Diagnostic value of serum soluble triggering expressed receptor on myeloid cells 1 (sTREM-1) in suspected sepsis: a meta-analysis

The potential immunological mechanisms of sepsis

Sepsis is described as a life-threatening organ dysfunction and a heterogeneous syndrome that is a leading cause of morbidity and mortality in intensive care settings. Severe sepsis could incite an uncontrollable surge of inflammatory cytokines, and the host immune system's immunosuppression could respond to counter excessive inflammatory responses, characterized by the accumulated anti-inflammatory cytokines, impaired function of immune cells, over-proliferation of myeloid-derived suppressor cells and regulatory T cells, depletion of immune effector cells by different means of death, etc. In this review, we delve into the underlying pathological mechanisms of sepsis, emphasizing both the hyperinflammatory phase and the associated immunosuppression. We offer an in-depth exploration of the critical mechanisms underlying sepsis, spanning from individual immune cells to a holistic organ perspective, and further down to the epigenetic and metabolic reprogramming. Furthermore, we outline the strengths of artificial intelligence in analyzing extensive datasets pertaining to septic patients, showcasing how classifiers trained on various clinical data sources can identify distinct sepsis phenotypes and thus to guide personalized therapy strategies for the management of sepsis. Additionally, we provide a comprehensive summary of recent, reliable biomarkers for hyperinflammatory and immunosuppressive states, facilitating more precise and expedited diagnosis of sepsis.

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.

Advances in sepsis biomarkers

Sepsis, a dysregulated host immune response to an infectious agent, significantly increases morbidity and mortality for hospitalized patients worldwide. This chapter reviews (1) the basic principles of infectious diseases, pathophysiology and current definition of sepsis, (2) established sepsis biomarkers such lactate, procalcitonin and C-reactive protein, (3) novel, newly regulatory-cleared/approved biomarkers, such as assays that evaluate white blood cell properties and immune response molecules, and (4) emerging biomarkers and biomarker panels to highlight future directions and opportunities in the diagnosis and management of sepsis.

Significance of sTREM-1 and sST2 combined diagnosis for sepsis detection and prognosis prediction

The diagnosis of sepsis still lacks a practical and reliable gold standard. The purpose of this study was to confirm the effect of soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) combined with soluble suppression of tumorigenicity 2 (sST2) in the diagnosis of sepsis through the correlation between sTREM-1, sST2, and sequential organ failure assessment (SOFA) scores. Baseline data of 91 patients with sepsis in the intensive care unit were collected, sTREM-1 and sST2 were detected, and the correlation between markers and SOFA score was analyzed. Besides, the prognostic value of baseline and postadmission indicators for sepsis was analyzed with death as the outcome. The results showed that the expressions of sST2 and sTREM-1 in death group and survival group were higher than those in the survival group (p < 0.05). Correlation analysis showed that sST2, sTREM-1, and the joint diagnosis model had a high correlation with SOFA score (p < 0.05), but poor correlation with Acute Physiology and Chronic Health Evaluation Ⅱ score (p > 0.05). Among them, joint diagnosis model has the highest correlation. Receiver operating characteristic curve analysis showed that combined diagnosis had higher area under curve values. sTREM-1/sST2 can be better used in the diagnosis of sepsis than the single biomarker detection, and the combination of the above two biomarkers has potential application value in the detection and prognosis prediction of sepsis.

The Diagnostic Value of Triggering Receptor Expressed on Myeloid Cells-1 in Post-Traumatic Bacterial Endophthalmitis

Purpose

To determine whether soluble-triggering receptor expressed on myeloid cells-1 (sTREM-1) could serve as a reliable diagnostic biomarker of post-traumatic bacterial endophthalmitis (PTBE).

Methods

Thirty-two patients (32 eyes) clinically diagnosed having PTBE were further divided into a culture-positive (CP) group and a culture-negative (CN) group. Sixty-two patients (62 eyes) without traumatic endophthalmic infection were also enrolled. Twenty-one eyes from 11 donors without globe ocular injuries were included as control group. Vitreous sTREM-1 levels were detected by ELISA. The expression and tissue distribution of TREM-1 were revealed by immunohistochemistry. The diagnostic value of sTREM-1 was determined by receiver operating characteristic curve (ROC). The correlation between sTREM-1 concentration and final best-corrected visual acuity (FBCVA) and Peyman endophthalmitis score (PES) were also assessed.

Results

The vitreous sTREM-1 level in the PTBE group was higher than that in noninfected group and control group (P < 0.05). No remarkable difference was found between the CP group and the CN group in vitreous sTREM-1 levels (P > 0.05). No remarkable difference was found between the noninfected group and the control group (P > 0.05). No remarkable difference in TREM-1 level was found before and after intravitreal antibiotics (P > 0.05). TREM-1 was selectively highly expressed on the surface of cell membrane of neutrophils and monocytes/macrophages infiltrated in vitreous and uveal of the PTBE group. The area under the ROC curve (AUC) was 0.79 (>0.75), with a medium diagnostic efficiency. The sensitivity and specificity of sTREM-1 to differentiate PTBE from the noninfected intraocular condition were 62.50% and 86.25% separately. A cutoff value >524.50 pg/mL for sTREM-1 was predicted to be PTBE. Vitreous sTREM-1 levels in PTBE group were positively correlated with PES (r = 0.428, P < 0.05). However, sTREM-1 levels and FBCVA did not significantly correlate with one another (P > 0.05).

Conclusions

The sTREM-1 was a promising diagnostic biomarker of PTBE, especially CN-PTBE. Vitreous sTREM-1 levels were linked with intraocular inflammation levels and severity of PTBE.

Combined Multiomics and In Silico Approach Uncovers PRKAR1A as a Putative Therapeutic Target in Multi-Organ Dysfunction Syndrome

Despite all epidemiological, clinical, and experimental research efforts, therapeutic concepts in sepsis and sepsis-induced multi-organ dysfunction syndrome (MODS) remain limited and unsatisfactory. Currently, gene expression data sets are widely utilized to discover new biomarkers and therapeutic targets in diseases. In the present study, we analyzed MODS expression profiles (comprising 13 sepsis and 8 control samples) retrieved from NCBI-GEO and found 359 differentially expressed genes (DEGs), among which 170 were downregulated and 189 were upregulated. Next, we employed the weighted gene co-expression network analysis (WGCNA) to establish a MODS-associated gene co-expression network (weighted) and identified representative module genes having an elevated correlation with age. Based on the results, a turquoise module was picked as our hub module. Further, we constructed the PPI network comprising 35 hub module DEGs. The DEGs involved in the highest-confidence PPI network were utilized for collecting pathway and gene ontology (GO) terms using various libraries. Nucleotide di- and triphosphate biosynthesis and interconversion was the most significant pathway. Also, 3 DEGs within our PPI network were involved in the top 5 significantly enriched ontology terms, with hypercortisolism being the most significant term. PRKAR1A was the overlapping gene between top 5 significant pathways and GO terms, respectively. PRKAR1A was considered as a therapeutic target in MODS, and 2992 ligands were screened for binding with PRKAR1A. Among these ligands, 3 molecules based on CDOCKER score (molecular dynamics simulated-based score, which allows us to rank the binding poses according to their quality and to identify the best pose for each system) and crucial interaction with human PRKAR1A coding protein and protein kinase-cyclic nucleotide binding domains (PKA RI alpha CNB-B domain) via active site binding residues, viz. Val283, Val302, Gln304, Val315, Ile327, Ala336, Ala337, Val339, Tyr373, and Asn374, were considered as lead molecules.

Diagnostic Performance of Transient Elastography Versus Two-Dimensional Shear Wave Elastography for Liver Fibrosis in Chronic Viral Hepatitis: Direct Comparison and a Meta-Analysis

Objective. This systematic review and meta-analysis aimed to compare the diagnostic performance of transient elastography (TE) and two-dimensional shear wave elastography (2D-SWE) for staging liver fibrosis in patients with chronic viral hepatitis (CVH). Methods. Pubmed, Embase, Web of Science, and Cochrane Library were searched (-01/08/2021) for studies comparing TE with 2D-SWE in patients with CVH. Other etiologies of chronic liver disease (CLD) and articles not published in SCI journals were excluded. The bivariate random-effects model was used to pool the performance of the TE and 2D-SWE. Results. Eight articles with a total of 1301 CVH patients were included. The prevalence of significant fibrosis ( $\text{fibrosis}\text{stage}\ge 2$ ), advanced fibrosis ( $\text{fibrosis}\text{stage}\ge 3$ ), and cirrhosis was 50.8%, 44.8%, and 34.7%, respectively. 2D-SWE expressed higher overall accuracy than TE in detecting significant fibrosis (0.93 vs. 0.85, $P=0.04$ ). No significant difference among the overall diagnostic accuracy of TE and 2D-SWE in staging advanced fibrosis and cirrhosis was found. Conclusion. TE and 2D-SWE express good to excellent diagnostic accuracies to stage fibrosis in CVH patients. 2D-SWE compares favorably with TE especially for predicting significant fibrosis.

TREM-1 Modulation Strategies for Sepsis

The triggering receptor expressed on myeloid cells-1 (TREM-1) is a pattern recognition receptor, which can be upregulated in inflammatory diseases as an amplifier of immune responses. Once activated, TREM-1 induces the production and release of pro-inflammatory cytokines and chemokines, in addition to increasing its own expression and circulating levels of the cleaved soluble extracellular portion of TREM-1 (sTREM-1). This amplification of the inflammatory response by TREM-1 has now been considered as a critical contributor to the dysregulated immune responses in sepsis. Studies have shown that in septic patients there is an elevated expression of TREM-1 on immune cells and increased circulating levels of sTREM-1, associated with increased mortality. As a result, a considerable effort has been made towards identifying endogenous ligands of TREM-1 and developing TREM-1 inhibitory peptides to attenuate the exacerbated inflammatory response in sepsis. TREM-1 modulation has proven a promising strategy for the development of therapeutic agents to treat sepsis. Therefore, this review encompasses the ligands investigated as activators of TREM-1 thus far and highlights the development and efficacy of novel inhibitors for the treatment of sepsis and septic shock.

The diagnostic performance of contrast-enhanced CT versus extracellular contrast agent-enhanced MRI in detecting hepatocellular carcinoma: direct comparison and a meta-analysis

To compare the diagnostic value of contrast-enhanced computed tomography (CT) with extracellular contrast agent-enhanced magnetic resonance imaging (ECA-MRI) for the detection of hepatocellular carcinoma (HCC). Pubmed, Embase, Web of Science and Cochrane Library were searched (1/5/2021) for studies comparing contrast-enhanced CT with ECA-MRI in patients suspected of HCC. Studies without head-to-head comparison were excluded. The pooled sensitivity, specificity and summary area under the curve (sAUC) of contrast-enhanced CT and ECA-MRI in detecting HCC was calculated based on bivariate random effects model. Heterogeneity test included threshold effect analysis and meta-regression. Subgroup analyses were conducted according to lesion size (< 20 mm or ≥ 20 mm). Overall, 10 articles containing 1333 patients were deemed suitable for inclusion in this meta-analysis. ECA-MRI displayed increased sensitivity to contrast-enhanced CT in detecting HCC (0.77 vs. 0.63, P < 0.01). The difference in specificity between ECA-MRI and contrast-enhanced CT was not statistically significant (0.93 vs. 0.94, P = 0.25). ECA-MRI yielded higher diagnostic accuracy (sAUCs = 0.88 vs. 0.80, P < 0.01). In the subgroup analysis with a lesion size < 20 mm, ECA-MRI allowed significant gains of accuracy compared to contrast-enhanced CT (0.79 vs. 0.72, P = 0.02). ECA-MRI also outperformed contrast-enhanced CT in patients with lesion size ≥ 20 mm (sAUCs = 0.96 vs. 0.93, P = 0.04). ECA-MRI provided higher sensitivity and accuracy than contrast-enhanced CT in detecting HCC, especially lesions size < 20 mm.

Biomarkers Predicting Tissue Pharmacokinetics of Antimicrobials in Sepsis: A Review

The pathophysiology of sepsis alters drug pharmacokinetics, resulting in inadequate drug exposure and target-site concentration. Suboptimal exposure leads to treatment failure and the development of antimicrobial resistance. Therefore, we seek to optimize antimicrobial therapy in sepsis by selecting the right drug and the correct dosage. A prerequisite for achieving this goal is characterization and understanding of the mechanisms of pharmacokinetic alterations. However, most infections take place not in blood but in different body compartments. Since tissue pharmacokinetic assessment is not feasible in daily practice, we need to tailor antibiotic treatment according to the specific patient’s pathophysiological processes. The complex pathophysiology of sepsis and the ineffectiveness of current targeted therapies suggest that treatments guided by biomarkers predicting target-site concentration could provide a new therapeutic strategy. Inflammation, endothelial and coagulation activation markers, and blood flow parameters might be indicators of impaired tissue distribution. Moreover, hepatic and renal dysfunction biomarkers can predict not only drug metabolism and clearance but also drug distribution. Identification of the right biomarkers can direct drug dosing and provide timely feedback on its effectiveness. Therefore, this might decrease antibiotic resistance and the mortality of critically ill patients. This article fills the literature gap by characterizing patient biomarkers that might be used to predict unbound plasma-to-tissue drug distribution in critically ill patients. Although all biomarkers must be clinically evaluated with the ultimate goal of combining them in a clinically feasible scoring system, we support the concept that the appropriate biomarkers could be used to direct targeted antibiotic dosing.

OUP accepted manuscript

Background

This study aimed to assess the performance of transient elastography (TE), two-dimensional shear wave elastography (2D-SWE), and magnetic resonance elastography (MRE) for staging significant fibrosis and cirrhosis in untreated chronic hepatitis B (CHB) patients.

Methods

Pubmed, Embase, Web of Science, and Cochrane Library were searched for terms involving CHB, TE, 2D-SWE, and MRE. Other etiologies of chronic liver disease, previous treatment in patients, or articles not published in SCI journals were excluded. Hierarchical non-linear models were used to evaluate the diagnostic accuracy of TE, 2D-SWE, and MRE. Heterogeneity was explored via analysis of threshold effect and meta-regression.

Results

Twenty-eight articles with a total of 4,540 untreated CHB patients were included. The summary areas under the receiver-operating characteristic curves (AUROCs) using TE, 2D-SWE, and MRE for predicting significant fibrosis (SF) were 0.84, 0.89, and 0.99, respectively. The AUROC values of TE, 2D-SWE, and MRE for staging cirrhosis were 0.9, 0.94, and 0.99, respectively. Based on the meta-analysis of studies with head-to-head comparison, 2D-SWE is superior to TE (0.92 vs 0.85, P < 0.01) in staging significant fibrosis.

Conclusion

TE, 2D-SWE, and MRE express acceptable diagnostic accuracies in staging significant fibrosis and cirrhosis in untreated CHB patients. 2D-SWE outperforms TE in detecting significant fibrosis in treatment-naive people with hepatitis B virus.

Diagnostic and prognostic predictive values of triggering receptor expressed on myeloid cell-1 expression in neonatal sepsis: A meta-analysis and systematic review

OBJECTIVE

The purpose of this systematic review was to explore the value of the expression level of the triggering receptor expressed on myeloid cell-1 (TREM-1) in the diagnosis and prognosis of neonatal sepsis.

METHODS

A comprehensive search was performed to identify the diagnostic and prognostic predictive values of the TREM-1 expression level in neonatal sepsis. Based on the retrieval strategy, Cochrane Library, Embase, Ovid, ProQuest, PubMed, Scopus, and Web of Science databases were searched from inception to February 2022. Studies were included if they assessed the accuracy of TREM-1 expression in the diagnosis of neonatal sepsis and distinguished survival and death in neonatal sepsis. Two authors independently evaluated the study and extracted the data, including the first author of the literature, country, total study population, basic population characteristics of the study group and the control group, study design (observational studies), type of sample, sepsis onset, type of biomarker, assay method, cut-off, sensitivity, specificity, true positives (TP), false positives (FP), false negatives (FN), and true negatives (TN). A third party will be consulted if disputed. The accuracy of TREM-1 expression in the diagnosis and prognostic prediction of neonatal sepsis was evaluated by a bivariate mixed-effects model. The source of heterogeneity was explored through meta-regression analysis.

RESULTS

Thirteen articles that met the research criteria were included in qualitative analysis, and 11 of them were included in quantitative analysis. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and the area under the summary receiver operator characteristic (SROC) curve of soluble TREM-1 (sTREM-1) were 0.94 (95% CI: 0.82, 0.98), 0.87 (95% CI: 0.70, 0.95), 7.36 (95% CI: 2.75, 19.74), 0.07 (95% CI: 0.02, 0.24), 111.71 (95% CI: 13.24, 942.92), and 0.96 (95% CI: 0.94, 0.98), respectively. Meta-regression and subgroup analysis were used to investigate the heterogeneity, owing to non-threshold effects caused by types of test sample and research design. sTREM-1 as a biomarker for distinguishing survival and death in neonates with sepsis had pooled sensitivity, specificity, area under the SROC curve, PLR, NLR, and DOR of 0.95 (95% CI: 0.83, 0.99), 0.98 (95% CI: 0.68, 1.00), 0.99 (95% CI: 0.97, 0.99), 39.28 (95% CI: 2.13, 723.99), 0.05 (95% CI: 0.01, 0.19), and 789.61 (95% CI: 17.53, 35,560.72), respectively.

CONCLUSION

The study showed that TREM-1 was a potential biomarker for the diagnosis and prognosis of neonatal sepsis. The biggest advantage of this study is that it is the first to comprehensively explore the role of TREM-1 expression in the diagnosis and prognosis of neonatal sepsis. However, there are some limitations in this study, such as the reduced number of clinical studies on TREM-1 expression as a biomarker of neonatal sepsis, regional bias, and differences in detection methods. Hence, more large-scale and high-quality studies are needed to improve diagnostic accuracy.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42022338041.

Risk-stratification of febrile African children at risk of sepsis using sTREM-1 as basis for a rapid triage test

Identifying febrile children at risk of sepsis in low-resource settings can improve survival, but recognition triage tools are lacking. Here we test the hypothesis that measuring circulating markers of immune and endothelial activation may identify children with sepsis at risk of all-cause mortality. In a prospective cohort study of 2,502 children in Uganda, we show that Soluble Triggering Receptor Expressed on Myeloid cells-1 (sTREM-1) measured at first clinical presentation, had high predictive accuracy for subsequent in-hospital mortality. sTREM-1 had the best performance, versus 10 other markers, with an AUROC for discriminating children at risk of death of 0.893 in derivation (95% CI 0.843-0.944) and 0.901 in validation (95% CI 0.856-0.947) cohort. sTREM-1 cutoffs corresponding to a negative likelihood ratio (LR) of 0.10 and a positive LR of 10 classified children into low (1,306 children, 53.1%), intermediate (942, 38.3%) and high (212, 8.6%) risk zones. The estimated incidence of death was 0.5%, 3.9%, and 31.8%, respectively, suggesting sTREM-1 could be used to risk-stratify febrile children. These findings do not attempt to derive a risk prediction model, but rather define sTREM-1 cutoffs as the basis for rapid triage test for all cause fever syndromes in children in low-resource settings.

Diagnostic and prognostic predictive values of circulating sTREM-1 in sepsis: A meta-analysis

BACKGROUND

With the increasing studies regarding the diagnostic value of soluble triggering receptor expressed on myeloid cells (sTREM)-1 in sepsis in recent years, it is essential to make an updated meta-analysis to explore the sepsis differentiation value of circulating sTREM-1 from systemic inflammatory response syndrome (SIRS). Recently, no meta-analysis was made to explore the prognostic predictive value of circulating sTREM-1 in sepsis. Thus, the present aimed to make meta-analyses to explore the diagnostic and prognostic predictive values of circulating sTREM-1 in sepsis.

METHODS

Articles published before March 2021 were searched in databases: PubMed, Web of Science, EMBASE, Medline and Google Scholar. After a summary of sensitivity, specificity, positive likelihood ratios (PLR), negative likelihood ratios (NLR), and diagnostic odds ratio (DOR), the receive-operating characteristics (SROC) curve were performed to summarize true positive (TP) and false positive (FP) rates. Q test and I² were used to explore heterogeneity between studies.

RESULTS

Circulating sTREM-1 showed a high sensitivity (0.85 (95% confidence interval (CI): 0.76-0.91)) and moderate specificity (0.79 (95% CI: 0.70-0.86)) to differentiate sepsis from SIRS. The study showed a high sensitivity (0.80 (95% CI: 0.66-0.89)) and moderate specificity (0.75 (95% CI: 0.69-0.81)) to predict 28-day mortality in sepsis.

CONCLUSION

In conclusion, the present study suggested that circulating sTREM-1 showed diagnostic and prognostic predictive values in sepsis.

Evaluation of "soluble triggering receptor expressed on myeloid cells-1 (sTREM-1), interleukin-1β, and matrix metalloproteinase-8" as a short panel of salivary biomarkers in patients with and without stage III/IV periodontitis and type 2 diabetes mellitus

Background and aim

Periodontitis involves a dynamic disease process, demanding the identification of biomarkers to diagnose the current state of disease activity. Therefore this study assessed the potential of "sTREM-1, IL-1β, and MMP-8" as a short panel of biomarkers of host biological process indicating the inflammatory burden in periodontium and thereby serving as a panel of diagnostic markers in periodontal disease.

Methods

Sixty eight patients were recruited and allotted into four groups comprising of subjects with clinically healthy gingiva and Stage III/IV Periodontitis with and without type 2 diabetes with HbA1c levels in the range of 6.5-7.9%. Periodontal parameters were measured and full mouth radiographic assessment was done. Whole saliva (unstimulated) samples were collected from all patients and estimation of the levels of markers was done employing ELISA.

Results

All the three biomarkers were noted to be the lowest in group I (sTREM-1: 75.63 ± 13.77; IL-1β: 15.67 ± 3.39; MMP-8: 85.83 ± 22.32) and highest in group IV (sTREM-1: 138.83 ± 14.89; IL-1β: 39.19 ± 7.20; MMP-8: 201.15 ± 50.32) with statistically significant difference. The difference observed between groups II and III for all the biomarkers assessed were statistically insignificant. The clinical parameters and HbA1c levels had positive correlation with the levels of biomarkers which was statistically significant.

Conclusion

This study unveils the potential of the short panel of biomarkers ("sTREM-1, IL-1β, and MMP-8") to be used as diagnostic and possible prognostic markers for Periodontitis. It further corroborates the role of type 2 diabetes mellitus in amplifying the diverse processes that result in periodontal destruction.

Evaluation of sTREM1 and suPAR Biomarkers as Diagnostic and Prognostic Predictors in Sepsis Patients

Background

The purpose of this study was to explore the diagnostic role of sTREM1 in the diagnosis of sepsis and in differentiating between sepsis and systemic inflammatory response syndrome (SIRS). We also aimed to assess the prognostic value of suPAR in comparison to sequential organ-failure assessment (SOFA), acute physiology and chronic health evaluation (APACHE) II scores, and 28-day mortality.

Methods

This was a cross-sectional study conducted in the Medical Microbiology and Immunology Department and Central Research Laboratory, Faculty of Medicine, Sohag University from June 2019 to January 2021. The study population was classified into two groups: SIRS (no evidence of infection) and sepsis (with SIRS and evidence of infection). Patients were rated on the SOFA and APACHE II scoring systems at admission and after 7 days. Serum levels of sTREM1 and suPAR were measured by ELISA at the same time points.

Results

CRP and sTREM1 values were significantly higher in the sepsis group than the SIRS group on both days (P<0.0001). The area under the curve (AUC) for CRP was 0.87 on the first day and 0.97 on the seventh, while the AUC for sTREM1 was 1.00 and 0.93 on the first and seventh days, respectively. The sensitivity of sTREM1 was 100% and specificity 84% at a cutoff of 49 pg/mL. There was a significantly positive correlation between CRP and sTREM1 values (P<0.0001). On the seventh day, nonsurvivors had significantly higher serum levels of suPAR (median 4.9 ng/mL) than survivors (median 2.9 ng/mL; P<0.0001). Nonsurvivors also had significantly higher SOFA and APACHE II scores than survivors (P<0.0001 and P<0.0001, respectively).

Conclusion

sTREM1 can be used as a good indicator for diagnosing sepsis in intensive care–unit patients. suPAR can also be used as a predictor of bad prognosis and poor survival at 7 days following admission.

Inflammation and Cell Death of the Innate and Adaptive Immune System during Sepsis

Sepsis is a life-threatening medical condition that occurs when the host has an uncontrolled or abnormal immune response to overwhelming infection. It is now widely accepted that sepsis occurs in two concurrent phases, which consist of an initial immune activation phase followed by a chronic immunosuppressive phase, leading to immune cell death. Depending on the severity of the disease and the pathogen involved, the hosts immune system may not fully recover, leading to ongoing complications proceeding the initial infection. As such, sepsis remains one of the leading causes of morbidity and mortality world-wide, with treatment options limited to general treatment in intensive care units (ICU). Lack of specific treatments available for sepsis is mostly due to our limited knowledge of the immuno-physiology associated with the disease. This review will provide a comprehensive overview of the mechanisms and cell types involved in eliciting infection-induced immune activation from both the innate and adaptive immune system during sepsis. In addition, the mechanisms leading to immune cell death following hyperactivation of immune cells will be explored. The evaluation and better understanding of the cellular and systemic responses leading to disease onset could eventuate into the development of much needed therapies to combat this unrelenting disease.

Novel Diagnostics and Therapeutics in Sepsis

Sepsis management demands early diagnosis and timely treatment that includes source control, antimicrobial therapy, and resuscitation. Currently employed diagnostic tools are ill-equipped to rapidly diagnose sepsis and isolate the offending pathogen, which limits the ability to offer targeted and lowest-toxicity treatment. Cutting edge diagnostics and therapeutics in development may improve time to diagnosis and address two broad management principles: (1) source control by removing the molecular infectious stimulus of sepsis, and (2) attenuation of the pathological immune response allowing the body to heal. This review addresses novel diagnostics and therapeutics and their role in the management of sepsis.

Current Evidence and Limitation of Biomarkers for Detecting Sepsis and Systemic Infection

Sepsis was recently redefined as a life-threatening disease involving organ dysfunction caused by a dysregulated host response to infection. Biomarkers play an important role in early detection, diagnosis, and prognostication. We reviewed six promising biomarkers for detecting sepsis and systemic infection, including C-reactive protein (CRP), procalcitonin (PCT), interleukin-6 (IL-6), CD64, presepsin, and sTREM-1. Among the recent studies, we found the following risks of bias: only a few studies adopted the random or consecutive sampling strategy; extensive case-control analysis, which worsened the over-estimated performance; most of the studies used post hoc cutoff values; and heterogeneity with respect to the inclusion criteria, small sample sizes, and different quantitative synthesis methods applied in meta-analyses. We recommend that CD64 and presepsin should be considered as the most promising biomarkers for diagnosing sepsis. Future studies should enroll a larger sample size with a cohort rather than a case-control study design. A random or consecutive study design with a pre-specified laboratory threshold, consistent sampling timing, and an updated definition of sepsis will also increase the reliability of the studies. Further investigations of appropriate specimens, testing assays, and cutoff levels for specific biomarkers are also warranted.