Biomarkers for sepsis: more than just fever and leukocytosis-a narrative review

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.

Revolution in sepsis: a symptoms-based to a systems-based approach?

Severe infection and sepsis are medical emergencies. High morbidity and mortality are linked to CNS dysfunction, excessive inflammation, immune compromise, coagulopathy and multiple organ dysfunction. Males appear to have a higher risk of mortality than females. Currently, there are few or no effective drug therapies to protect the brain, maintain the blood brain barrier, resolve excessive inflammation and reduce secondary injury in other vital organs. We propose a major reason for lack of progress is a consequence of the treat-as-you-go, single-nodal target approach, rather than a more integrated, systems-based approach. A new revolution is required to better understand how the body responds to an infection, identify new markers to detect its progression and discover new system-acting drugs to treat it. In this review, we present a brief history of sepsis followed by its pathophysiology from a systems' perspective and future opportunities. We argue that targeting the body's early immune-driven CNS-response may improve patient outcomes. If the barrage of PAMPs and DAMPs can be reduced early, we propose the multiple CNS-organ circuits (or axes) will be preserved and secondary injury will be reduced. We have been developing a systems-based, small-volume, fluid therapy comprising adenosine, lidocaine and magnesium (ALM) to treat sepsis and endotoxemia. Our early studies indicate that ALM therapy shifts the CNS from sympathetic to parasympathetic dominance, maintains cardiovascular-endothelial glycocalyx coupling, reduces inflammation, corrects coagulopathy, and maintains tissue O2 supply. Future research will investigate the potential translation to humans.

Immunotherapy in the context of sepsis-induced immunological dysregulation

Sepsis is a clinical syndrome caused by uncontrollable immune dysregulation triggered by pathogen infection, characterized by high incidence, mortality rates, and disease burden. Current treatments primarily focus on symptomatic relief, lacking specific therapeutic interventions. The core mechanism of sepsis is believed to be an imbalance in the host's immune response, characterized by early excessive inflammation followed by late immune suppression, triggered by pathogen invasion. This suggests that we can develop immunotherapeutic treatment strategies by targeting and modulating the components and immunological functions of the host's innate and adaptive immune systems. Therefore, this paper reviews the mechanisms of immune dysregulation in sepsis and, based on this foundation, discusses the current state of immunotherapy applications in sepsis animal models and clinical trials.

Evaluation of ERCP-related perforation: a single-center retrospective study

Background

Endoscopic retrograde cholangiopancreatography (ERCP)-related perforation is a rare and serious adverse event. The aim of our study was to evaluate the risk factors and management of ERCP-related perforation, and to further determine the predictive factors associated with perforation outcome.

Methods

A total of 27,018 ERCP procedures performed at the First Affiliated Hospital of Nanchang University (Nanchang, China) between January 2007 and March 2022 were included in the investigation of ERCP-related perforation. Medical records and endoscopic data were extracted to analyse the risk factors, management, and clinical outcome of ERCP-related perforation.

Results

Seventy-six patients (0.28%) were identified as having experienced perforation following ERCP. Advanced age, Billroth II anatomy, precut sphincterotomy, and papillary balloon dilatation were significantly associated with ERCP-related perforation. Most patients with perforation (n = 65) were recognized immediately during ERCP whereas 11 were recognized later on. The delay in recognition primarily resulted from stent migration (n = 9). In addition, 12 patients experienced poor clinical outcome including death or hospice discharge (n = 3), ICU admission for >3 days (n = 6), and prolonged hospital stay for >1 month due to perforation (n = 3). Cancer and systemic inflammatory response syndrome (SIRS) are associated with a higher risk of poor outcome.

Conclusions

Advanced age, Billroth II anatomy, precut sphincterotomy, and balloon dilation increase the risk of ERCP-related perforation whereas cancer and SIRS independently predicted poor clinical outcome.

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.

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.

Single-cell RNA sequencing reveals cell-cell communication and potential biomarker in sepsis and septic shock patients

BACKGROUND

Sepsis is a disease characterized by infection-induced multiorgan dysfunction, which can progress to septic shock if not promptly treated. Early identification of sepsis is crucial for its treatment. However, there are currently limited specific biomarkers for sepsis or septic shock. This study aims to identify potential biomarkers for sepsis and septic shock.

METHODS

We analyzed single-cell transcriptomic data of peripheral blood mononuclear cells (PBMCs) from healthy individuals, sepsis and septic shock patients, identified differences in gene expression and cell-cell communication between different cell types during disease progression. Moreover, our analyses were further validated with flow cytometry and bulk RNA-seq data.

RESULTS

Our study elucidates the alterations in cellular proportions and cell-cell communication among healthy controls, sepsis, and septic shock patients. We identified a specific augmentation in the Resistin signaling within sepsis monocytes, mediated via RETN-CAP1 ligand-receptor pairs. Additionally, we observed enhanced IL16 signaling within monocytes from septic shock patients, mediated through IL16-CD4 ligand-receptor pairs. Subsequently, we confirmed our findings by validating the increase in CAP-1+ monocytes in sepsis and IL16+ monocytes in septic shock in mouse models. And a significant upregulation of CAP-1 and IL16 was also observed in the bulk RNA-seq data from patients with sepsis and septic shock. Furthermore, we identified four distinct clusters of CD14+ monocytes, highlighting the heterogeneity of monocytes in the progress of sepsis.

CONCLUSIONS

In summary, our work demonstrates changes in cell-cell communication of healthy controls, sepsis and septic shock, confirming that the molecules CAP-1 and IL16 on monocytes may serve as potential diagnostic markers for sepsis and septic shock, respectively. These findings provide new insights for early diagnosis and stratified treatment of the disease.

Lactate Levels and Clearance: Key Predictors of Prognosis for COVID-19 and Non-COVID-19 Septic Shock Patients in the Emergency Department

BACKGROUND

This investigation assesses the prognostic value of lactate levels and their clearance in septic shock patients, particularly emphasizing the comparative analysis between COVID-19 and non-COVID-19 patients in the emergency department. This study aims to elucidate the unique prognostic implications of lactate dynamics in these distinct patient groups, thereby enhancing the management of septic shock.

METHODS

An observational prospective study was conducted, enrolling 114 septic shock patients from the Emergency County Hospital Resita, Romania, categorizing them into COVID-19 and non-COVID-19 groups to examine their initial lactate levels, clearance rates, and their correlation with patient outcomes.

RESULTS

This study identified significant differences in the initial lactate levels and clearance rates between the two groups, indicating higher initial lactate levels and slower clearance rates in COVID-19 patients. Survivors demonstrated significantly lower initial lactate levels (1.5 ± 0.4 mmol/L) and higher lactate clearance rates (33 ± 15%) compared to non-survivors (2.5 ± 0.5 mmol/L and 24 ± 9%, respectively; lactate levels p = 0.001, clearance rates p = 0.002).

CONCLUSIONS

Lactate monitoring, particularly clearance rates, is crucial in the prognostic assessment of septic shock patients. These findings highlight the need for targeted interventions in COVID-19 patients to improve outcomes, underscoring lactate dynamics as a vital component of septic shock management in differing patient populations.

Interleukin-6 as a critical inflammatory marker for early diagnosis of surgical site infection after spine surgery

PURPOSE

Early diagnosis of surgical site infections (SSIs) could prevent surgical revision. Inflammatory markers (IMs), such as procalcitonin (PCT), interleukin-6 (IL-6), and tumor necrosis factor α (TNF-α), seem more accurate in diagnosing SSI than C-reactive protein (CRP) and white blood cell (WBC) count. The aim was to compare the predictive values of CRP, WBC count, PCT, IL-6, and TNF-α in SSI detection.

METHODS

A total of 130 patients undergoing dorsal spondylodesis from 2019 to 2024 were enrolled in a prospective diagnostic study at a maximum care spine center. IMs were measured preoperatively and on the postoperative days (PODs) 1, 2, 3, 5, and 7. Patients with high suspicion of SSI underwent revision surgery. SSI was diagnosed when the microbiological evidence was positive. Patients were divided a posteriori into the non-infection and infection groups.

RESULTS

IMs of 118 patients (66.9 ± 13.0 years, 61.0% females) were measured. Fifteen of the 118 patients (12.7%) developed an SSI. The groups differed with respect to existing hypertension, number of instrumented segments, region of surgery, CRPPOD1,7, PCTPOD7, and IL-6POD3,5,7. Binary logistic regression for SSI detection including these parameters showed an area under the curve (AUC) of 0.88 (95% CI 0.79-0.98; P < 0.001). The main effect for SSI detection was maintained by IL-6POD7 (odds ratio = 1.13; 95% CI 1.05-1.23; P = 0.001), which itself showed an AUC of 0.86 (95% CI 0.75-0.97).

CONCLUSION

Compared to CRP, WBC count, PCT, and TNF-α, IL-6 seems to be the critical IM for the early detection of an SSI.

TRIAL REGISTRATION

drks.de: DRKS00033773, date of registration: 29.02.2024, retrospectively registered; Postoperative Markers of Inflammation in Spine Surgery (POMIS) Trial.

Unveiling the role of PD-L1 in vascular endothelial dysfunction: Insights into the mtros/NLRP3/caspase-1 mediated pyroptotic pathway

BACKGROUND

Programmed death ligand-1(PD-L1) has been postulated to play a crucial role in the regulation of barrier functions of the vascular endothelium, yet how this novel molecule mediates dysfunction in endothelial cells (ECs) during acute lung injury (ALI) remains largely unknown.

METHODS

PD-L1 siRNA and plasmids were synthesized and applied respectively to down- or up-regulate PD-L1 expression in human lung microvascular endothelial cells (HMVECs). RNA sequencing was used to explore the differentially expressed genes following PD-L1 overexpression. The expression levels of tight junction proteins (ZO-1 and occludin) and the signaling pathways of NLRP-3/caspase-1/pyroptosis were analyzed. A mouse model of indirect ALI was established through hemorrhagic shock (HEM) followed by cecal ligation and puncture (CLP), enabling further investigation into the effects of intravenous delivery of PD-L1 siRNA.

RESULTS

A total of 1502 differentially expressed genes were identified, comprising 532 down-regulated and 970 up-regulated genes in ECs exhibiting PD-L1overexpression. Enrichment of PD-L1-correlated genes were observed in the NOD-like receptor signaling pathway and the TNF signaling pathway. Western blot assays confirmed that PD-L1 overexpression elevated the expression of NLRP3, cleaved-caspase-1, ASC and GSDMD, and concurrently diminished the expression of ZO-1 and occludin. This overexpression also enhanced mitochondrial oxidative phosphorylation and mitochondrial reactive oxygen species (mtROS) production. Interestingly, mitigating mitochondrial dysfunction with mitoQ partially countered the adverse effects of PD-L1 on the functionality of ECs. Furthermore, intravenous administration of PD-L1 siRNA effectively inhibited the activation of the NLRP3 inflammasome and pyroptosis in pulmonary ECs, subsequently ameliorating lung injury in HEM/CLP mice.

CONCLUSION

PD-L1-mediated activation of the inflammasome contributes significantly to the disruption of tight junction and induction of pyroptosis in ECs, where oxidative stress associated with mitochondrial dysfunction serves as a pivotal mechanism underpinning these effects.

Alterations in the immune landscape characterized by inflammatory activation and immune escape within 12 h after trauma

BACKGROUND

Trauma is statistically a significant cause of mortality among patients across countries. Nevertheless, the precise correlation between genetic diagnostic markers and the intricate mechanism of trauma remains indistinct.

METHODS

Our study exclusively centered on trauma patients and selected three trauma-related datasets from the Gene Expression Omnibus (GEO) database, all of which had blood samples collected within post-traumatic 12 h. Differential gene screening, the WGCNA and Cytoscape software were employed to analyze the two datasets, with a particular emphasis on the top 100 genes selected based on MCC algorithm scores. A logistic diagnostic model was constructed by analyzing the intersection genes in the third dataset, leading to the identification of diagnostic biomarkers with high efficiency. The global immune landscape of these patients was extensively investigated using a multidimensional approach. Meanwhile, the underlying pathological and physiological mechanisms associated with early trauma status are summarized by integrating existing literature.

RESULTS

Out of these two GEO datasets, 21 overlapping genes were identified and incorporated into in the logistic diagnostic model constructed in the GSE36809 dataset. A panel of 9 genes was uncovered as a diagnostic biomarker, and their expression and correlation were subsequently verified. Additionally, by virtue of various algorithms, the findings revealed an upregulation of neutrophil expression and a downregulation of CD8+ T cell expression, indicating characteristic early trauma-induced inflammation activation and immune suppression. The correlation observed between the feature genes and immune cells serves to validate the exceptional diagnostic capability of these 9 genes in identifying trauma status and their promising potential for patients who could benefit from targeted immune interventions. Drawing from these findings, the discussion section offers insights into the underlying pathological and physiological mechanisms at play.

CONCLUSION

Our research has discovered a novel diagnostic biomarker and unveiled its association with post-traumatic immune alterations. This breakthrough enables accurate and timely diagnosis of early trauma, facilitating the implementation of appropriate healthcare interventions.

Thrombopoietin levels in sepsis and septic shock - a systematic review and meta-analysis

OBJECTIVES

Sepsis is a life-threatening condition implicating an inadequate activation of the immune system. Platelets act as modulators and contributors to immune processes. Indeed, altered platelet turnover, thrombotic events, and changes in thrombopoietin levels in systemic inflammation have been reported, but thrombopoietin-levels in sepsis and septic-shock have not yet been systematically evaluated. We therefore performed a meta-analysis of thrombopoietin (TPO)-levels in patients with sepsis.

METHODS

Two independent reviewers screened records and full-text articles for inclusion. Scientific databases were searched for studies examining thrombopoietin levels in adult sepsis and septic-shock patients until August 1st 2022.

RESULTS

Of 95 items screened, six studies met the inclusion criteria, including 598 subjects. Both sepsis and severe sepsis were associated with increased levels of thrombopoietin (sepsis vs. control: standardized mean difference 3.06, 95 % CI 1.35-4.77; Z=3.50, p=0.0005) (sepsis vs. severe sepsis: standardized mean difference -1.67, 95 % CI -2.46 to -0.88; Z=4.14, p<0.0001). TPO-levels did not show significant differences between severe sepsis and septic shock patients but differed between sepsis and inflammation-associated non-septic controls. Overall, high heterogeneity and low sample size could be noted.

CONCLUSIONS

Concluding, increased levels of thrombopoietin appear to be present both in sepsis and severe sepsis with high heterogeneity but thrombopoietin does not allow to differentiate between severe sepsis and septic-shock. TPO may potentially serve to differentiate sepsis from non-septic trauma and/or tissue damage related (systemic) inflammation. Usage of different assays and high heterogeneity demand standardization of methods and further large multicenter trials.

Cell-Free Nuclear and Mitochondrial DNA as Potential Biomarkers for Assessing Sepsis Severity

Sepsis continues to be a significant public health challenge despite advances in understanding its pathophysiology and management strategies. Therefore, this study evaluated the value of cell-free nuclear DNA (cf-nDNA) and cell-free mitochondrial DNA (cf-mtDNA) for assessing the severity and prognosis of sepsis. Ninety-four patients were divided into three groups: infection (n = 32), sepsis (n = 30), and septic shock (n = 32). Plasma samples were collected at the time of diagnosis, and cfDNA concentrations were determined by qPCR assay. The results showed that plasma cfDNA levels increased with the severity of the disease. To distinguish between patients with infection and those with sepsis, the biomarker L1PA290 achieved the highest AUC of 0.817 (95% CI: 0.725-0.909), demonstrating a sensitivity of 77.0% and a specificity of 79.3%. When cf-nDNA was combined with the SOFA score, there was a significant improvement in the AUC (0.916 (0.853-0.979)), sensitivity (88.1%), and specificity (80.0%). Moreover, patients admitted to the ICU after being diagnosed with sepsis had significantly higher cf-nDNA concentrations. In patients admitted to the ICU, combining cf-nDNA with the SOFA score yielded an AUC of 0.753 (0.622-0.857), with a sensitivity of 95.2% and a specificity of 50.0%. cfDNA can differentiate between patients with infection and those with sepsis. It can also identify patients who are likely to be admitted to the ICU by predicting those with indications for intensive care, suggesting its potential as a biomarker for sepsis.

Meta-analysis of evaluating neuron specific enolase as a serum biomarker for sepsis-associated encephalopathy

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 Meta-analysis aimed 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

The study protocol was registered in the PROSPERO database (CRD42023398736) and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We conducted a systematic review and Meta-analysis to evaluate the serum NSE's diagnostic accuracy for SAE and prognostic strength for probability of death of septic patients. We systematic searched electronic bibliographic databases from PubMed, MEDLINE, Web of Science, Embase, Cochrane databases, CNKI, CQVIP, and WFSD. QUADAS-2 assessment tool was used to evaluate quality and risk of bias of the selected studies. Subgroup analyses, funnel plots, sensitivity analyses were also carried out. Review Manager version 5.4 and Stata16.0. was used for statistical analysis.

RESULTS

This Meta-analysis included 22 studies with 1361 serum samples from SAE patients and 1580 serum samples from no-encephalopathy septic (NE) patients. The Meta-analysis showed that individuals with SAE had higher serum NSE level than NE controls (SMD 1.93 (95 % CI 1.51-2.35), P < 0.00001). In addition, there are 948 serum samples from survival septic patients and 446 serum samples from non-survival septic patients, septic patients with survival outcomes had lower serum NSE levels than those with death outcomes (SMD -1.87 (95 % CI -2.43 to -1.32), P < 0.00001).

CONCLUSION

Our Meta-analysis reveals a significant association between elevated NSE concentrations and the increased likelihood of concomitant SAE and mortality during septic patients. This comprehensive analysis will equip ICU physicians with up-to-date insights to accurately identify patients at risk of SAE and implement appropriate intervention strategies to mitigate morbidity and improve neurological outcomes. However, it is important to note that the presence of substantial heterogeneity among studies poses challenges in determining the most effective discrimination cutoff values and optimal sampling collection time.

Strong ion gap and anion gap corrected for albumin and lactate in patients with sepsis in the intensive care unit

INTRODUCTION

Metabolic acidosis is very common amongst critically ill sepsis patients partly due to the presence of unmeasured ions in serum. These ions can be detected by anion gap (AG) or strong ion gap (SIG) concentration values. The purpose of this study is to assess the correlation and potential agreement of the two methods in critically ill patients with sepsis.

MATERIALS AND METHODS

The present is a retrospective study including septic patients admitted to the Intensive Care Unit from December 2014 to July 2016. The [SIG] and the [AG] corrected for albumin and lactate ([AGcl]) were calculated on admission and on sepsis remission or deterioration. The correlation of the two parameters was assessed in all patient groups using the Pearson correlation coefficient and linear regression analysis and the agreement with Bland-Altman plots. ROC survival curves were also generated for the patients in relation to the values of [AGcl], [SIG] and inorganic [SIG] ([SIGi]) on admission.

RESULTS

There was a strong correlation linking [AGcl] and [SIG] values (r>0.9, P<0.05) in all patient groups. The results from all three linear regression equations were statistically significant as the models predicted the [AGcl] value from the [SIG] value with high accuracy. The mean difference of the two methods (i.e. [AGcl] - [SIG] in every patient separately) in septic patients on admission was 11.75 mEq/l with 95% limits of agreement [9.7-13.8]; in patients with sepsis deterioration, it was 11.8 mEq/l with 95% limits of agreement [9.8-13.7] and in patients with sepsis remission, it was 11.5 mEq/l with 95% limits of agreement [10.4-12.7]. ROC survival curves demonstrated a small area under the curve (AUC): [SIG] AUC: 0.479, 95% CI [0.351, 0.606], [SIGi] AUC: 0.581, 95% CI [0.457, 0.705], [AGcl] AUC: 0.529, 95% CI [0.401, 0.656].

CONCLUSION

[AGcl] and [SIG] demonstrate excellent correlation in septic patients, with a mean difference of about 12 mEq/l. Both parameters failed to demonstrate any predictive ability regarding patient mortality.

SIMPLIFIED IMMUNE-DYSREGULATION INDEX: A NOVEL MARKER PREDICTS 28-DAY MORTALITY OF INTENSIVE CARE PATIENTS WITH SEPSIS

ABSTRACT

Background: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. There is currently no simple immune-imbalance-driven indicator for patients with sepsis. Methods: This study was conducted in Peking Union Medical College Hospital. Patients with sepsis were identified according to Sepsis 3.0 after reviewing patient data from May 2018 through October 2022. Least absolute shrinkage and selection operator logistic regression was used for features selection. Receiver operating characteristic curves for 28-day mortality were used to compare the predictive performance of level of interleukin 6 (IL-6) and lymphocyte count (LY#) with that of the combined ratio, namely, the IL-6/LY# ratio. A Cox hazard model was also used to test the predictive performance of IL-6/LY# versus several other measurements. The dynamic trend of IL-6/LY# based on day 1 IL-6/LY# level was analyzed. Results: The mortality rate was 24.5% (220/898) in the study cohort. The LY#, IL-6 level, blood platelet count, Sequential Organ Failure Assessment score, Acute Physiology and Chronic Health Evaluation II score, heart rate, age and Fi o2 level were identified as key factors for predicting 28-day mortality. IL-6/LY# was identified as a core indicator according to Least absolute shrinkage and selection operator logistic regression analysis. IL-6/LY# was significantly higher in nonsurvivors than in survivors (348 [154.6-1371.7] vs. 42.3 [15.4-117.1]). IL-6/LY# yielded a higher area under the curve (0.852 [95% CI = 0.820-0.879]) than the level of IL-6 (0.776 [95% CI = 0.738-0.809]) and LY# (0.719 [95% CI = 0.677-0.755]) separately. Survival analysis of mortality risk versus the IL-6/LY# ratio suggested that IL-6/LY# was significantly more predictive of patient risk than the Sequential Organ Failure Assessment score or the other factors ( P = 1.5 × 10 -33 ). In trend analysis, as the trend of D1-D3-D7 IL-6/LY# decreases, the morality rate is lower than increase or fluctuate group (42.1% vs. 58.3%, 37.9% vs. 43.8%, 37.5% vs. 38.5% in high, moderate, and low D1 IL-6/LY# group separately). Conclusion: IL-6/LY# examined on first day in intensive care unit can be used as an immune-imbalance alert to identify sepsis patients with higher risk of 28-day mortality. Decreasing trend of IL-6/LY# suggests a lower 28-day mortality rate of sepsis patients.

Protracted fibrinolysis resistance following cardiac surgery with cardiopulmonary bypass: A prospective observational study of clinical associations and patient outcomes

BACKGROUND

Surgery on cardiopulmonary bypass (CPB) elicits a pleiomorphic systemic host response which, when severe, requires prolonged intensive care support. Given the substantial cross-talk between inflammation, coagulation, and fibrinolysis, the aim of this hypothesis-generating observational study was to document the kinetics of fibrinolysis recovery post-CPB using ClotPro® point-of-care viscoelastometry. Tissue plasminogen activator-induced clot lysis time (TPA LT, s) was correlated with surgical risk, disease severity, organ dysfunction and intensive care length of stay (ICU LOS).

RESULTS

In 52 patients following CPB, TPA LT measured on the first post-operative day (D1) correlated with surgical risk (EuroScore II, Spearman's rho .39, p < .01), time on CPB (rho = .35, p = .04), disease severity (APACHE II, rho = .52, p < .001) and organ dysfunction (SOFA, rho = .51, p < .001) scores, duration of invasive ventilation (rho = .46, p < .01), and renal function (eGFR, rho = -.65, p < .001). In a generalized linear regression model containing TPA LT, CPB run time and markers of organ function, only TPA LT was independently associated with the ICU LOS (odds ratio 1.03 [95% CI 1.01-1.05], p = .01). In a latent variables analysis, the association between TPA LT and the ICU LOS was not mediated by renal function and thus, by inference, variation in the clearance of intraoperative tranexamic acid.

CONCLUSIONS

This observational hypothesis-generating study in patients undergoing cardiac surgery with cardiopulmonary bypass demonstrated an association between the severity of fibrinolysis resistance, measured on the first post-operative day, and the need for extended postoperative ICU level support. Further examination of the role of persistent fibrinolysis resistance on the clinical outcomes in this patient cohort is warranted through large-scale, well-designed clinical studies.

Serum monocyte chemotactic protein 1 and soluble mannose receptor aid predictive diagnosis of pediatric sepsis

BACKGROUND

To investigate the value of serum monocyte chemotactic protein 1 (MCP-1) and soluble mannose receptor (sMR) for predictive diagnosis of pediatric sepsis.

METHODS

This study retrospectively analyzed the data of 82 children with acute and severe signs of inflammation. According to the diagnostic criteria of sepsis, these children were divided into a sepsis group (40 cases) and a non-sepsis group (42 cases). In addition, 50 children who received health examinations during the same time period in Cangzhou Central Hospital were selected as a control group. According to the prognosis of the children in the sepsis group, they were further divided into a survival group (33 cases) and a death group (7 cases). The levels of blood indicators, inflammatory markers, liver and kidney function indicators, MCP-1 level, and sMR were collected from the children. The efficacy of using sMR and MCP-1 levels in the predictive diagnosis of sepsis was analyzed by using the area under the ROC curve (AUC).

RESULTS

Serum levels of MCP-1 and sMR were (452.32±2.79) μg/ml and (97.23±.15) μg/ml, respectively, in the sepsis group, significantly higher than those in all controls (P<0.001). In the death group, the levels of white blood cells (WBC), C-reactive protein (CRP), procalcitonin (PCT), sMR, and MCP-1 were significantly higher compared to the survival group (P<0.05). The AUC for CRP in predictive diagnosis of sepsis was 0.9075; the AUC for PCT was 0.8759; the AUC for sMR was 0.9244; and the AUC for MCP-1 was 0.9406.

CONCLUSIONS

Serum sMR and MCP-1 levels can help predict the diagnosis of pediatric sepsis.

Integrated Bioinformatics Exploration and Preliminary Clinical Verification for the Identification of Crucial Biomarkers in Severe Cases of COVID-19

Background

Coronavirus disease 2019 (COVID-19) is a respiratory infectious illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The objective of this study is to identify reliable and accurate biomarkers for the early stratification of disease severity, a crucial aspect that is currently lacking for the impending phases of the next COVID-19 pandemic.

Methods

In this study, we identified important module and hub genes related to clinical severe COVID-19 using differentially expressed genes (DEGs) screening combing weighted gene co-expression network analysis (WGCNA) in dataset GSE213313. We further screened and confirmed these hub genes in another two new independent datasets (GSE172114 and GSE157103). In order to evaluate these key genes' stability and robustness for diagnosing or predicting the progression of illness, we used RT-PCR validation of selected genes in blood samples obtained from hospitalized COVID-19 patients.

Results

A total of 968 and 52 DEGs were identified between COVID-19 patients and normal people, critical and non-critical patients, respectively. Then, using WGCNA, 10 modules were constructed. Among them, the blue module positively associated with clinic disease severity of COVID-19. From overlapped section between DEGs and blue module, 12 intersected common differential genes were obtained. Subsequently, these hub genes were validated in another two new independent datasets as well and 9 genes that overlapped showed a highly correlation with disease severity. Finally, the mRNA expression levels of these hub genes were tested in blood samples from COVID-19 patients. In severe cases, there was increased expression of MCEMP1, ANXA3, CD177, and SCN9A. In particular, MCEMP1 increased with disease severity, which suggested an unfavorable development and a frustrating prognosis.

Conclusion

Using comprehensive bioinformatical analysis and the validation of clinical samples, we identified four major candidate genes, MCEMP1, ANXA3, CD177, and SCN9A, which are essential for diagnosis or development of COVID-19.

SPINK1 is a Potential Diagnostic and Prognostic Biomarker for Sepsis

Purpose

There are no satisfactory diagnostic biomarkers for sepsis. Accordingly, this study screened biomarkers valuable for sepsis diagnosis and prognosis using data-independent acquisition (DIA) combined with clinical data analysis.

Patients and Methods

Serine protease inhibitor Kazal-type 1 (SPINK1) is a differentially expressed protein that was screened using DIA and bioinformatics in sepsis patients (n = 22) and healthy controls (n = 10). The plasma SPINK1 levels were detected using an enzyme-linked immunosorbent assay (ELISA) in an expanded population (sepsis patients, n = 52; healthy controls, n = 10). The diagnostic value of SPINK1 in sepsis was evaluated using receiver operating characteristic (ROC) curve analysis based on clinical data. The prognostic value of SPINK1 for sepsis was evaluated using correlation and survival analyses.

Results

DIA quality control identified 78 differential proteins (72 upregulated and six downregulated), among which SPINK1 was highly expressed in sepsis. The ELISA results suggested that SPINK1 expression was significantly elevated in the sepsis group (P < 0.05). ROC analysis of SPINK1 yielded an area under the curve (AUC) of 0.9096. Combining SPINK1 with procalcitonin (PCT) for ROC analysis yielded an AUC of 1. SPINK1 expression was positively correlated with the Sequential Organ Failure Assessment (SOFA) score (r = 3497, P = 0.0053) and APACHE II score (r = 3223, P = 0.0106). High plasma SPINK1 protein expression was negatively correlated with the 28-day survival rate of patients with sepsis (P = 0.0149).

Conclusion

The plasma of sepsis patients contained increased SPINK1 protein expression. Combining SPINK1 with PCT might have a high diagnostic value for sepsis. SPINK1 was associated with the SOFA score, APACHE II score, and the 28-day survival rate in patients with sepsis.

Prognostic Value of Macrophage Inflammatory Protein-3alpha (MIP3-Alpha) and Severity Scores in Elderly Patients with Sepsis

Objective

This study examines the effectiveness of MIP-3alpha and severity scores in determining the prognosis of elderly sepsis patients.

Methods

From October 2020 to April 2021, a total of 171 elderly sepsis patients were admitted to the Emergency Department of the Shijingshan Branch of Beijing Chaoyang Hospital, Capital Medical University. According to the 28-day mortality rate, they were divided into two groups: survivors (48 cases) and deaths (123 cases). At admission, severity scores which are the Sequential Organ Failure Assessment (SOFA) and the Acute Physiology and Chronic Health Evaluation II (APACHE II) were calculated. The logistic regression was used to analyze the independent risk factors associated with 28-day mortality in elderly sepsis patients. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the value of MIP-3alpha, SOFA, and APACHE II in the evaluation of 28-day mortality in elderly sepsis patients.

Results

MIP-3alpha, SOFA and APACHE II of the death group were significantly higher than those of the survival group (P < 0.05). Multivariate logistic regression analysis showed that MIP-3alpha, SOFA, APACHE II, and systolic blood pressure (SBP) were independent risk factors for 28-day mortality of senile sepsis (P < 0.05). Analysis of the ROC curve revealed that MIP-3alpha, SOFA, APACHE II had predictive value for the 28-day prognosis of senile sepsis (all P < 0.01). Combing with MIP-3alpha and SOFA showed better predictive ability (Z1 = 3.733, Z2 = 2.996, both P < 0.01), compared to detecting MIP-3alpha and SOFA alone.

Conclusion

In senile sepsis, MIP-3alpha, SOFA, APACHE II and SBP are independent risk factors for 28-day mortality. The combination of MIP-3alpha and SOFA can further enhance the predictive value of 28-day mortality in patients with senile sepsis and provide some reference value for the evaluation and treatment of senile sepsis.

Distinct functional neutrophil phenotypes in sepsis patients correlate with disease severity

Purpose

Sepsis is a clinical syndrome defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis is a highly heterogeneous syndrome with distinct phenotypes that impact immune function and response to infection. To develop targeted therapeutics, immunophenotyping is needed to identify distinct functional phenotypes of immune cells. In this study, we utilized our Organ-on-Chip assay to categorize sepsis patients into distinct phenotypes using patient data, neutrophil functional analysis, and proteomics.

Methods

Following informed consent, neutrophils and plasma were isolated from sepsis patients in the Temple University Hospital ICU (n=45) and healthy control donors (n=7). Human lung microvascular endothelial cells (HLMVEC) were cultured in the Organ-on-Chip and treated with buffer or cytomix ((TNF/IL-1β/IFNγ). Neutrophil adhesion and migration across HLMVEC in the Organ-on-Chip were used to categorize functional neutrophil phenotypes. Quantitative label-free global proteomics was performed on neutrophils to identify differentially expressed proteins. Plasma levels of sepsis biomarkers and neutrophil extracellular traps (NETs) were determined by ELISA.

Results

We identified three functional phenotypes in critically ill ICU sepsis patients based on ex vivo neutrophil adhesion and migration patterns. The phenotypes were classified as: Hyperimmune characterized by enhanced neutrophil adhesion and migration, Hypoimmune that was unresponsive to stimulation, and Hybrid with increased adhesion but blunted migration. These functional phenotypes were associated with distinct proteomic signatures and differentiated sepsis patients by important clinical parameters related to disease severity. The Hyperimmune group demonstrated higher oxygen requirements, increased mechanical ventilation, and longer ICU length of stay compared to the Hypoimmune and Hybrid groups. Patients with the Hyperimmune neutrophil phenotype had significantly increased circulating neutrophils and elevated plasma levels NETs.

Conclusion

Neutrophils and NETs play a critical role in vascular barrier dysfunction in sepsis and elevated NETs may be a key biomarker identifying the Hyperimmune group. Our results establish significant associations between specific neutrophil functional phenotypes and disease severity and identify important functional parameters in sepsis pathophysiology that may provide a new approach to classify sepsis patients for specific therapeutic interventions.

Pediatric sepsis inflammatory blood biomarkers that correlate with clinical variables and severity of illness scores

BACKGROUND

Sepsis is a dysregulated systemic inflammatory response triggered by infection, resulting in organ dysfunction. A major challenge in clinical pediatrics is to identify sepsis early and then quickly intervene to reduce morbidity and mortality. As blood biomarkers hold promise as early sepsis diagnostic tools, we aimed to measure a large number of blood inflammatory biomarkers from pediatric sepsis patients to determine their predictive ability, as well as their correlations with clinical variables and illness severity scores.

METHODS

Pediatric patients that met sepsis criteria were enrolled, and clinical data and blood samples were collected. Fifty-eight inflammatory plasma biomarker concentrations were determined using immunoassays. The data were analyzed with both conventional statistics and machine learning.

RESULTS

Twenty sepsis patients were enrolled (median age 13 years), with infectious pathogens identified in 75%. Vasopressors were administered to 85% of patients, while 55% received invasive ventilation and 20% were ventilated non-invasively. A total of 24 inflammatory biomarkers were significantly different between sepsis patients and age/sex-matched healthy controls. Nine biomarkers (IL-6, IL-8, MCP-1, M-CSF, IL-1RA, hyaluronan, HSP70, MMP3, and MMP10) yielded AUC parameters > 0.9 (95% CIs: 0.837-1.000; p < 0.001). Boruta feature reduction yielded 6 critical biomarkers with their relative importance: IL-8 (12.2%), MCP-1 (11.6%), HSP70 (11.6%), hyaluronan (11.5%), M-CSF (11.5%), and IL-6 (11.5%); combinations of 2 biomarkers yielded AUC values of 1.00 (95% CI: 1.00-1.00; p < 0.001). Specific biomarkers strongly correlated with illness severity scoring, as well as other clinical variables. IL-3 specifically distinguished bacterial versus viral infection (p < 0.005).

CONCLUSIONS

Specific inflammatory biomarkers were identified as markers of pediatric sepsis and strongly correlated to both clinical variables and sepsis severity.

The early predictive roles of NLR and NE% in in-hospital mortality of septic patients

Background

This study aimed to retrospectively investigate the early predictive value of inflammation-related parameters in-hospital mortality of septic patients.

Methods

We retrospectively recruited 606 patients from Wuhan Union Hospital from January 2009 to October 2022. The inflammation-related parameters including neutrophil-to-lymphocyte ratio (NLR), neutrophil percentage (NE%), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) in survivals and non-survivals on day 1, 2, 3 and 7 after hospitalization were collected and analyzed.

Results

NLR and NE% in non-survivals (n = 185) were significantly higher than those in survivals (n = 421). The area under the receiver operating characteristic curve (AUC) of NLR or NE% was 0.880 or 0.852 on day 1, 0.770 or 0.790 on day 2, 0.784 or 0.777 on day 3, and 0.732 or 0.741 on day 7. The optimal cut-off values of NLR or NE% for predicting in-hospital mortality were 10.769 or 87.70% on day 1, 17.544 or 90.69% on day 2, 14.395 or 85.00% on day 3, and 9.105 or 83.93% on day 7. The day 1, 2 and 3 NLR and NE% were significant predictors of in-hospital mortality in the Cox proportional hazards models.

Conclusions

NLR ≥10.769 and NE% ≥ 87.70% could be used early biomarkers for predicting in-hospital mortality of septic patients.

Machine Learning Interpretability Methods to Characterize the Importance of Hematologic Biomarkers in Prognosticating Patients with Suspected Infection

Early detection of sepsis in patients admitted to the emergency department (ED) is an important clinical objective as early identification and treatment can help reduce morbidity and mortality rate of 20% or higher. Hematologic changes during sepsis-associated organ dysfunction are well established and a new biomarker called Monocyte Distribution Width (MDW) has been recently approved by the US Food and Drug Administration for sepsis. However, MDW, which quantifies monocyte activation in sepsis patients, is not a routinely reported parameter and it requires specialized proprietary laboratory equipment. Further, the relative importance of MDW as compared to other routinely available hematologic parameters and vital signs has not been studied, which makes it difficult for resource constrained hospital systems to make informed decisions in this regard. To address this issue, we analyzed data from a cohort of ED patients (n=10,229) admitted to a large regional safety-net hospital in Cleveland, Ohio with suspected infection who later developed poor outcomes associated with sepsis. We developed a new analytical framework consisting of seven data models and an ensemble of high accuracy machine learning (ML) algorithms (accuracy values ranging from 0.83 to 0.90) for the prediction of outcomes more common in sepsis than uncomplicated infection (3-day intensive care unit stay or death). To characterize the contributions of individual hematologic parameters, we applied the Local Interpretable Model-Agnostic Explanation (LIME) and Shapley Additive Value (SHAP) interpretability methods to the high accuracy ML algorithms. The ML interpretability results were consistent in their findings that the value of MDW is grossly attenuated in the presence of other routinely reported hematologic parameters and vital signs data. Further, this study for the first time shows that complete blood count with differential (CBC-DIFF) together with vital signs data can be used as a substitute for MDW in high accuracy ML algorithms to screen for poor outcomes associated with sepsis.

Myeloid-Derived Suppressor-like Cells as a Prognostic Marker in Critically Ill Patients: Insights from Experimental Endotoxemia and Intensive Care Patients

Patients admitted to the intensive care unit (ICU) often experience endotoxemia, nosocomial infections and sepsis. Polymorphonuclear and monocytic myeloid-derived suppressor cells (PMN-MDSCs and M-MDSCs) can have an important impact on the development of infectious diseases, but little is known about their potential predictive value in critically ill patients. Here, we used unsupervised flow cytometry analyses to quantify MDSC-like cells in healthy subjects challenged with endotoxin and in critically ill patients admitted to intensive care units and at risk of developing infections. Cells phenotypically similar to PMN-MDSCs and M-MDSCs increased after endotoxin challenge. Similar cells were elevated in patients at ICU admission and normalized at ICU discharge. A subpopulation of M-MDSC-like cells expressing intermediate levels of CD15 (CD15int M-MDSCs) was associated with overall mortality (p = 0.02). Interestingly, the high abundance of PMN-MDSCs and CD15int M-MDSCs was a good predictor of mortality (p = 0.0046 and 0.014), with area under the ROC curve for mortality of 0.70 (95% CI = 0.4-1.0) and 0.86 (0.62-1.0), respectively. Overall, our observations support the idea that MDSCs represent biomarkers for sepsis and that flow cytometry monitoring of MDSCs may be used to risk-stratify ICU patients for targeted therapy.

Comparison of plasma inflammatory biomarkers between MIS-C and potentially serious infections in pediatric patients

BACKGROUND

Inflammatory biomarkers have been used for the diagnosis and management of multisystemic inflammatory syndrome in children (MIS-C). We aimed to compare the clinical and laboratory findings of MIS-C cases versus other febrile cases cataloged as potentially suspected bacterial infection (non-MIS-C).

METHODS

Unicentric ambispective observational cohort study (June 2020-February 2022). We analyzed demographics, clinical symptoms and laboratory findings in MIS-C cases and in non-MIS-C cases with febrile processes of patients under 15 years of age admitted to hospital.

RESULTS

We enrolled 54 patients with potential suspected bacterial infection and 20 patients with MIS-C for analysis. Fever (100%), gastrointestinal (80%) and mucocutaneous findings (35%) were common in MIS-C patients, also hypotension (36.8%) and tachycardia (55%). Laboratory findings showed significantly elevated proBNP (70%), ferritin (35%), D-dimer (80%) and lymphopenia (55%) and thrombocytopenia (27.8%) in MIS-C cases. IL-6 values were high in non-MIS-C patients (92.6%).

CONCLUSIONS

In the management of MIS-C patients, the dynamic monitoring of proBNP, ferritin, D-dimer, lymphocytes and platelets could be helpful to pediatricians to effectively evaluate the progress of MIS-C in the early phases, not IL-6 values. The applicability of the IL-6 level as a prognostic biomarker in MIS-C patients may require closer discussion. In addition, the optimal laboratory markers, as stated in our study, can help establish a biomarkers model to early distinguish the MIS-C versus non-MIS-C in patients who are admitted to febrile syndrome.

The 'analysis of gene expression and biomarkers for point-of-care decision support in Sepsis' study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS discrimination

Introduction

Early diagnosis of sepsis and discrimination from SIRS is crucial for clinicians to provide appropriate care, management and treatment to critically ill patients. We describe identification of mRNA biomarkers from peripheral blood leukocytes, able to identify severe, systemic inflammation (irrespective of origin) and differentiate Sepsis from SIRS, in adult patients within a multi-center clinical study.

Methods

Participants were recruited in Intensive Care Units (ICUs) from multiple UK hospitals, including fifty-nine patients with abdominal sepsis, eighty-four patients with pulmonary sepsis, forty-two SIRS patients with Out-of-Hospital Cardiac Arrest (OOHCA), sampled at four time points, in addition to thirty healthy control donors. Multiple clinical parameters were measured, including SOFA score, with many differences observed between SIRS and sepsis groups. Differential gene expression analyses were performed using microarray hybridization and data analyzed using a combination of parametric and non-parametric statistical tools.

Results

Nineteen high-performance, differentially expressed mRNA biomarkers were identified between control and combined SIRS/Sepsis groups (FC>20.0, p<0.05), termed 'indicators of inflammation' (I°I), including CD177, FAM20A and OLAH. Best-performing minimal signatures e.g. FAM20A/OLAH showed good accuracy for determination of severe, systemic inflammation (AUC>0.99). Twenty entities, termed 'SIRS or Sepsis' (S°S) biomarkers, were differentially expressed between sepsis and SIRS (FC>2·0, p-value<0.05).

Discussion

The best performing signature for discriminating sepsis from SIRS was CMTM5/CETP/PLA2G7/MIA/MPP3 (AUC=0.9758). The I°I and S°S signatures performed variably in other independent gene expression datasets, this may be due to technical variation in the study/assay platform.

Development of macrophage-associated genes prognostic signature predicts clinical outcome and immune infiltration for sepsis

Sepsis is a major global health problem, causing a significant burden of disease and death worldwide. Risk stratification of sepsis patients, identification of severe patients and timely initiation of treatment can effectively improve the prognosis of sepsis patients. We procured gene expression datasets for sepsis (GSE54514, GSE65682, GSE95233) from the Gene Expression Omnibus and performed normalization to mitigate batch effects. Subsequently, we applied weighted gene co-expression network analysis to categorize genes into modules that exhibit correlation with macrophage activity. To pinpoint macrophage-associated genes (MAAGs), we executed differential expression analysis and single sample gene set enrichment analysis. We then established a prognostic model derived from four MAAGs that were significantly differentially expressed. Functional enrichment analysis and immune infiltration assessments were instrumental in deciphering the biological mechanisms involved. Furthermore, we employed principal component analysis and conducted survival outcome analyses to delineate molecular subgroups within sepsis. Four novel MAAGs-CD160, CX3CR1, DENND2D, and FAM43A-were validated and used to create a prognostic model. Subgroup classification revealed distinct molecular profiles and a correlation with 28-day survival outcomes. The MAAGs risk score was developed through univariate Cox, LASSO, and multivariate Cox analyses to predict patient prognosis. Validation of the risk score upheld its prognostic significance. Functional enrichment implicated ribonucleoprotein complex biogenesis, mitochondrial matrix, and transcription coregulator activity in sepsis, with an immune infiltration analysis indicating an association between MAAGs risk score and immune cell populations. The four MAAGs exhibited strong diagnostic capabilities for sepsis. The research successfully developed a MAAG-based prognostic model for sepsis, demonstrating that such genes can significantly stratify risk and reflect immune status. Although in-depth mechanistic studies are needed, these findings propose novel targets for therapy and provide a foundation for future precise clinical sepsis management.

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.

Identifying biomarkers deciphering sepsis from trauma-induced sterile inflammation and trauma-induced sepsis

Objective

The purpose of this study was to identify a panel of biomarkers for distinguishing early stage sepsis patients from non-infected trauma patients.

Background

Accurate differentiation between trauma-induced sterile inflammation and real infective sepsis poses a complex life-threatening medical challenge because of their common symptoms albeit diverging clinical implications, namely different therapies. The timely and accurate identification of sepsis in trauma patients is therefore vital to ensure prompt and tailored medical interventions (provision of adequate antimicrobial agents and if possible eradication of infective foci) that can ultimately lead to improved therapeutic management and patient outcome. The adequate withholding of antimicrobials in trauma patients without sepsis is also important in aspects of both patient and environmental perspective.

Methods

In this proof-of-concept study, we employed advanced technologies, including Matrix-Assisted Laser Desorption/Ionization (MALDI) and multiplex antibody arrays (MAA) to identify a panel of biomarkers distinguishing actual sepsis from trauma-induced sterile inflammation.

Results

By comparing patient groups (controls, infected and non-infected trauma and septic shock patients under mechanical ventilation) at different time points, we uncovered distinct protein patterns associated with early trauma-induced sterile inflammation on the one hand and sepsis on the other hand. SYT13 and IL1F10 emerged as potential early sepsis biomarkers, while reduced levels of A2M were indicative of both trauma-induced inflammation and sepsis conditions. Additionally, higher levels of TREM1 were associated at a later stage in trauma patients. Furthermore, enrichment analyses revealed differences in the inflammatory response between trauma-induced inflammation and sepsis, with proteins related to complement and coagulation cascades being elevated whereas proteins relevant to focal adhesion were diminished in sepsis.

Conclusions

Our findings, therefore, suggest that a combination of biomarkers is needed for the development of novel diagnostic approaches deciphering trauma-induced sterile inflammation from actual infective sepsis.

PAMPs and DAMPs in Sepsis: A Review of Their Molecular Features and Potential Clinical Implications

Sepsis is a serious organ dysfunction caused by a dysregulated immune host reaction to a pathogen. The innate immunity is programmed to react immediately to conserved molecules, released by the pathogens (PAMPs), and the host (DAMPs). We aimed to review the molecular mechanisms of the early phases of sepsis, focusing on PAMPs, DAMPs, and their related pathways, to identify potential biomarkers. We included studies published in English and searched on PubMed® and Cochrane®. After a detailed discussion on the actual knowledge of PAMPs/DAMPs, we analyzed their role in the different organs affected by sepsis, trying to elucidate the molecular basis of some of the most-used prognostic scores for sepsis. Furthermore, we described a chronological trend for the release of PAMPs/DAMPs that may be useful to identify different subsets of septic patients, who may benefit from targeted therapies. These findings are preliminary since these pathways seem to be strongly influenced by the peculiar characteristics of different pathogens and host features. Due to these reasons, while initial findings are promising, additional studies are necessary to clarify the potential involvement of these molecular patterns in the natural evolution of sepsis and to facilitate their transition into the clinical setting.

Comprehensive analysis of senescence-associated genes in sepsis based on bulk and single-cell sequencing data

Background: Sepsis is a pathological state resulting from dysregulated immune response in host during severe infection, leading to persistent organ dysfunction and ultimately death. Senescence-associated genes (SAGs) have manifested their potential in controlling the proliferation and dissemination of a variety of diseases. Nevertheless, the correlation between sepsis and SAGs remains obscure and requires further investigation. Methods: Two RNA expression datasets (GSE28750 and GSE57065) specifically related to sepsis were employed to filter hub SAGs, based on which a diagnostic model predictive of the incidence of sepsis was developed. The association between the expression of the SAGs identified and immune-related modules was analyzed employing Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) and Microenvironment Cell Populations-counter (MCP-counter) analysis. The identified genes in each cohort were clustered by unsupervised agreement clustering analysis and weighted gene correlation network analysis (WGCNA). Results: A diagnostic model for sepsis established based on hub genes (IGFBP7, GMFG, IL10, IL18, ETS2, HGF, CD55, and MMP9) exhibited a strong clinical reliability (AUC = 0.989). Sepsis patients were randomly assigned and classified by WGCNA into two clusters with distinct immune statuses. Analysis on the single-cell RNA sequencing (scRNA-seq) data revealed high scores of SAGs in the natural killer (NK) cells of the sepsis cohort than the healthy cohort. Conclusion: These findings suggested a close association between SAGs and sepsis alterations. The identified hub genes had potential to serve as a viable diagnostic marker for sepsis.

Immune-Related Molecules CD3G and FERMT3: Novel Biomarkers Associated with Sepsis

Sepsis ranks among the most common health problems worldwide, characterized by organ dysfunction resulting from infection. Excessive inflammatory responses, cytokine storms, and immune-induced microthrombosis are pivotal factors influencing the progression of sepsis. Our objective was to identify novel immune-related hub genes for sepsis through bioinformatic analysis, subsequently validating their specificity and potential as diagnostic and prognostic biomarkers in an animal experiment involving a sepsis mice model. Gene expression profiles of healthy controls and patients with sepsis were obtained from the Gene Expression Omnibus (GEO) and analysis of differentially expressed genes (DEGs) was conducted. Subsequently, weighted gene co-expression network analysis (WGCNA) was used to analyze genes within crucial modules. The functional annotated DEGs which related to the immune signal pathways were used for constructing protein-protein interaction (PPI) analysis. Following this, two hub genes, FERMT3 and CD3G, were identified through correlation analyses associated with sequential organ failure assessment (SOFA) scores. These two hub genes were associated with cell adhesion, migration, thrombosis, and T-cell activation. Furthermore, immune infiltration analysis was conducted to investigate the inflammation microenvironment influenced by the hub genes. The efficacy and specificity of the two hub genes were validated through a mice sepsis model study. Concurrently, we observed a significant negative correlation between the expression of CD3G and IL-1β and GRO/KC. These findings suggest that these two genes probably play important roles in the pathogenesis and progression of sepsis, presenting the potential to serve as more stable biomarkers for sepsis diagnosis and prognosis, deserving further study.

Multifunctional Carbon Dots for Biomedical Applications: Diagnosis, Therapy, and Theranostic

Designing suitable nanomaterials is an ideal strategy to enable early diagnosis and effective treatment of diseases. Carbon dots (CDs) are luminescent carbonaceous nanoparticles that have attracted considerable attention. Through facile synthesis, they process properties including tunable light emission, low toxicity, and light energy transformation, leading to diverse applications as optically functional materials in biomedical fields. Recently, their potentials have been further explored, such as enzyme-like activity and ability to promote osteogenic differentiation. Through refined synthesizing strategies carbon dots, a rich treasure trove for new discoveries, stand a chance to guide significant development in biomedical applications. In this review, the authors start with a brief introduction to CDs. By presenting mechanisms and examples, the authors focus on how they can be used in diagnosing and treating diseases, including bioimaging failure of tissues and cells, biosensing various pathogenic factors and biomarkers, tissue defect repair, anti-inflammation, antibacterial and antiviral, and novel oncology treatment. The introduction of the application of integrated diagnosis and treatment follows closely behind. Furthermore, the challenges and future directions of CDs are discussed. The authors hope this review will provide critical perspectives to inspire new discoveries on CDs and prompt their advances in biomedical applications.

An integrative model with HLA-DR, CD64, and PD-1 for the diagnostic and prognostic evaluation of sepsis

BACKGROUND

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection and progressive immunosuppression with high mortality. HLA-DR, CD64, and PD-1 were assumed to be useful biomarkers for sepsis prediction. However, the ability of a combination of these biomarkers has not been clarified.

METHODS

An observational case-control study was conducted that included 30 sepsis patients, 30 critically ill patients without sepsis admitted to the intensive care unit (ICU), and 32 healthy individuals. The levels of HLA-DR, CD64, and PD-1 expression in peripheral blood immune cells and subsets was assayed on Days 1, 3, and 5, and the clinical information of patients was collected. We compared these biomarkers between groups and evaluated the predictive validity of single and combined biomarkers on sepsis mortality.

RESULTS

The results indicate that PD-1 expression on CD4- CD8- T (PD-1+ CD4- CD8- T) (19.19% ± 10.78% vs. 9.88% ± 1.79%, p = .004) cells and neutrophil CD64 index (nCD64 index) (9.15 ± 5.46 vs. 5.33 ± 2.34, p = .001) of sepsis patients were significantly increased, and HLA-DR expression on monocytes (mHLA-DR+ ) was significantly reduced (13.26% ± 8.06% vs. 30.17% ± 21.42%, p = 2.54 × 10-4 ) compared with nonsepsis critically ill patients on the first day. Importantly, the expression of PD-1+ CD4- CD8- T (OR = 0.622, 95% CI = 0.423-0.916, p = .016) and mHLA-DR+ (OR = 1.146, 95% CI = 1.014-1.295, p = .029) were significantly associated with sepsis mortality. For sepsis diagnosis, the mHLA-DR+ , PD-1+ CD4- CD8- T, and nCD64 index showed the moderate individual performance, and combinations of the three biomarkers achieved greater diagnostic value (AUC = 0.899, 95% CI = 0.792-0.962). When adding PCT into the combined model, the AUC increased to 0.936 (95% CI = 0.840-0.983). For sepsis mortality, combinations of PD-1+ CD4- CD8- T and mHLA-DR+ , have a good ability to predict the prognosis of sepsis patients, with an AUC = 0.921 (95% CI = 0.762-0.987).

CONCLUSION

These findings indicate that the combinations of HLA-DR, CD64, and PD-1 outperformed each of the single indicator in diagnosis and predicting prognosis of sepsis.

A Simple Bacteremia Score for Predicting Bacteremia in Patients with Suspected Infection in the Emergency Department: A Cohort Study

Bacteremia is a life-threatening condition that has increased in prevalence over the past two decades. Prompt recognition of bacteremia is important; however, identification of bacteremia requires 1 to 2 days. This retrospective cohort study, conducted from 10 November 2014 to November 2019, among patients with suspected infection who visited the emergency department (ED), aimed to develop and validate a simple tool for predicting bacteremia. The study population was randomly divided into derivation and development cohorts. Predictors of bacteremia based on the literature and logistic regression were assessed. A weighted value was assigned to predictors to develop a prediction model for bacteremia using the derivation cohort; discrimination was then assessed using the area under the receiver operating characteristic curve (AUC). Among the 22,519 patients enrolled, 18,015 were assigned to the derivation group and 4504 to the validation group. Sixteen candidate variables were selected, and all sixteen were used as significant predictors of bacteremia (model 1). Among the sixteen variables, the top five with higher odds ratio, including procalcitonin, neutrophil-lymphocyte ratio (NLR), lactate level, platelet count, and body temperature, were used for the simple bacteremia score (model 2). The proportion of bacteremia increased according to the simple bacteremia score in both cohorts. The AUC for model 1 was 0.805 (95% confidence interval [CI] 0.785-0.824) and model 2 was 0.791 (95% CI 0.772-0.810). The simple bacteremia prediction score using only five variables demonstrated a comparable performance with the model including sixteen variables using all laboratory results and vital signs. This simple score is useful for predicting bacteremia-assisted clinical decisions.

A comprehensive analysis of immune features and construction of an immune gene diagnostic model for sepsis

Sepsis is a life-threatening syndrome resulting from immune system dysfunction that is caused by infection. It is of great importance to analyze the immune characteristics of sepsis, identify the key immune system related genes, and construct diagnostic models for sepsis. In this study, the sepsis transcriptome and expression profiling data were merged into an integrated dataset containing 277 sepsis samples and 117 non-sepsis control samples. Single-sample gene set enrichment analysis (ssGSEA) was used to assess the immune cell infiltration. Two sepsis immune subtypes were identified based on the 22 differential immune cells between the sepsis and the healthy control groups. Weighted gene co-expression network analysis (WCGNA) was used to identify the key module genes. Then, 36 differentially expressed immune-related genes were identified, based on which a robust diagnostic model was constructed with 11 diagnostic genes. The expression of 11 diagnostic genes was finally assessed in the training and validation datasets respectively. In this study, we provide comprehensive insight into the immune features of sepsis and establish a robust diagnostic model for sepsis. These findings may provide new strategies for the early diagnosis of sepsis in the future.

Study on identification of a three-microRNA panel in serum for diagnosing neonatal early onset sepsis

BACKGROUND

Comparing with other diseases, early onset sepsis (EOS) is a global health concern in neonatal period for its high morbidity and mortality rates. In recent years, many studies have contributed to the figure out the expression patterns of circulating micro-RNAs (miRNAs) in different diseases and progressions, which could function as diagnostic biomarkers for EOS. The purpose of this study was to analyze the expression patterns of selected miRNAs and evaluate their diagnostic value for early detection and treatment.

METHODS

This was a prospective cross-sectional study conducted from 1 July 2021 to 30 June 2022. We collected surplus peripheral blood and demographic statistics of septic neonates and non-infected neonates during the first 24 h after delivery and obtained 11 candidate miRNAs by literature screening. First, we extracted the candidate miRNAs from the serum of selected neonates and analyzed their expression levels, and then the receiver operating characteristic (ROC) curve was used to select the differentially expressed miRNAs. We analyzed their sensitivity and specificity and obtained the best diagnostic panel. Finally, with the help of differentially expressed miRNAs, we performed gene ontology (GO) enrichment and protein-protein interaction (PPI) analyses by their target genes.

RESULTS

In patients with EOS, three miRNAs (mir-223-3p, mir-15a-5p, and mir-17-5p) in serum were significantly downregulated, and mir-146a-5p, mir-1-3p, and mir-16-5p were upregulated. The diagnostic value of these miRNAs (miR-15a-5p, AUC = 0.67; miR-223-3p, AUC = 0.72; miR-16-5p, AUC = 0.68; miR-17-5p, AUC = 0.70; miR-1-3p, AUC = 0.69; miR-146a-5p, AUC = 0.72) was moderate, and the diagnostic panel constructed by miR-15a-5p, miR-223-3p, and miR-16-5p possessed a comparatively higher diagnostic value (AUC = 0.85, sensitivity: 74.6%, specificity: 86%), indicating that their combined application may be a promising biomarker for clinical diagnosis of EOS. According to GO enrichment analysis, most proteins encoded by target genes were located in the cytosol as for cellular component (CC), for molecular function (MF), most proteins acted as regulators in protein binding, and for biological process (BP). Most genes function in positive or negative regulation of transcription from RNA polymerase II promoter, and the top 10 hub genes were CDKN1A, YAP1, CCNE1, CCND1, CKK6, ERBB4, CHEK1, DICER1, VEGFA, and APP by rank degree after PPI construction.

CONCLUSIONS

The three-miRNA panels (miR-15a-5p, miR-223-3p, and miR-16-5p) may be a novel noninvasive biological marker for EOS screening.

What Is Left to Tackle in Inpatient Antimicrobial Stewardship Practice and Research

Despite widespread uptake of antimicrobial stewardship in acute care hospitals, there is ongoing need for innovation and optimization of ASPs. This article discusses current antimicrobial stewardship practice challenges and ways to improve current antimicrobial stewardship workflows. Additionally, we propose new workflows that further engage front line clinicians in optimizing their own antibiotic decision making.

Analysis of Protein Biomarkers From Hospitalized COVID-19 Patients Reveals Severity-Specific Signatures and Two Distinct Latent Profiles With Differential Responses to Corticosteroids

OBJECTIVES

To identify and validate novel COVID-19 subphenotypes with potential heterogenous treatment effects (HTEs) using electronic health record (EHR) data and 33 unique biomarkers.

DESIGN

Retrospective cohort study of adults presenting for acute care, with analysis of biomarkers from residual blood collected during routine clinical care. Latent profile analysis (LPA) of biomarker and EHR data identified subphenotypes of COVID-19 inpatients, which were validated using a separate cohort of patients. HTE for glucocorticoid use among subphenotypes was evaluated using both an adjusted logistic regression model and propensity matching analysis for in-hospital mortality.

SETTING

Emergency departments from four medical centers.

PATIENTS

Patients diagnosed with COVID-19 based on International Classification of Diseases , 10th Revision codes and laboratory test results.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Biomarker levels generally paralleled illness severity, with higher levels among more severely ill patients. LPA of 522 COVID-19 inpatients from three sites identified two profiles: profile 1 ( n = 332), with higher levels of albumin and bicarbonate, and profile 2 ( n = 190), with higher inflammatory markers. Profile 2 patients had higher median length of stay (7.4 vs 4.1 d; p < 0.001) and in-hospital mortality compared with profile 1 patients (25.8% vs 4.8%; p < 0.001). These were validated in a separate, single-site cohort ( n = 192), which demonstrated similar outcome differences. HTE was observed ( p = 0.03), with glucocorticoid treatment associated with increased mortality for profile 1 patients (odds ratio = 4.54).

CONCLUSIONS

In this multicenter study combining EHR data with research biomarker analysis of patients with COVID-19, we identified novel profiles with divergent clinical outcomes and differential treatment responses.

Impact of microbiota and host immunologic response on the efficacy of anticholinergic treatment for urgency urinary incontinence

INTRODUCTION AND HYPOTHESIS

Studies within the past decade have suggested associations among composition of the urinary microbiota, local immune responses, and urinary incontinence symptoms. To investigate these relationships, we evaluated the structure of the urinary microbiome, local inflammatory markers, and patient responses prior to and at 6-weeks after treatment with anticholinergic medication for urgency urinary incontinence (UUI).

METHODS

Using a prospective pilot study, we enrolled women who presented with UUI symptoms and were prescribed treatment with anticholinergics. Catheterized urine samples were collected from participants at their baseline and 6-week follow-up visits for microbiological (standard and 16S rRNA gene phylotyping analyses) and cytokine analysis along with the UDI-6 questionnaire and 2-day bladder diary.

RESULTS

Patients were Caucasian, post- menopausal, with a median age of 64 and median BMI of 30.1 kg/m2. Among the patients, 75% had UUI symptoms for less than 2 years, but with a frequency of at least a few times a week or every day. Most women were prescribed 10 mg oxybutynin ER daily at enrollment. Patients had varied urinary microbiota by culture and 16S phylotyping, with species of Lactobacillus being the most common, in six samples, in addition to taxa associated with Enterococcus, Staphylococcus, and mixed flora. Cytokine levels showed no differences before and after treatment with anticholinergics, nor correlation with urinary bacteria or microbiome composition.

CONCLUSIONS

Our pilot study suggests factors in addition to the urinary microbiome and local immune responses may be involved in patients' response to anticholinergics for UUI.

TRIM45 aggravates microglia pyroptosis via Atg5/NLRP3 axis in septic encephalopathy

BACKGROUND

Neuroinflammation mediated by microglial pyroptosis is an important pathogenic mechanism of septic encephalopathy (SAE). It has been reported that TRIM45 is associated with tumours and inflammatory diseases. However, the role of TRIM45 in SAE and the relationship between TRIM45 and microglial pyroptosis are unknown. In this study, we found that TRIM45 played an important role in regulating microglial pyroptosis and the molecular mechanism.

METHODS

SAE was induced by intraperitoneal injection of LPS in WT and AAV-shTRIM45 mice. BV2 cells were treated with LPS/ATP in vitro. Cognitive function was assessed by the Morris water maze. Nissl staining was used to evaluate histological and structural lesions. ELISA was used to dectect neuroinflammation. qPCR was used to detect the mRNA levels of inflammatory cytokines, NLRP3, and autophagy genes. Western blotting and immunofluorescence analysis were used to analyse the expression of the proteins. Changes in reactive oxygen species (ROS) in cells were observed by flow cytometry. Changes in mitochondrial membrane potential in BV2 cells were detected by JC-1 staining. Peripheral blood mononuclear cells were extracted from blood by density gradient centrifugation and then used for qPCR, western blotting and flow detection. To further explore the mechanism, we used the overexpression plasmids TRIM45 and Atg5 as well as siRNA-TRIM45 and siRNA-Atg5 to analyse the downstream pathway of NLRP3. The protein and mRNA levels of TRIM45 in peripheral blood mononuclear cells from sepsis patients were examined.

RESULTS

Knocking down TRIM45 protected against neuronal damage and cognitive impairment in septic mice. TRIM45 knockdown inhibited microglial pyroptosis and the secretion of inflammatory cytokines in vivo and in vitro, which was mediated by NLRP3/Gsdmd-N activation. Overexpression of TRIM45 could activate NLRP3 and downstream proteins. Further examination showed that TRIM45 regulated the activation of NLRP3 by altering Atg5 and regulating autophagic flux. It was also found that overexpression and knockdown of TRIM45 affected the changes in ROS and mitochondrial membrane potential. Thus, knocking down TRIM45 could reduce microglial pyroptosis, the secretion of proinflammatory cytokines, and neuronal damage and improve cognitive function. In addition, the level of TRIM45 protein in septic patients was increased. There was a positive linear correlation between APACHE II score and TRIM45, between SOFA score and TRIM45. Compared to group GCS > 9, level of TRIM45 were increased in group GCS ≤ 8.

CONCLUSION

TRIM45 plays a key role in neuroinflammation caused by LPS, and the mechanism may involve TRIM45-mediated exacerbation of microglial pyroptosis via the Atg5/NLRP3 axis.

Three-dimensional label-free morphology of CD8 + T cells as a sepsis biomarker

Sepsis is a dysregulated immune response to infection that leads to organ dysfunction and is associated with a high incidence and mortality rate. The lack of reliable biomarkers for diagnosing and prognosis of sepsis is a major challenge in its management. We aimed to investigate the potential of three-dimensional label-free CD8 + T cell morphology as a biomarker for sepsis. This study included three-time points in the sepsis recovery cohort (N = 8) and healthy controls (N = 20). Morphological features and spatial distribution within cells were compared among the patients' statuses. We developed a deep learning model to predict the diagnosis and prognosis of sepsis using the internal cell morphology. Correlation between the morphological features and clinical indices were analysed. Cell morphological features and spatial distribution differed significantly between patients with sepsis and healthy controls and between the survival and non-survival groups. The model for predicting the diagnosis and prognosis of sepsis showed an area under the receiver operating characteristic curve of nearly 100% with only a few cells, and a strong correlation between the morphological features and clinical indices was observed. Our study highlights the potential of three-dimensional label-free CD8 + T cell morphology as a promising biomarker for sepsis. This approach is rapid, requires a minimum amount of blood samples, and has the potential to provide valuable information for the early diagnosis and prognosis of sepsis.

Sepsis-associated encephalopathy: From pathophysiology to clinical management

Sepsis-associated encephalopathy, which presents as delirium and coma, is a significant complication of sepsis characterized by acute brain dysfunction. The presence of inflammatory pathological changes in the brain of sepsis patients and animal models has been recognized since the 1920 s, initially attributed to the entry of microbial toxins into the brain. In the early 2000 s, attention shifted towards the impact of oxidative stress, the cholinergic system, and cytokines on brain function following sepsis onset. More recently, sepsis-associated encephalopathy has been defined as a diffuse brain dysfunction not directly caused by pathogenic infection of the brain. Currently, there is no evidence-based standard for diagnosing sepsis-associated encephalopathy, and clinical management is primarily focused on symptomatic and supportive measures. This review aims to explore the pathophysiology of sepsis-associated encephalopathy and establish the connection between pathophysiological mechanisms and clinical characteristics. We hope that this work will spark the interest of researchers from various fields and contribute to the advancement of sepsis-associated encephalopathy research.

A MACHINE LEARNING MODEL DERIVED FROM ANALYSIS OF TIME-COURSE GENE-EXPRESSION DATASETS REVEALS TEMPORALLY STABLE GENE MARKERS PREDICTIVE OF SEPSIS MORTALITY

ABSTRACT

Sepsis is associated with significant mortality and morbidity among critically ill patients admitted to intensive care units and represents a major health challenge globally. Given the significant clinical and biological heterogeneity among patients and the dynamic nature of the host immune response, identifying those at high risk of poor outcomes remains a critical challenge. Here, we performed secondary analysis of publicly available time-series gene-expression datasets from peripheral blood of patients admitted to the intensive care unit to elucidate temporally stable gene-expression markers between sepsis survivors and nonsurvivors. Using a limited set of genes that were determined to be temporally stable, we derived a dynamical model using a Support Vector Machine classifier to accurately predict the mortality of sepsis patients. Our model had robust performance in a test dataset, where patients' transcriptome was sampled at alternate time points, with an area under the curve of 0.89 (95% CI, 0.82-0.96) upon 5-fold cross-validation. We also identified 7 potential biomarkers of sepsis mortality (STAT5A, CX3CR1, LCP1, SNRPG, RPS27L, LSM5, SHCBP1) that require future validation. Pending prospective testing, our model may be used to identify sepsis patients with high risk of mortality accounting for the dynamic nature of the disease and with potential therapeutic implications.

Prognostic value of serum phosphate levels in sepsis: a systematic review and meta-analysis

Background

There remain controversies over the conclusion of different serum phosphate levels as prognostic predictors of sepsis patients. As such, this study investigated the association between different serum phosphate and the prognosis of sepsis.

Methods

Data from PubMed, Embase, Cochrane Library, and Web of Science were systematically retrieved from the inception of databases to June 1, 2023 and independently screened and extracted by two authors. Binary variables in the study were estimated as relative risk ratio (RR) and 95% confidence interval (CI), and continuous variables were estimated as mean and standard deviation. The Newcastle-Ottawa Scale (NOS) was employed to evaluate the quality of the included studies, and subgroup analysis and sensitivity analysis were performed for all outcomes to explore the sources of heterogeneity.

Results

Ten studies were included in this study including 38,320 patients with sepsis or septic shock. Against normal serum phosphate levels, a high serum phosphate level was associated with an elevated all-cause mortality risk (RR = 1.46; 95% CI [1.22-1.74]; P = 0.000) and prolonged Intensive Care Unit (ICU) length of stay (LOS) (WMD = 0.63; 95% CI [0.27-0.98]; P = 0.001). However, there was no significant difference in the in-hospital LOS (WMD = 0.22; 95% CI [-0.61-1.05]; P = 0.609). A low serum phosphate level was not significantly associated with the all-cause mortality risk (RR = 0.97; 95% CI [0.86-1.09]; P = 0.588), ICU LOS (WMD = -0.23; 95% CI [-0.75-0.29]; P = 0.394) and in-hospital LOS (WMD = -0.62; 95% CI [-1.72-0.49]; P = 0.274).

Conclusion

Sepsis patients with high serum phosphate levels before therapeutic interventions were associated with a significant increase in the all-cause mortality risk, prolonged ICU LOS, and no significant difference in in-hospital LOS. Sepsis patients with low serum phosphate levels before interventions may have a reduced risk of all-cause mortality, shorter ICU LOS, and in-hospital LOS, but the results were not statistically significant.