Pentraxin-3 as a predictive marker of mortality in sepsis: an updated systematic review and meta-analysis

Brain natriuretic peptide as a predictive marker of mortality in sepsis: an updated systematic review and meta-analysis

INTRODUCTION

Early identification of patients with sepsis at high risk of death remains a challenge, and whether brain natriuretic peptide (BNP) or N-terminal pro-B-type natriuretic peptide (NT-proBNP) has a prognostic effect on patients with sepsis is controversial. Here, we clarified the prognostic value of BNP and NT-proBNP and sought to establish suitable cutoff values and intervals.

METHODS

We searched five databases to identify studies that met the inclusion criteria. The primary outcomes were the pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), area under the curve (AUC), and corresponding 95% credible interval (95% CI) of BNP and NT-proBNP. The secondary outcomes were the sensitivity and specificity of BNP or NT-proBNP in subgroup analyses.

RESULTS

Forty-seven studies were included in our meta-analysis. The pooled sensitivity of NT-proBNP (0.77 [0.68, 0.84]) was weaker than that of BNP (0.82 [0.76, 0.87]), the pooled specificity of NT-proBNP (0.70 [0.60, 0.77]) was less than that of BNP (0.77 [0.71, 0.82]), and the AUC of BNP (0.87 [0.83-0.89]) was greater than that of NT-proBNP (0.80 (0.76-0.83]). The results of the subgroup analysis showed that the cutoff range of 400-800 pg/mL for BNP had high sensitivity (0.86 [0.74-0.98]) and specificity (0.87 [0.81-0.93]) and was probably the most appropriate cutoff range.

CONCLUSIONS

Elevated levels of BNP and NT-proBNP were significantly related to the mortality of patients with sepsis and had a moderate prognostic value in predicting the mortality of patients with sepsis. In addition, our meta-analysis preliminarily established appropriate cutoff values for BNP and NT-proBNP.

IDENTIFICATION OF A NOVEL SEPSIS PROGNOSIS MODEL: BASED ON TRANSCRIPTOME AND PROTEOME ANALYSIS

ABSTRACT

Sepsis is a highly prevalent and deadly disease. Currently, there is a lack of ideal biomarker prognostis models for sepsis. We attempt to construct a model capable of predicting the prognosis of sepsis patients by integrating transcriptomic and proteomic data. Through analysis of proteomic and transcriptomic data, we identified 25 differentially expressed genes (DEGs). Single-factor Cox-Lasso regression analysis identified 16 DEGs (overall survival-DEGs) associated with patient prognosis. Through multifactor Cox-Lasso regression analysis, a prognostic model based on these 16 genes was constructed. Kaplan-Meier survival analysis and receiver operating characteristic curve analysis were used to further validate the high stability and good predictive ability of this prognostic model with internal and external data. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis of overall survival-DEGs and differentially expressed genes between high and low-risk groups based on the prognostic model revealed significant enrichment in immune-related pathways, particularly those associated with viral regulation.

Progress in the study of pentraxin-3(PTX-3) as a biomarker for sepsis

Sepsis is a intricate pathological process characterized by life-threatening organ dysfunction resulting from a dysregulated host response to infection. It stands as a prominent cause of mortality among critically ill patients globally. The pivotal focus in sepsis management lies in the early identification and prompt administration of antimicrobial agents. Owing to the constraints of current diagnostic methodologies, marked by insufficient sensitivity and delayed outcomes, extensive research has been undertaken to ascertain novel biomarkers for sepsis. In this review, we provide an overview discussing the latest advancements in the study of PTX-3 as a biomarker for sepsis. We acknowledge pivotal discoveries from preceding research and engage in discourse regarding the challenges and limitations confronted by PTX-3 as a sepsis biomarker.

Hic-5 regulates extracellular matrix-associated gene expression and cytokine secretion in cancer associated fibroblasts

The focal adhesion protein, Hic-5 plays a key role in promoting extracellular matrix deposition and remodeling by cancer associated fibroblasts within the tumor stroma to promote breast tumor cell invasion. However, whether stromal matrix gene expression is regulated by Hic-5 is still unknown. Utilizing a constitutive Hic-5 knockout, Mouse Mammary Tumor Virus-Polyoma Middle T-Antigen spontaneous breast tumor mouse model, bulk RNAseq analysis was performed on cancer associated fibroblasts isolated from Hic-5 knockout mammary tumors. Functional network analysis highlighted a key role for Hic-5 in extracellular matrix organization, with both structural matrix genes, as well as matrix remodeling genes being differentially expressed in relation to Hic-5 expression. The subcellular distribution of the MRTF-A transcription factor and expression of a subset of MRTF-A responsive genes was also impacted by Hic-5 expression. Additionally, cytokine array analysis of conditioned media from the Hic-5 and Hic-5 knockout cancer associated fibroblasts revealed that Hic-5 is important for the secretion of several key factors that are associated with matrix remodeling, angiogenesis and immune evasion. Together, these data provide further evidence of a central role for Hic-5 expression in cancer associated fibroblasts in regulating the composition and organization of the tumor stroma microenvironment to promote breast tumor progression.

Immunosuppression in Sepsis: Biomarkers and Specialized Pro-Resolving Mediators

Severe infection can lead to sepsis. In sepsis, the host mounts an inappropriately large inflammatory response in an attempt to clear the invading pathogen. This sustained high level of inflammation may cause tissue injury and organ failure. Later in sepsis, a paradoxical immunosuppression occurs, where the host is unable to clear the preexisting infection and is susceptible to secondary infections. A major issue with sepsis treatment is that it is difficult for physicians to ascertain which stage of sepsis the patient is in. Sepsis treatment will depend on the patient's immune status across the spectrum of the disease, and these immune statuses are nearly polar opposites in the early and late stages of sepsis. Furthermore, there is no approved treatment that can resolve inflammation without contributing to immunosuppression within the host. Here, we review the major mechanisms of sepsis-induced immunosuppression and the biomarkers of the immunosuppressive phase of sepsis. We focused on reviewing three main mechanisms of immunosuppression in sepsis. These are lymphocyte apoptosis, monocyte/macrophage exhaustion, and increased migration of myeloid-derived suppressor cells (MDSCs). The biomarkers of septic immunosuppression that we discuss include increased MDSC production/migration and IL-10 levels, decreased lymphocyte counts and HLA-DR expression, and increased GPR18 expression. We also review the literature on the use of specialized pro-resolving mediators (SPMs) in different models of infection and/or sepsis, as these compounds have been reported to resolve inflammation without being immunosuppressive. To obtain the necessary information, we searched the PubMed database using the keywords sepsis, lymphocyte apoptosis, macrophage exhaustion, MDSCs, biomarkers, and SPMs.

Pentraxin 3: A promising therapeutic target for cardiovascular diseases

Cardiovascular disease (CVD) is the primary global cause of death, and inflammation is a crucial factor in the development of CVDs. The acute phase inflammatory protein pentraxin 3 (PTX3) is a biomarker reflecting the immune response. Recent research indicates that PTX3 plays a vital role in CVDs and has been investigated as a possible biomarker for CVD in clinical trials. PTX3 is implicated in the progression of CVDs through mechanisms such as exacerbating vascular endothelial dysfunction, affecting angiogenesis, and regulating inflammation and oxidative stress. This review summarized the structure and function of PTX3, focusing on its multifaceted effects on CVDs, such as atherosclerosis, myocardial infarction, and hypertension. This may help in explaining the varying PTX3 functions and usage, as well as in utilizing target organs to manage diseases. Moreover, elucidating the opposite role of PTX3 in the cardiovascular system will demonstrate the therapeutic and predictive potential in human diseases.

Clinical Utility of Circulating Pentraxin 3 as a Prognostic Biomarker in Coronavirus Disease 2019: A Systematic Review and Meta-analysis

INTRODUCTION

Pentraxin 3 (PTX3) is involved in inflammation regulation and has a certain association with infectious diseases. However, its specific correlation with infectious diseases remains controversial. This study aimed to analyze the association between them and explore the possible role of PTX3 in the prognosis of coronavirus disease 2019 (COVID-19).

METHODS

Five databases (PubMed, Cochrane Library, Embase, Clinicaltrials.gov, and gray literature) were searched. Outcomes were expressed as a standardized mean difference (SMD) and 95% confidence intervals (CI). The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of included articles. Stata 12 and Meta-DiSc were applied to analyze the pooled data. Receiver operating characteristic (ROC) curves were conducted to determine the prognostic value of PTX3 for mortality.

RESULTS

Six articles met the inclusion criteria. Circulating PTX3 levels had a nonsignificant difference between intensive care unit (ICU) and non-ICU patients with COVID-19 [SMD 1.37 (-0.08, 2.81); I² = 93.9%, P < 0.01], while the PTX3 levels in nonsurvival COVID-19 patients was significantly lower than those in survival patients [SMD -1.41 (-1.92, -0.91); I² = 66.4%, P = 0.051]. Circulating PTX3 had good mortality prediction ability (area under ROC curve, AUC = 0.829) in COVID-19. Funnel plots and Egger's tests showed low probabilities of publication bias. Through sensitivity analysis, the results of this study were robust.

CONCLUSION

This study found that PTX3 was differentially expressed between survival and nonsurvival patients with COVID-19, while there was no significant difference between ICU and non-ICU patients. Meanwhile, circulating PTX3 may be a good biomarker for monitoring the prognosis of COVID-19, which may provide new ideas and directions for clinical and scientific research.

Long pentraxin 3 (PTX3) levels predict death, intubation and thrombotic events among hospitalized patients with COVID-19

BACKGROUND

PTX3 is an important mediator of inflammation and innate immunity. We aimed at assessing its prognostic value in a large cohort of patients hospitalized with COVID-19.

METHODS

Levels of PTX3 were measured in 152 patients hospitalized with COVID-19 at San Gerardo Hospital (Monza, Italy) since March 2020. Cox regression was used to identify predictors of time from admission to in-hospital death or mechanical ventilation. Crude incidences of death were compared between patients with PTX3 levels higher or lower than the best cut-off estimated with the Maximally Selected Rank Statistics Method.

RESULTS

Upon admission, 22% of the patients required no oxygen, 46% low-flow oxygen, 30% high-flow nasal cannula or CPAP-helmet and 3% MV. Median level of PTX3 was 21.7 (IQR: 13.5-58.23) ng/ml. In-hospital mortality was 25% (38 deaths); 13 patients (8.6%) underwent MV. PTX3 was associated with risk of death (per 10 ng/ml, HR 1.08; 95%CI 1.04-1.11; P<0.001) and death/MV (HR 1.04; 95%CI 1.01-1.07; P=0.011), independently of other predictors of in-hospital mortality, including age, Charlson Comorbidity Index, D-dimer and C-reactive protein (CRP). Patients with PTX3 levels above the optimal cut-off of 39.32 ng/ml had significantly higher mortality than the others (55% vs 8%, P<0.001). Higher PTX3 plasma levels were found in 14 patients with subsequent thrombotic complications (median [IQR]: 51.4 [24.6-94.4] versus 21 [13.4-55.2]; P=0.049).

CONCLUSIONS

High PTX3 levels in patients hospitalized with COVID-19 are associated with a worse outcome. The evaluation of this marker could be useful in prognostic stratification and identification of patients who could benefit from immunomodulant therapy.

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

Background

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

Methods

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

Results

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

Conclusion

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