Enibarcimab treatment, appear promising but require further evaluation. Artificial intelligence also has great potential in the sepsis biomarker discovery field through capability to analyse high volume complex data and identify complex multiparametric patient endotypes or trajectories. To conclude, biomarker development in sepsis requires (i) a comprehensive and multidisciplinary approach employing the most advanced analytical tools, (ii) the creation of a platform that collaboratively merges scientific and commercial needs and (iii) the support of an expedited regulatory approval process.

Navigating the Modern Landscape of Sepsis: Advances in Diagnosis and Treatment

Sepsis poses a significant threat to human health due to its high morbidity and mortality rates worldwide. Traditional diagnostic methods for identifying sepsis or its causative organisms are time-consuming and contribute to a high mortality rate. Biomarkers have been developed to overcome these limitations and are currently used for sepsis diagnosis, prognosis prediction, and treatment response assessment. Over the past few decades, more than 250 biomarkers have been identified, a few of which have been used in clinical decision-making. Consistent with the limitations of diagnosing sepsis, there is currently no specific treatment for sepsis. Currently, the general treatment for sepsis is conservative and includes timely antibiotic use and hemodynamic support. When planning sepsis-specific treatment, it is important to select the most suitable patient, considering the heterogeneous nature of sepsis. This comprehensive review summarizes current and evolving biomarkers and therapeutic approaches for sepsis.

Cuproptosis-Related Genes as Prognostic Biomarkers for Sepsis: Insights into Immune Function and Personalized Immunotherapy

Background

This study aimed to discover diagnostic and prognostic biomarkers for sepsis immunotherapy through analyzing the novel cellular death process, cuproptosis.

Methods

We used transcriptome data from sepsis patients to identify key cuproptosis-related genes (CuRGs). We created a predictive model and used the CIBERSORT algorithm to observe the link between these genes and the septic immune microenvironment. We segregated sepsis patients into three subgroups, comparing immune function, immune cell infiltration, and differential analysis. Single-cell sequencing and real-time quantitative PCR were used to view the regulatory effect of CuRGs on the immune microenvironment and compare the mRNA levels of these genes in sepsis patients and healthy controls. We established a sepsis forecast model adapted to heart rate, body temperature, white blood cell count, and cuproptosis key genes. This was followed by a drug sensitivity analysis of cuproptosis key genes.

Results

Our results filtered three key genes (LIAS, PDHB, PDHA1) that impact sepsis prognosis. We noticed that the high-risk group had poorer immune cell function and lesser immune cell infiltration. We also discovered a significant connection between CuRGs and immune cell infiltration in sepsis. Through consensus clustering, sepsis patients were classified into three subgroups. The best immune functionality and prognosis was observed in subgroup B. Single-cell sequencing exposed that the key genes manage the immune microenvironment by affecting T cell activation. The qPCR results highlighted substantial mRNA level reduction of the three key genes in the SP compared to the HC. The prediction model, which combines CuRGs and traditional diagnostic indicators, performed better in accuracy than the other markers. The drug sensitivity analysis listed bisphenol A as highly sensitive to all the key genes.

Conclusion

Our study suggests these CuRGs may offer substantial potential for sepsis prognosis prediction and personalized immunotherapy.

Utilizing procalcitonin, C-reactive protein, and serum amyloid A in combination for diagnosing sepsis due to urinary tract infection

OBJECTIVE

In this study, we aimed to evaluate the combined diagnostic value of procalcitonin (PCT), C-reactive protein (CRP), and serum amyloid A (SAA) in sepsis caused by urinary tract infection.

METHOD

A total of 80 patients with urosepsis who were hospitalized were included in the study group, and 80 patients with urinary tract infection without sepsis were included in the control group. We collected the PCT, SAA, and CRP levels of patients following admission. Subsequently, we conducted a comparative analysis to assess the specificity, accuracy, and sensitivity of combined diagnostic approaches in contrast to individual diagnostic methods for blood PCT, SAA, and CRP.

RESULTS

The levels of PCT, SAA, and CRP in the study group were significantly higher than those in the control group, and the differences were statistically significant (P < 0.01). Multi-factor logistic regression analysis revealed that the levels of PCT (P = 0.003) and SAA (P = 0.014) were associated with urosepsis. The sensitivity of PCT was 87.133% and the specificity was 93.066%, which were higher than that of SAA and CRP. The specificity of the combined detection of the three was 95.670%, which was higher than that of PCT, SAA, and CRP alone. Correlation analysis revealed that PCT had a significant positive correlation with CRP and SAA (P < 0.01), and a weak correlation with white blood cell count (WBC) and fibrinogen (FIB) (P = 0.03 for WBC, P = 0.04 for FIB).

CONCLUSION

PCT, SAA, and CRP indicators in patients with urosepsis are significantly elevated, and all three are valuable in the diagnosis of urosepsis. PCT alone has good diagnostic efficiency for urosepsis, and a certain correlation with other inflammatory factors. The diagnostic efficacy of the three indicators in combination is better than that of any one of the three, and is worthy of widespread clinical application.

Interleukin-6 in Sepsis-Promising but Yet to Be Proven

How to cite this article: Sinha S. Interleukin-6 in Sepsis-Promising but Yet to Be Proven. Indian J Crit Care Med 2024;28(7):629-631.

Combination of Creatinine with Inflammatory Biomarkers (PCT, CRP, hsCRP) for Predicting Postoperative ICU Admissions for Elderly Patients

INTRODUCTION

The number of elderly patients who require surgery as their primary treatment has increased rapidly in recent years. Among 300 million people globally who underwent surgery every year, patients aged 65 years and over accounted for more than 30% of cases. Despite medical advances, older patients remain at higher risk of postoperative complications. Early diagnosis and effective prediction are essential requirements for preventing serious postoperative complications. In this study, we aim to provide new biomarker combinations to predict the incidence of postoperative intensive care unit (ICU) admissions > 24 h in elderly patients.

METHODS

This investigation was conducted as a nested case-control study, incorporating 413 participants aged ≥ 65 years who underwent non-cardiac, non-urological elective surgeries. These individuals underwent a 30-day postoperative follow-up. Before surgery, peripheral venous blood was collected for analyzing serum creatinine (Scr), procalcitonin (PCT), C-reactive protein (CRP), and high-sensitivity CRP (hsCRP). The efficacy of these biomarkers in predicting postoperative complications was evaluated using receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) values.

RESULTS

Postoperatively, 10 patients (2.42%) required ICU admission. Regarding ICU admissions, the AUCs with 95% confidence intervals (CIs) for the biomarker combinations of Scr × PCT and Scr × CRP were 0.750 (0.655-0.845, P = 0.007) and 0.724 (0.567-0.882, P = 0.015), respectively. Furthermore, cardiovascular events were observed in 14 patients (3.39%). The AUC with a 95% CI for the combination of Scr × CRP in predicting cardiovascular events was 0.688 (0.560-0.817, P = 0.017).

CONCLUSION

The innovative combinations of biomarkers (Scr × PCT and Scr × CRP) demonstrated efficacy as predictors for postoperative ICU admissions in elderly patients. Additionally, the Scr × CRP also had a moderate predictive value for postoperative cardiovascular events.

TRIAL REGISTRATION

China Clinical Trial Registry, ChiCTR1900026223.

Circulating Nucleosomes as a Novel Biomarker for Sepsis: A Scoping Review

Circulating nucleosome levels are commonly elevated in physiological and pathological conditions. Their potential as biomarkers for diagnosing and prognosticating sepsis remains uncertain due, in part, to technical limitations in existing detection methods. This scoping review explores the possible role of nucleosome concentrations in the diagnosis, prognosis, and therapeutic management of sepsis. A comprehensive literature search of the Cochrane and Medline libraries from 1996 to 1 February 2024 identified 110 potentially eligible studies, of which 19 met the inclusion criteria, encompassing a total of 39 SIRS patients, 893 sepsis patients, 280 septic shock patients, 117 other ICU control patients, and 345 healthy volunteers. The enzyme-linked immunosorbent assay [ELISA] was the primary method of nucleosome measurement. Studies consistently reported significant correlations between nucleosome levels and other NET biomarkers. Nucleosome levels were higher in patients with sepsis than in healthy volunteers and associated with disease severity, as indicated by SOFA and APACHE II scores. Non-survivors had higher nucleosome levels than survivors. Circulating nucleosome levels, therefore, show promise as early markers of NETosis in sepsis, with moderate diagnostic accuracy and strong correlations with disease severity and prognosis. However, the available evidence is drawn mainly from single-center, observational studies with small sample sizes and varied detection methods, warranting further investigation.

Challenges and Advances in Biomarker Detection for Rapid and Accurate Sepsis Diagnosis: An Electrochemical Approach

Sepsis is a life-threatening condition with high mortality rates due to delayed treatment of patients. The conventional methodology for blood diagnosis takes several hours, which suspends treatment, limits early drug administration, and affects the patient's recovery. Thus, rapid, accurate, bedside (onsite), economical, and reliable sepsis biomarker reading of the clinical sample is an emergent need for patient lifesaving. Electrochemical label-free biosensors are specific and rapid devices that are able to perform analysis at the patient's bedside; thus, they are considered an attractive methodology in a clinical setting. To reveal their full diagnostic potential, electrode architecture strategies of fabrication are highly desirable, particularly those able to preserve specific antibody-antigen attraction, restrict non-specific adsorption, and exhibit high sensitivity with a low detection limit for a target biomarker. The aim of this review is to provide state-of-the-art methodologies allowing the fabrication of ultrasensitive and highly selective electrochemical sensors for sepsis biomarkers. This review focuses on different methods of label-free biomarker sensors and discusses their advantages and disadvantages. Then, it highlights effective ways of avoiding false results and the role of molecular labels and functionalization. Recent literature on electrode materials and antibody grafting strategies is discussed, and the most efficient methodology for overcoming the non-specific attraction issues is listed. Finally, we discuss the existing electrode architecture for specific biomarker readers and promising tactics for achieving quick and low detection limits for sepsis biomarkers.

Analysis of the effects of early screening combined with blood lactate on the severity of patients with sepsis

This work aimed to investigate the adoption value of blood lactic acid (BLA) combined with the National Early Warning Score (NEWS) in the early screening of sepsis patients and assessing their severity. The data and materials utilized in this work were obtained from the electronic medical record system of 537 anonymized sepsis patients who received emergency rescue in the emergency rescue area of Liuzhou People's Hospital, Guangxi, from July 1, 2020, to December 26, 2020. Based on the 28-day outcomes of sepsis patients, the medical records were rolled into Group S (407 survival cases) and Group D (130 dead cases). Basic information such as the mode of hospital admission, initial management, use of emergency ventilator within 24 h of admission, NEWS score, arterial oxygen pressure/alveolar oxygen pressure ratio (PaO2/PAO2), alveolar-arterial oxygen difference (A-aDO2), serum creatinine (SCr), blood urea nitrogen (BUN), oxygenation index (OI), Glasgow Coma Scale (GCS), D-dimer, use of vasoactive drugs within 24 h of admission, C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), N-terminal pro-B-type natriuretic peptide (NT-proBNP), quick Sequential Organ Failure Assessment (qSOFA) score, SOFA score, BLA level, NEWS with lactate (NEWS-L) score, SOFA score including lactate level (SOFA-L) score, Intensive Care Unit (ICU) length of stay, total hospital stay, ICU stay/total hospital stay, and septic shock condition were compared between groups. Logistic regression analysis was performed to assess the impact of various predictive factors on prognosis and to plot the receiver operating characteristic (ROC) curve. The results suggested marked differences between Group S and Group D in terms of mean age (t = -5.620; OR = -9.96, 95 % CI: -13.44∼-6.47; P < 0.001). Group S showed drastic differences in terms of mode of hospital admission (χ2 = 9.618, P < 0.01), method of initial management (χ2 = 51.766, P < 0.001), use of emergency ventilator within 24 h of admission (χ2 = 98.564, P < 0.001), incidence of septic shock (χ2 = 77.545, P < 0.001), use of vasoactive drugs within 24 h of admission (χ2 = 102.453, P < 0.001), heart rate (t = -4.063, P < 0.001), respiratory rate (t = -4.758, P < 0.001), oxygenation status (χ2 = 20.547, P < 0.001), NEWS score (t = -6.120, P < 0.001), PaO2/PAO2 ratio (t = 2.625, P < 0.01), A-aDO2 value (Z = -3.581, P < 0.001), OI value (Z = -3.106, P < 0.01), PLT value (Z = -2.305, P < 0.05), SCr value (Z = -3.510, P < 0.001), BUN value (Z = -3.170, P < 0.01), D-dimer (Z = -4.621, P < 0.001), CRP level (Z = -4.057, P < 0.001), PCT value (Z = -2.783, P < 0.01), IL-6 level (Z = -2.904, P < 0.001), length of hospital stay (Z = -4.138, P < 0.001), total hospital stay (Z = -8.488, P < 0.001), CCU/total hospital stay (Z = -9.118, P < 0.001), NEWS score (t = -6.120, P < 0.001), SOFA score (t = -6.961, P < 0.001), SOFA-L score (Z = -4.609, P < 0.001), NEWS-L score (Z = -5.845, P < 0.001), BLA level (Z = -6.557, P < 0.001), and GCS score (Z = 6.909, P < 0.001) when compared to Group D. The use of ventilators, septic shock, PCT, NEWS score, GCS score, SOFA score, SOFA-L score, NEWS-L score, and BLA level were identified as independent risk factors for predicting the prognosis of sepsis patients (P < 0.001). The areas under ROC curve (AUC) of blood lactic acid, PCT, NEWS, NEWS-L, GCS, SOFA, and SOFA-L were 0.695, 0.665, 0.692, 0.698, 0.477, 0.700, and 0.653, respectively. These findings indicate that the combination of BLA with NEWS (NEWS-L) score and SOFA score has certain advantages in assessing the prognosis of sepsis.

Heparin-binding protein as a biomarker for the diagnosis of sepsis in the intensive care unit: a retrospective cross-sectional study in China

OBJECTIVES

This study aims to investigate the diagnostic value of heparin-binding protein (HBP) in sepsis and develop a sepsis diagnostic model incorporating HBP with key biomarkers and disease-related scores for rapid, and accurate diagnosis of sepsis in the intensive care unit (ICU).

DESIGN

Clinical retrospective cross-sectional study.

SETTING

A comprehensive teaching tertiary hospital in China.

PARTICIPANTS

Adult patients (aged ≥18 years) who underwent HBP testing or whose blood samples were collected when admitted to the ICU.

MAIN OUTCOME MEASURES

HBP, C reactive protein (CRP), procalcitonin (PCT), white blood cell count (WBC), interleukin-6 (IL-6), lactate (LAC), Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) score were recorded.

RESULTS

Between March 2019 and December 2021, 326 patients were enrolled in this study. The patients were categorised into a non-infection group (control group), infection group, sepsis group and septic shock group based on the final diagnosis. The HBP levels in the sepsis group and septic shock group were 45.7 and 69.0 ng/mL, respectively, which were significantly higher than those in the control group (18.0 ng/mL) and infection group (24.0 ng/mL) (p<0.001). The area under the curve (AUC) value of HBP for diagnosing sepsis was 0.733, which was lower than those corresponding to PCT, CRP and SOFA but higher than those of IL-6, LAC and APACHE II. Multivariate logistic regression analysis identified HBP, PCT, CRP, IL-6 and SOFA as valuable indicators for diagnosing sepsis. A sepsis diagnostic model was constructed based on these indicators, with an AUC of 0.901, a sensitivity of 79.7% and a specificity of 86.9%.

CONCLUSIONS

HBP could serve as a biomarker for the diagnosis of sepsis in the ICU. Compared with single indicators, the sepsis diagnostic model constructed using HBP, PCT, CRP, IL-6 and SOFA further enhanced the diagnostic performance of sepsis.

Biomarkers Improve Diagnostics of Sepsis in Adult Patients With Suspected Organ Dysfunction Based on the Quick Sepsis-Related Organ Failure Assessment (qSOFA) Score in the Emergency Department

OBJECTIVES

Consensus regarding biomarkers for detection of infection-related organ dysfunction in the emergency department is lacking. We aimed to identify and validate biomarkers that could improve risk prediction for overt or incipient organ dysfunction when added to quick Sepsis-related Organ Failure Assessment (qSOFA) as a screening tool.

DESIGN

In a large prospective multicenter cohort of adult patients presenting to the emergency department with a qSOFA score greater than or equal to 1, admission plasma levels of C-reactive protein, procalcitonin, adrenomedullin (either bioavailable adrenomedullin or midregional fragment of proadrenomedullin), proenkephalin, and dipeptidyl peptidase 3 were assessed. Least absolute shrinkage and selection operator regression was applied to assess the impact of these biomarkers alone or in combination to detect the primary endpoint of prediction of sepsis within 96 hours of admission.

SETTING

Three tertiary emergency departments at German University Hospitals (Jena University Hospital and two sites of the Charité University Hospital, Berlin).

PATIENTS

One thousand four hundred seventy-seven adult patients presenting with suspected organ dysfunction based on qSOFA score greater than or equal to 1.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

The cohort was of moderate severity with 81% presenting with qSOFA = 1; 29.2% of these patients developed sepsis. Procalcitonin outperformed all other biomarkers regarding the primary endpoint (area under the curve for receiver operating characteristic [AUC-ROC], 0.86 [0.79-0.93]). Adding other biomarkers failed to further improve the AUC-ROC for the primary endpoint; however, they improved the model regarding several secondary endpoints, such as mortality, need for vasopressors, or dialysis. Addition of procalcitonin with a cutoff level of 0.25 ng/mL improved net (re)classification by 35.2% compared with qSOFA alone, with positive and negative predictive values of 60.7% and 88.7%, respectively.

CONCLUSIONS

Biomarkers of infection and organ dysfunction, most notably procalcitonin, substantially improve early prediction of sepsis with added value to qSOFA alone as a simple screening tool on emergency department admission.

Can serum NSE predict and evaluate sepsis-associated encephalopathy: A protocol for a systematic review and meta-analysis

INTRODUCTION

Brain dysfunction in sepsis is known as sepsis-associated encephalopathy (SAE), which often results in severe cognitive and neurological sequelae and increases the risk of death. Neuron specific enolase (NSE) may serve as an important neurocritical biomarker for detection and longitudinal monitoring in SAE patients. Our systematic review and meta-analysis will aim to explore the diagnostic and prognostic value of serum NSE in SAE patients. Currently, no systematic review and meta-analysis have been assessed that NSE as a biomarker of SAE.

METHODS AND ANALYSIS

We will conduct a systematic review and meta-analysis of serum NSE for the diagnostic and prognostic value of SAE patients. The primary objective is to evaluate the diagnostic accuracy of serum NSE as an independent biomarker for SAE. The secondary objective is to determine the prognostic strength of serum NSE as an independent biomarker of mortality in septic patients determine. We will perform a systematic search and descriptive review using the MEDLINE database and the PubMed interface. We will assign two independent reviewers to review all collected titles and associated abstracts, review full articles, and extract study data. We will use the Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) assessment tool according to the recommendation by the Cochrane Collaboration to evaluate quality and risk of bias of the selected studies. Subgroup and sensitivity analyses will also be used to assess heterogeneity. Review Manager version 5.4 and Stata16.0. will be used for statistical analysis.

ETHICS AND DISSEMINATION

The meta-analysis will provide ICU physicians with the most current information to predict which patients are at risk of SAE and take corresponding intervention measures to reduce morbidity and ameliorate neurological outcomes. There is no need for ethics approval for this review. The findings will be disseminated in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

CRD42023398736.

Procalcitonin and C-reactive protein as early predictors in patients at high risk of colorectal anastomotic leakage

OBJECTIVE

To assess the diagnostic value of C-reactive protein (CRP) and procalcitonin (PCT) for anastomotic leakage (AL) following colorectal surgery.

METHODS

We retrospectively analyzed data for patients who underwent colorectal surgery at our hospital between November 2019 and December 2023. CRP and PCT were measured postoperatively to compare patients with/without AL, and changes were compared between low- and high-risk groups. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic accuracy of CRP and PCT to identify AL in high-risk patients.

RESULTS

Mean CRP was 142.53 mg/L and 189.57 mg/L in the low- and high-risk groups, respectively, on postoperative day (POD)3. On POD2, mean PCT was 2.75 ng/mL and 8.16 ng/mL in low- and high-risk patients, respectively; values on POD3 were 3.53 ng/mL and 14.86 ng/mL, respectively. The areas under the curve (AUC) for CRP and PCT on POD3 were 0.71 and 0.78, respectively (CRP cut-off: 235.64 mg/L; sensitivity: 96%; specificity: 89.42% vs PCT cut-off: 3.94 ng/mL; sensitivity: 86%; specificity: 93.56%; AUC: 0.78). The AUC, sensitivity, and specificity for the combined diagnostic ability of CRP and PCT on POD3 were 0.92, 90%, and 100%, respectively (cut-off: 0.44).

CONCLUSIONS

Combining PCT and CRP on POD3 enhances the diagnostic accuracy for AL.

Hospital Acquired Sepsis, Disease Prevalence, and Recent Advances in Sepsis Mitigation

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection, commonly associated with nosocomial transmission. Gram-negative bacterial species are particularly problematic due to the release of the lipopolysaccharide toxins upon cell death. The lipopolysaccharide toxin of E. coli has a greater immunogenic potential than that of other Gram-negative bacteria. The resultant dysregulation of the immune system is associated with organ failure and mortality, with pregnant women, ICU patients, and neonates being particularly vulnerable. Additionally, sepsis recovery patients have an increased risk of re-hospitalisation, chronic illness, co-morbidities, organ damage/failure, and a reduced life expectancy. The emergence and increasing prevalence of antimicrobial resistance in bacterial and fungal species has impacted the treatment of sepsis patients, leading to increasing mortality rates. Multidrug resistant pathogens including vancomycin-resistant Enterococcus, beta lactam-resistant Klebsiella, and carbapenem-resistant Acinetobacter species are associated with an increased risk of mortality. To improve the prognosis of sepsis patients, predominantly high-risk neonates, advances must be made in the early diagnosis, triage, and control of sepsis. The identification of suitable biomarkers and biomarker combinations, coupled with machine learning and artificial intelligence, show promise in early detection protocols. Rapid diagnosis of sepsis in patients is essential to inform on clinical treatment, especially with resistant infectious agents. This timely review aims to discuss sepsis prevalence, aetiology, and recent advances towards disease mitigation and control.

Augmented Fluorescence Signaling on a Single BaTiO3 Microbead Optical Booster toward High-Sensitive Biosensing

In this work, we report a new generation of single microbead bioassay that employs a single BaTiO3 microbead as an optical booster for target biomarker enrichment and optical enhancement toward protein and nucleic acid analysis. The single BaTiO3 microbead can not only concentrate the target molecules by nearly 104-fold but also act as an optical booster to prominently enhance the target-induced fluorescence signal by the whispering gallery mode for improving the excitation efficiency and the microlens effect for promoting the signal collecting efficiency, respectively. Compared with using a conventional single microbead, this optical booster exhibits nearly 2 orders of magnitude higher sensitivity without the assistance of any signal amplification techniques or costly instruments. Moreover, this single microbead optical booster is capable of detecting different kinds of protein and nucleic acid biomarkers in a simple mix-and-read manner, holding great potential for early clinical diagnosis.

Dynamic Changes in Soluble Triggering Receptor Expressed on Myeloid Cells-1 in Sepsis with Respect to Antibiotic Susceptibility

Purpose

Proper antibiotic administration is crucial for sepsis management. Given the escalating incidence of antimicrobial resistance, there is a pressing need for indicators of antimicrobial susceptibility with short turnaround times. This study aimed to investigate the potential of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) as an early biomarker for in vivo antibiotic susceptibility in patients with sepsis.

Patients and Methods

We conducted a retrospective analysis of plasma samples from patients enrolled in a pre-established study designed to investigate prognostic biomarkers in patients with sepsis or septic shock. Baseline and 6 h sTREM-1 levels were examined using enzyme-linked immunosorbent assays. The primary outcome of the study was the comparison of percentage changes in sTREM-1 levels at the 6 h relative to baseline with respect to antibiotic susceptibility.

Results

Of the 596 patients enrolled in the pre-established study, 29 with a median age of 75.8 and a 28-day mortality rate of 17.2% were included in the present analysis. Among these patients, 24 were classified into the susceptible group, whereas the remaining five were classified into the resistant group. The trend in plasma sTREM-1 levels differed with respect to antibiotic susceptibility. Moreover, percentage change in sTREM-1 levels at the 6 h relative to baseline was significantly higher in the resistant group (P = 0.028).

Conclusion

The trend in plasma sTREM-1 levels in patients with sepsis differed with respect to antibiotic susceptibility, with a higher percentage change in patients treated with inappropriate antibiotics. These findings indicate the potential utility of sTREM-1 as an early biomarker of antibiotic susceptibility.

Conventional and unconventional T-cell responses contribute to the prediction of clinical outcome and causative bacterial pathogen in sepsis patients

Sepsis is characterized by a dysfunctional host response to infection culminating in life-threatening organ failure that requires complex patient management and rapid intervention. Timely diagnosis of the underlying cause of sepsis is crucial, and identifying those at risk of complications and death is imperative for triaging treatment and resource allocation. Here, we explored the potential of explainable machine learning models to predict mortality and causative pathogen in sepsis patients. By using a modelling pipeline employing multiple feature selection algorithms, we demonstrate the feasibility of identifying integrative patterns from clinical parameters, plasma biomarkers, and extensive phenotyping of blood immune cells. While no single variable had sufficient predictive power, models that combined five and more features showed a macro area under the curve (AUC) of 0.85 to predict 90-day mortality after sepsis diagnosis, and a macro AUC of 0.86 to discriminate between Gram-positive and Gram-negative bacterial infections. Parameters associated with the cellular immune response contributed the most to models predictive of 90-day mortality, most notably, the proportion of T cells among PBMCs, together with expression of CXCR3 by CD4+ T cells and CD25 by mucosal-associated invariant T (MAIT) cells. Frequencies of Vδ2+ γδ T cells had the most profound impact on the prediction of Gram-negative infections, alongside other T-cell-related variables and total neutrophil count. Overall, our findings highlight the added value of measuring the proportion and activation patterns of conventional and unconventional T cells in the blood of sepsis patients in combination with other immunological, biochemical, and clinical parameters.

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

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

Serum Mrp 8/14 as a Potential Biomarker for Predicting the Occurrence of Acute Respiratory Distress Syndrome Induced by Sepsis: A Retrospective Controlled Study

Background

To date, there are no studies regarding the Mrp 8/14 in predicting the occurrence of acute respiratory distress syndrome (ARDS) induced by sepsis. Thus, the objective of this study was to investigate the expression of Myeloid-related proteins 8 and 14 (Mrp 8/14) and its role in ARDS induced by sepsis.

Methods

A total of 168 septic patients were enrolled in the observational study. The baseline information and clinical outcomes were obtained retrospectively. Serum Mrp 8/14 level was determined by enzyme linked immunosorbent assay (ELISA). The patients were categorized into sepsis and ARDS group based on whether they developed ARDS during the intensive care unit (ICU) hospitalization.

Results

There was significant difference in the level of Mrp 8/14 between the sepsis group and ARDS groups (P < 0.05). Mrp 8/14 correlated positively with procalcitonin (PCT), interleukin-6 (IL-6), acute physiology and chronic health evaluation II (APACHE II) score, sequential organ failure assessment (SOFA) score on day 1, mechanical ventilation time, length of ICU stay and hospitalization expenses in ICU (all P < 0.05). Logistic regression analysis showed Mrp 8/14 was the independent factor for forecasting the occurrence of sepsis- induced ARDS (P < 0.05). The areas under receiver operating characteristic curves for Mrp 8/14 were higher than that of PCT, APACHE II score and SOFA score on day 1 (P < 0.05).

Conclusion

The serum Mrp 8/14 level at admission may be a potential marker for predicting the occurrence of ARDS induced by sepsis. Early detection of serum Mrp 8/14 could help clinicians to identify and evaluate the severity of ARDS induced by sepsis.