Biomarkers of sepsis: time for a reappraisal

Dysregulated Coagulation and Fibrinolysis Are Present in Patients Admitted to the Emergency Department with Acute Hypoxemic Respiratory Failure: A Prospective Study

Acute hypoxemic respiratory failure (AHRF) is defined as acute and progressive, and patients are at a greater risk of developing acute respiratory distress syndrome (ARDS). Until now, most studies have focused on prognostic and diagnostic biomarkers in ARDS. Since there is evidence supporting a connection between dysregulated coagulant and fibrinolytic pathways in ARDS progression, it is plausible that this dysregulation also exists in AHRF. The aim of this study was to explore whether levels of soluble endothelial protein C receptor (sEPCR) and plasminogen differentiate patients admitted to the emergency department (ED) with AHRF. sEPCR and plasminogen levels were measured in 130 AHRF patients upon ED presentation by ELISA. Our results demonstrated that patients presenting to the ED with AHRF had elevated levels of sEPCR and plasminogen. It seems that dysregulation of coagulation and fibrinolysis occur in the early stages of respiratory failure requiring hospitalisation. Further research is needed to fully comprehend the contribution of sEPCR and plasminogen in AHRF.

Anti-Inflammatory Potential of the Anti-Diabetic Drug Metformin in the Prevention of Inflammatory Complications and Infectious Diseases Including COVID-19: A Narrative Review

Metformin, a widely used first-line anti-diabetic therapy for the treatment of type-2 diabetes, has been shown to lower hyperglycemia levels in the blood by enhancing insulin actions. For several decades this drug has been used globally to successfully control hyperglycemia. Lactic acidosis has been shown to be a major adverse effect of metformin in some type-2 diabetic patients, but several studies suggest that it is a typically well-tolerated and safe drug in most patients. Further, recent studies also indicate its potential to reduce the symptoms associated with various inflammatory complications and infectious diseases including coronavirus disease 2019 (COVID-19). These studies suggest that besides diabetes, metformin could be used as an adjuvant drug to control inflammatory and infectious diseases. In this article, we discuss the current understanding of the role of the anti-diabetic drug metformin in the prevention of various inflammatory complications and infectious diseases in both diabetics and non-diabetics.

Biomarkers in Sepsis: A Current Review of New Technologies

Sepsis syndromes have been recognized since antiquity yet still pose significant challenges to modern medicine. One of the biggest challenges lies in the heterogeneity of triggers and its protean clinical manifestations, as well as its rapidly progressive and lethal nature. Thus, there is a critical need for biomarkers that can quickly and accurately detect sepsis onset and predict treatment response. In this review, we will briefly describe the current consensus definitions of sepsis and the ideal features of a biomarker. We will then delve into currently available and in-development markers of pathogens, hosts, and their interactions that together comprise the sepsis syndrome.

Immune profile of patients‑a new approach in management of sepsis and septic shock?

The present study was a prospective observational single center study, enrolling 102 patients with sepsis, admitted in the Intensive Care Unit of the County Emergency Clinical Hospital in Târgu Mureș (Mureș, Romania). The main goal of the present study was to compare the changes of the following parameters on day 1 compared with day 5, in sepsis compared with septic shock, as well as in survivors compared with non-survivors: Cell blood count parameters, neutrophil-lymphocyte ratio, platelet-lymphocyte ratio and systemic inflammation index, C reactive protein (CRP), ferritin, procalcitonin (PCT), CD 3+ T cells, CD4+ T cells, CD8+ T cells, CD16+CD56+/CD3-NK cells and CD19+ B cells. The relationship between the subcategories of lymphocytes with the inflammatory markers was evaluated. The serum concentration of CRP and PCT was significantly lower on day 5 compared with day 1 and serum ferritin was significantly higher in patients with septic shock. The percentage of cytotoxic T lymphocytes was significantly decreased and the percentage of NK lymphocytes was significantly increased in patients who developed septic shock. The results indicated a negative significant correlation between the proportion of T lymphocytes and PCT concentration and a positive significant correlation between the proportion of B lymphocytes and PCT concentration.

Early prediction of sepsis-induced respiratory tract infection using a biomarker-based machine-learning algorithm

Early and differential diagnosis of sepsis is essential to avoid unnecessary antibiotic use and further reduce patient morbidity and mortality. Here, we aimed to identify predictors of sepsis and advance a machine-learning strategy to predict sepsis-induced respiratory tract infection (RTI). Patients with sepsis and RTI were selected via retrospective analysis, and essential population characteristics and laboratory parameters were recorded. To improve the performance of the primary model and avoid over-fitting, a recursive feature elimination with cross-validation (RFECV) strategy was used to screen the optimal subset of biomarkers and construct nine machine-learning models based on this subset; the average accuracy, precision, recall, and F1-score were used for evaluation of the models. We identified 430 patients with sepsis and 686 patients with RTI. A total of 39 features were collected, with 23 features identified for initial model construction. Using the RFECV algorithm, we found that the XGBoost classifier, which only needed to include seven biomarkers, demonstrated the best performance among all prediction models, with an average accuracy of 89.24 ± 2.28, while the Ridge classifier, which included 11 biomarkers, had an average accuracy of only 83.87 ± 4.69. The remaining models had prediction accuracies greater than 88%. We developed nine models for predicting sepsis using a strategy that combined RFECV with machine learning. Among these models, the XGBoost classifier, which included seven biomarkers, showed the best performance and highest accuracy for predicting sepsis and may be a promising tool for the timely identification of sepsis.

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.

Monocytic myeloid-derived suppressor cells as an immune indicator of early diagnosis and prognosis in patients with sepsis

BACKGROUND

Immunosuppression is a leading cause of septic death. Therefore, it is necessary to search for biomarkers that can evaluate the immune status of patients with sepsis. We assessed the diagnostic and prognostic value of low-density neutrophils (LDNs) and myeloid-derived suppressor cells (MDSCs) subsets in the peripheral blood mononuclear cells (PBMCs) of patients with sepsis.

METHODS

LDNs and MDSC subsets were compared among 52 inpatients with sepsis, 33 inpatients with infection, and 32 healthy controls to investigate their potential as immune indicators of sepsis. The percentages of LDNs, monocytic MDSCs (M-MDSCs), and polymorphonuclear MDSCs (PMN-MDSCs) in PBMCs were analyzed. Sequential organ failure assessment (SOFA) scores, C-reactive protein (CRP), and procalcitonin (PCT) levels were measured concurrently.

RESULTS

The percentages of LDNs and MDSC subsets were significantly increased in infection and sepsis as compared to control. MDSCs performed similarly to CRP and PCT in diagnosing infection or sepsis. LDNs and MDSC subsets positively correlated with PCT and CRP levels and showed an upward trend with the number of dysfunctional organs and SOFA score. Non-survivors had elevated M-MDSCs compared with that of patients who survived sepsis within 28 days after enrollment.

CONCLUSIONS

MDSCs show potential as a diagnostic biomarker comparable to CRP and PCT, in infection and sepsis, even in distinguishing sepsis from infection. M-MDSCs show potential as a prognostic biomarker of sepsis and may be useful to predict 28-day hospital mortality in patients with sepsis.

Improved diagnostic markers for invasive pulmonary aspergillosis in COPD patients

Background

The prevalence of invasive pulmonary aspergillosis (IPA) among patients with chronic obstructive pulmonary disease (COPD) is steadily increasing, leading to high mortality. Although early diagnosis can significantly reduce mortality, the efficacy of current diagnostic methods is limited. Consequently, there is a need for novel approaches for early IPA detection.

Methods

This retrospective study involved 383 hospitalized COPD patients with GOLD stages III and IV. The IPA group (67 patients) and non-IPA group (316 patients) were identified at the First Affiliated Hospital of Guangzhou Medical University between January 2016 and February 2022. We analyzed common serological indicators in our hospital to identify predictive indicators for the early diagnosis of IPA in COPD patients.

Results

The sensitivity and specificity of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), lactate dehydrogenase (LDH), and ceruloplasmin (CER) for diagnosing IPA in COPD patients were as follows: CRP (91.2%, 57.7%), ESR (77.5%, 73.0%), PCT (60.5%, 71.4%), LDH (50.0%, 88.8%), and CER (60.7%, 74.3%). Combinations of biomarkers, such as CRP-ESR, CRP-LDH, ESR-LDH, ESR-CER, and LDH-CER, showed promising diagnostic potential, with larger area under the curve (AUC) values for IPA diagnosis in COPD patients. However, no statistically significant difference was observed between the diagnostic efficacy of single biomarkers and combined biomarkers. Notably, compared to those in the unassisted ventilation group, the patients in the assisted ventilation group (including noninvasive ventilation and tracheal intubation/incision-assisted ventilation group) exhibited significantly greater PCT and LDH levels, while the CER significantly decreased (p=0.021). There were no significant differences in biomarker levels between the ICU group and the non-ICU group. CRP (p<0.01), ESR (p=0.028), PCT (p<0.01), and CER (p<0.01) were positively correlated with hospitalization duration, whereas LDH was not correlated with hospitalization duration.

Conclusion

Our study highlights the diagnostic potential of CRP, ESR, PCT, LDH, and CER for IPA in COPD patients. CRP and LDH can also initially predict the need for assisted ventilation, while CRP can initially estimate the length of hospitalization. This study represents the first report of the potential of CER for diagnosing IPA, suggesting its significance for further research.

Profiling the dysregulated immune response in sepsis: overcoming challenges to achieve the goal of precision medicine

Sepsis is characterised by a dysregulated host immune response to infection. Despite recognition of its significance, immune status monitoring is not implemented in clinical practice due in part to the current absence of direct therapeutic implications. Technological advances in immunological profiling could enhance our understanding of immune dysregulation and facilitate integration into clinical practice. In this Review, we provide an overview of the current state of immune profiling in sepsis, including its use, current challenges, and opportunities for progress. We highlight the important role of immunological biomarkers in facilitating predictive enrichment in current and future treatment scenarios. We propose that multiple immune and non-immune-related parameters, including clinical and microbiological data, be integrated into diagnostic and predictive combitypes, with the aid of machine learning and artificial intelligence techniques. These combitypes could form the basis of workable algorithms to guide clinical decisions that make precision medicine in sepsis a reality and improve patient outcomes.

The usefulness of lactate/albumin ratio, C-reactive protein/albumin ratio, procalcitonin/albumin ratio, SOFA, and qSOFA in predicting the prognosis of patients with sepsis who presented to EDs

PURPOSE

Early identification of sepsis with a poor prognosis in the emergency department (ED) is crucial for prompt management and improved outcomes. This study aimed to examine the predictive value of sequential organ failure assessment (SOFA), quick SOFA (qSOFA), lactate to albumin ratio (LAR), C-reactive protein to albumin ratio (CAR), and procalcitonin to albumin ratio (PAR), obtained in the ED, as predictors for 28-day mortality in patients with sepsis and septic shock.

MATERIALS AND METHODS

We included 3499 patients (aged ≥19 years) from multicenter registry of the Korean Shock Society between October 2015 and December 2019. The SOFA score, qSOFA score, and lactate level at the time of registry enrollment were used. Albumin, C-reactive protein, and procalcitonin levels were obtained from the initial laboratory results measured upon ED arrival. We evaluated the predictive accuracy for 28-day mortality using the area under the receiver operating characteristic (AUROC) curve. A multivariable logistic regression analysis of the independent predictors of 28-day mortality was performed. The SOFA score, LAR, CAR, and PAR were converted to categorical variables using Youden's index and analyzed. Adjusting for confounding factors such as age, sex, comorbidities, and infection focus, adjusted odds ratios (aOR) were calculated.

RESULTS

Of the 3499 patients, 2707 (77.4%) were survivors, whereas 792 (22.6%) were non-survivors. The median age of the patients was 70 (25th-75th percentiles, 61-78), and 2042 (58.4%) were male. LAR for predicting 28-day mortality had the highest AUROC, followed by the SOFA score (0.715; 95% confidence interval (CI): 0.69-0.74 and 0.669; 95% CI: 0.65-0.69, respectively). The multivariable logistic regression analysis revealed that the aOR of LAR >1.52 was 3.75 (95% CI: 3.16-4.45), and the aOR, of SOFA score at enrollment >7.5 was 2.67 (95% CI: 2.25-3.17).

CONCLUSION

The results of this study showed that LAR is a relatively strong predictor of sepsis prognosis in the ED setting, indicating its potential as a straightforward and practical prognostic factor. This finding may assist healthcare providers in the ED by providing them with tools to risk-stratify patients and predict their mortality.

Early prediction of sepsis in intensive care patients using the machine learning algorithm NAVOY® Sepsis, a prospective randomized clinical validation study

PURPOSE

To prospectively validate, in an ICU setting, the prognostic accuracy of the sepsis prediction algorithm NAVOY® Sepsis which uses 4 h of input for routinely collected vital parameters, blood gas values, and lab values.

MATERIALS AND METHODS

Patients 18 years or older admitted to the ICU at Skåne University Hospital Malmö from December 2020 to September 2021 were recruited in the study. A total of 304 patients were randomized into one of two groups: Algorithm group with active sepsis alerts, or Standard of care. NAVOY® Sepsis made silent predictions in the Standard of care group, in order to evaluate its performance without disturbing the outcome. The study was blinded, i.e., study personnel did not know to which group patients were randomized. The healthcare provider followed standard practices in assessing possible development of sepsis and intervening accordingly. The patients were followed-up in the study until ICU discharge.

RESULTS

NAVOY® Sepsis could predict the development of sepsis, according to the Sepsis-3 criteria, three hours before sepsis onset with high performance: accuracy 0.79; sensitivity 0.80; and specificity 0.78.

CONCLUSIONS

The accuracy, sensitivity, and specificity were all high, validating the prognostic accuracy of NAVOY® Sepsis in an ICU setting, including Covid-19 patients.

Comparison of Clinical Characteristics and Biomarkers in Culture-Positive and Culture-Negative Sepsis Patients

OBJECTIVES

Sepsis is one of the leading causes of morbidity and mortality worldwide, and culture-negative sepsis, despite its prevalence, is largely understudied. The current study intends to examine clinical characteristics and biomarkers in culture-positive and culture-negative sepsis, focusing on 30-day mortality and duration of hospital stay in both groups.  Materials and methods: A prospective observational comparative cohort study was done on 150 patients admitted to the intensive care unit (ICU) and wards of Jaipur Golden Hospital. Patients with documented fungal, viral, or parasitic infections, as well as those who had undergone surgery or experienced trauma, were excluded.  Results: The mean age of the patients was 51.31±18.94 years. Of 150 patients, 95 (63.3%) were culture-negative, whereas 55 (36.7%) were culture-positive, with more men in the former and more women in the latter. Patients with negative cultures had fewer comorbidities. The levels of procalcitonin (PCT), C-reactive protein (CRP), and serum lactate were within the prescribed limit for both culture-negative and positive patients. A higher proportion (87.3%) of the organisms isolated from culture-positive individuals were gram-negative, with Escherichia coli (E. coli) having the highest prevalence (27.3%), followed by Klebsiella (20%). There were 12.7% gram-positive isolates. The culture-negative patients had significantly better outcomes (P=0.003) as well as the duration of hospital stay (P<0.001) than the culture-positive patients. Culture-positive patients had a more severe illness, a higher incidence of septic shock, and a higher fatality rate than culture-negative patients.

CONCLUSION

It can be concluded that CRP and PCT can be used as clinically reliable sepsis biomarkers in both culture-positive and culture-negative patients. The study found that culture-negative sepsis is more prevalent and that there are substantial differences between culture-negative and culture-positive sepsis, with the former group having fewer comorbidities, less severe illness, a shorter duration of hospital stays, lower death rates, and better outcomes.

Maresins as novel anti-inflammatory actors and putative therapeutic targets in sepsis

Sepsis, a complex clinical syndrome characterized by an exaggerated host response to infection, often necessitates hospitalization and intensive care unit admission. Delayed or inaccurate diagnosis of sepsis, coupled with suboptimal treatment strategies, can result in unfavorable outcomes, including mortality. Maresins, a newly discovered family of lipid mediators synthesized from docosahexaenoic acid by macrophages, have emerged as key players in promoting inflammation resolution and the termination of inflammatory processes. Extensive evidence has unequivocally demonstrated the beneficial effects of maresins in modulating the inflammatory response associated with sepsis; however, their bioactivity and functions exhibit remarkable diversity and complexity. This article presents a comprehensive review of recent research on the role of maresins in sepsis, aiming to enhance our understanding of their effectiveness and elucidate the specific mechanisms underlying their actions in sepsis treatment. Furthermore, emerging insights into the management of patients with sepsis are also highlighted.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Predictive value of the neutrophil-to-lymphocyte ratio in the prognosis and risk of death for adult sepsis patients: a meta-analysis

Background

The neutrophil-to-lymphocyte ratio (NLR) is a commonly used biomarker for acute inflammation that often rises during sepsis, making it a valuable diagnostic indicator for clinical practice. However, no consensus has been reached on the prognostic value of NLR for predicting the prognosis and mortality risk in adult sepsis patients. In light of this controversy, we conducted a meta-analysis to clarify the prognostic significance of NLR in adult sepsis patients. The meta-analysis was registered in the PROSPERO database (registration number CRD42023433143).

Methods

We performed a comprehensive literature search in PubMed, Cochrane Library, Ovid, and Springer databases, using retrieval terms "sepsis" or "septic shock" and "prognosis" or "mortality" for studies published between January 1, 2000, and May 31, 2023. Children and neonates with sepsis were excluded from our research. Two independent researchers conducted the literature search and data extraction. Consensus was reached when discrepancies occurred, and in case of persistent discrepancies, the final decision was made by the research supervisor. The hazard ratio (HR) and its corresponding 95% confidence interval (95% CI) were extracted from each study included in the analysis. A random-effects model was used to synthesize all HRs and their 95% CIs. Sensitivity analysis was performed to investigate heterogeneity. Sensitivity analysis was conducted to identify studies that had a significant impact on the overall results of the meta-analysis. Subgroup analysis and meta-regression were performed to explore sources of heterogeneity. Egger's test was also used to investigate publication bias in this meta-analysis.

Results

After a comprehensive literature search and screening, we included 12 studies comprising 10,811 patients for the meta-analysis. The pooled results indicated that patients with a higher NLR level were associated with a poor prognosis (Random-effects model, HR: 1.6273, 95% CI: 1.3951-1.8981). Heterogeneity testing showed significant heterogeneity (I2 = 87.2%, 95% CI: 79.5-92, p<0.0001). Sensitivity analysis was performed to investigate the sources of heterogeneity, which revealed that the omission of one highly sensitive study significantly reduced the I2 value. After removing this study, a strong association was found between a higher NLR level and poor prognosis and risk of death in adult sepsis patients (Random-effects model, HR: 1.6884, 95% CI: 1.4338-1.9882). Both subgroup analysis and meta-regression indicated that the study design and testing time of NLR were sources of heterogeneity. Egger's test showed no obvious publication bias in this meta-analysis.

Conclusion

NLR is a reliable and valuable biomarker for predicting prognosis and the risk of death in adult sepsis patients.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023433143] PROSPERO, identifier [CRD42023433143].

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.

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.

Applying Machine Learning to Blood Count Data Predicts Sepsis with ICU Admission

BACKGROUND

Timely diagnosis is crucial for sepsis treatment. Current machine learning (ML) models suffer from high complexity and limited applicability. We therefore created an ML model using only complete blood count (CBC) diagnostics.

METHODS

We collected non-intensive care unit (non-ICU) data from a German tertiary care centre (January 2014 to December 2021). Using patient age, sex, and CBC parameters (haemoglobin, platelets, mean corpuscular volume, white and red blood cells), we trained a boosted random forest, which predicts sepsis with ICU admission. Two external validations were conducted using data from another German tertiary care centre and the Medical Information Mart for Intensive Care IV database (MIMIC-IV). Using the subset of laboratory orders also including procalcitonin (PCT), an analogous model was trained with PCT as an additional feature.

RESULTS

After exclusion, 1 381 358 laboratory requests (2016 from sepsis cases) were available. The CBC model shows an area under the receiver operating characteristic (AUROC) of 0.872 (95% CI, 0.857-0.887). External validations show AUROCs of 0.805 (95% CI, 0.787-0.824) for University Medicine Greifswald and 0.845 (95% CI, 0.837-0.852) for MIMIC-IV. The model including PCT revealed a significantly higher AUROC (0.857; 95% CI, 0.836-0.877) than PCT alone (0.790; 95% CI, 0.759-0.821; P < 0.001).

CONCLUSIONS

Our results demonstrate that routine CBC results could significantly improve diagnosis of sepsis when combined with ML. The CBC model can facilitate early sepsis prediction in non-ICU patients with high robustness in external validations. Its implementation in clinical decision support systems has strong potential to provide an essential time advantage and increase patient safety.

Defining sepsis in small animals

OBJECTIVE

To discuss the definitions of sepsis in human and veterinary medicine.

DESIGN

International, multicenter position statement on the need for consensus definitions of sepsis in veterinary medicine.

SETTING

Veterinary private practice and university teaching hospitals.

ANIMALS

Dogs and cats.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Sepsis is a life-threatening condition associated with the body's response to an infection. In human medicine, sepsis has been defined by consensus on 3 occasions, most recently in 2016. In veterinary medicine, there is little uniformity in how sepsis is defined and no consensus on how to identify it clinically. Most publications rely on modified criteria derived from the 1991 and 2001 human consensus definitions. There is a divergence between the human and veterinary descriptions of sepsis and no consensus on how to diagnose the syndrome. This impedes research, hampers the translation of pathophysiology insights to the clinic, and limits our abilities to optimize patient care. It may be time to formally define sepsis in veterinary medicine to help the field move forward. In this narrative review, we present a synopsis of prior attempts to define sepsis in human and veterinary medicine, discuss developments in our understanding, and highlight some criticisms and shortcomings of existing schemes.

CONCLUSIONS

This review is intended to serve as the foundation of current efforts to establish a consensus definition for sepsis in small animals and ultimately generate evidence-based criteria for its recognition in veterinary clinical practice.

HEPARIN-BINDING PROTEIN LEVELS PREDICT UNFAVORABLE OUTCOME IN COVID-19 PNEUMONIA: A POST HOC ANALYSIS OF THE SAVE TRIAL

ABSTRACT

We aimed to evaluate heparin-binding protein (HBP) as a marker of prognosis of unfavorable outcome in COVID-19 pneumonia. This was a post hoc analysis of the SAVE clinical trial investigating anakinra treatment, guided by suPAR (soluble urokinase plasminogen activator receptor) levels ≥6 ng/mL, for the prevention of severe respiratory failure in hospitalized patients with COVID-19 pneumonia. Baseline HBP plasma levels were measured in 534 patients by fluorescence dry quantitative immunoassay using the Jet-iStar 800 analyzer. Concentrations higher than 35 ng/mL predicted 30-day mortality with a moderate specificity of 53.3% and negative predictive value 78.1%; sensitivity was low (29.0%). After multivariate Cox analysis, HBP higher than 35 ng/mL was an independent predictor of 30-day unfavorable outcome (adjusted hazard ratio, 1.77; 95% CI, 1.06-2.94; P = 0.028) and these patients were also at greater risk of death after 90 days (hazard ratio, 1.85; 95% CI, 1.25-2.74; P = 0.002). The cutoff was not predictive of development of severe respiratory failure, septic shock or acute kidney injury. Among patients with baseline HBP levels higher than 35 ng/mL, anakinra treatment was associated with decreased mortality (7.2%) versus comparators (18.1%; P < 0.001). Results confirm that HBP may be an early biomarker of poor outcome among preselected patients at risk from COVID-19 pneumonia.ClinicalTrials.gov registration NCT04357366.

Blood neutrophil to lymphocyte ratio is associated with 90-day mortality and 60-day readmission in Gram negative bacteremia: a multi-center cohort study

INTRODUCTION

The Neutrophil-Lymphocyte Ratio (NLR) in blood has demonstrated its capability to predict bacteremia in emergency departments, and its association with mortality has been established in patients with sepsis in intensive care units. However, its potential concerning mortality and readmission in patients with Gram-negative bacteremia (GNB) is unexplored.

METHODS

This retrospective cohort study included patients with GNB between 2018 and 2022 from six hospitals in the Capital Region of Denmark. Patients who were immunosuppressed or had missing NLR values on the day of blood culture were excluded. Logistic regression models were used to analyze the association between NLR levels and 90-day all-cause mortality, while the logit link interpretation of the cumulative incidence function was used to assess the association between NLR levels and 60-day readmission. Associations were quantified as odds ratios (OR) with corresponding 95% confidence intervals (CI).

RESULTS

The study included 1763 patients with a median age was 76.8 years and 51.3% were female. The median NLR was 17.3 and 15.8% of patients had a quick sequential organ failure assessment score of two or three. Urinary tract infection (UTI) was the most frequent focus and Escherichia coli the most frequent pathogen. Statistically significant differences in median NLR were found by age group and pathogen, and for patients with or without hypertension, liver disease, chronic obstructive pulmonary disease, dementia, and alcohol abuse. 378 patients (21.4%) died before 90 days. 526 (29.8%) patients were readmitted to the hospital within 60 days. For each doubling of the NLR, the OR for all-cause 90-day mortality was 1.15 (95% CI, 1.04-1.27) and 1.12 (95% CI, 1.02-1.24) for 60-day readmission. Analysis of subgroups did not show statistically significant differences between groups in relation to the association between NLR and mortality. The discriminatory ability of NLR for mortality was limited and comparable to blood neutrophil or lymphocyte count, producing receiver operating characteristic curves with an area under the curve of 0.59 (95% CI, 0.56-0.63), 0.60 (95% CI, 0.56-0.65) and 0.53 (95% CI, 0.49-0.56), respectively.

CONCLUSION

Blood neutrophil-lymphocyte ratio was associated with 90-day all-cause mortality and 60-day readmission in patients with GNB. However, the ratio has limited ability in predicting mortality or readmission.

Prognostic stratification of sepsis through DNA damage response based RiskScore system: insights from single-cell RNA-sequencing and transcriptomic profiling

Background

A novel risk scoring system, predicated on DNA damage response (DDR), was developed to enhance prognostic predictions and potentially inform the creation of more effective therapeutic protocols for sepsis.

Methods

To thoroughly delineate the expression profiles of DDR markers within the context of sepsis, an analytical approach utilizing single-cell RNA-sequencing (scRNA-seq) was implemented. Our study utilized single-cell analysis techniques alongside weighted gene co-expression network analysis (WGCNA) to pinpoint the genes that exhibit the most substantial associations with DNA damage response (DDR). Through Cox proportional hazards LASSO regression, we distinguished DDR-associated genes and established a risk model, enabling the stratification of patients into high- and low-risk groups. Subsequently, we carried out an analysis to determine our model's predictive accuracy regarding patient survival. Moreover, we examined the distinct biological characteristics, various signal transduction routes, and immune system responses in sepsis patients, considering different risk categories and outcomes related to survival. Lastly, we conducted experimental validation of the identified genes through in vivo and in vitro assays, employing RT-PCR, ELISA, and flow cytometry.

Results

Both single-cell RNA sequencing (scRNA-seq) and bulk transcriptomic analyses have demonstrated a strong correlation between DNA damage response (DDR) levels and sepsis prognosis. Specific cell subtypes, including monocytes, megakaryocytes, CD4+ T cells, and neutrophils, have shown elevated DDR activity. Cells with increased DDR scores exhibited more robust and numerous interactions with other cell populations. The weighted gene co-expression network analysis (WGCNA) and single-cell analyses revealed 71 DDR-associated genes. We developed a four-gene risk scoring system using ARL4C, CD247, RPL7, and RPL31, identified through univariate COX, LASSO COX regression, and log-rank (Mantel-Cox) tests. Nomograms, calibration plots, and decision curve analyses (DCA) regarding these specific genes have provided significant clinical benefits for individuals diagnosed with sepsis. The study suggested that individuals categorized as lower-risk demonstrated enhanced infiltration of immune cells, upregulated expression of immune regulators, and a more prolific presence of immune-associated functionalities and pathways. RT-qPCR analyses on a sepsis rat model revealed differential gene expression predominantly in the four targeted genes. Furthermore, ARL4C knockdown in sepsis model in vivo and vitro caused increased inflammatory response and a worse prognosis.

Conclusion

The delineated DDR expression landscape offers insights into sepsis pathogenesis, whilst our riskScore model, based on a robust four-gene signature, could underpin personalized sepsis treatment strategies.

Clinical Application of Serum Interleukin-6 Combined with Inflammatory Cytokines in the Dynamic Monitoring of Patients with Acute Cholecystitis

Objective

To investigate the dynamic fluctuations of serum interleukin-6 (IL-6), procalcitonin (PCT), and neutrophil counts in individuals diagnosed with acute cholecystitis. Additionally, the research seeks to investigate the potential clinical significance of these biomarkers in the early stages of acute cholecystitis.

Methods

This retrospective cohort study included one hundred patients with acute cholecystitis (60 with mild acute cholecystitis and 40 with severe cholecystitis) admitted to our hospital between January 2022 and December 2022 were included. The levels of various cytokines, PCT and neutrophils in serum on days 1, 3, 5, and 7 were dynamically detected. The difference in each indicator between the two groups was analysed, and the diagnostic value of each indicator for acute cholecystitis was evaluated using a receiver operating characteristic (ROC) curve.

Results

IL-6 and PCT levels and neutrophil counts were significantly higher in patients with moderate and severe cholecystitis than those in those with mild cholecystitis (P <0.01). The AUC values for the three indicators were all greater than 60%, and the AUC value for the joint diagnosis of the three indicators reached 90%.

Conclusion

Serum interleukin-6 combined with PCT and neutrophil count is helpful to determine the degree of disease development in patients with acute cholecystitis. The advantage of dynamic monitoring of the three indicators is that the detection is simple and worthy of clinical promotion.

The Role of New Morphological Parameters Provided by the BC 6800 Plus Analyzer in the Early Diagnosis of Sepsis

BACKGROUND

Late diagnosis of sepsis is associated with adverse consequences and high mortality rate. The aim of this study was to evaluate the diagnostic value of hematologic research parameters, that reflect the cell morphology of blood cells, available on the BC 6800 plus automated analyzer (Mindray) for the early detection of sepsis.

MATERIALS AND METHODS

A complete blood count (CBC) was performed by Mindray BC 6800 Plus Analyzer in 327 patients (223 with a confirmed diagnosis of sepsis following sepsis-3 criteria, 104 without sepsis), admitted at the Intensive Care Unit of the Novara's Hospital (Italy) and in 56 patients with localized infection.

RESULTS

In univariate logistic regression, age, Hb, RDW, MO#, NMR, NeuX, NeuY, NeuZ, LymX, MonX, MonY, MonZ were associated with sepsis (p < 0.005). In multivariate analysis, only RDW, NeuX, NeuY, NeuZ, MonX and MonZ were found to be independent predictors of sepsis (p < 0.005). Morphological research parameters are confirmed to be predictors of sepsis even when analyzing the group with localized infection.

CONCLUSIONS

In addition to already established biomarkers and basic CBC parameters, new morphological cell parameters can be a valuable aid in the early diagnosis of sepsis at no additional cost.

A pairwise cytokine code explains the organism-wide response to sepsis

Sepsis is a systemic response to infection with life-threatening consequences. Our understanding of the molecular and cellular impact of sepsis across organs remains rudimentary. Here, we characterize the pathogenesis of sepsis by measuring dynamic changes in gene expression across organs. To pinpoint molecules controlling organ states in sepsis, we compare the effects of sepsis on organ gene expression to those of 6 singles and 15 pairs of recombinant cytokines. Strikingly, we find that the pairwise effects of tumor necrosis factor plus interleukin (IL)-18, interferon-gamma or IL-1β suffice to mirror the impact of sepsis across tissues. Mechanistically, we map the cellular effects of sepsis and cytokines by computing changes in the abundance of 195 cell types across 9 organs, which we validate by whole-mouse spatial profiling. Our work decodes the cytokine cacophony in sepsis into a pairwise cytokine message capturing the gene, cell and tissue responses of the host to the disease.

Clinical value of the red blood cell distribution width to albumin ratio in the assessment of prognosis in critically ill patients with sepsis: a retrospective analysis

Background

Red blood cell (RBC) distribution width (RDW) to albumin ratio is a novel biomarker and its prognostic effect on critically ill patients with sepsis has not been extensively investigated. The objective of this study was to identify the prognostic value of the RDW to albumin ratio in these patients.

Methods

Data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. A Cox proportional hazards model and restricted cubic spline model were used to determine the association of RDW to albumin ratio with mortality. Receiver operating characteristic (ROC) curves and Kaplan-Meier survival curves were applied, and the area under the curve (AUC) was used to compare the predictive value.

Results

A total of 3,969 eligible patients were enrolled. The median RDW to albumin ratio was significantly higher in non-survivors than in survivors at 30 and 90 days. Patients were divided into groups according to the RDW to albumin ratio, and the risk of 30- and 90-day mortality markedly increased in the group with a higher ratio. The relationship between the RDW to albumin ratio as a continuous variable and 30-day mortality also showed an upward trend in the restricted cubic spline. The AUC of the RDW to albumin ratio was 0.633 in discriminating 30-day mortality which was similar to that of the lactate to albumin ratio (AUC =0.617; P=0.133) and higher than that of the neutrophil percentage to albumin ratio (AUC =0.559; P<0.001).

Conclusions

The RDW to albumin ratio is a promising biomarker for assessing the prognosis of critically ill patients with sepsis. Its predictive value in determining mortality was found to be similar to that of the lactate to albumin ratio and superior to that of the neutrophil percentage to albumin ratio.

Proposed Framework for Conducting Clinically Relevant Translational Biomarker Research for the Diagnosis, Prognosis and Management of Sepsis

Although the diagnosis of sepsis requires the identification of the three components of infection, a systemic inflammation response, and organ dysfunction, there is currently no consensus on gold-standard criteria. There are however suggested tools and tests, which have been proposed in international guidelines, including those produced by the Surviving Sepsis Campaign. Biomarkers play an important role in these tools and tests, and numerous heterogeneous studies have been performed to evaluate their respective clinical utility. Our review of the current practice shows that no biomarkers of infection, systemic inflammation response, organ dysfunction and sepsis are currently specifically recommended, which is probably due to the lack of standardization of studies. We therefore propose to define a framework for conducting clinically relevant translational biomarker research and seek to establish ideal criteria that can be applied to an infection, systemic inflammation response, organ dysfunction and sepsis biomarkers, which can enable early screening of sepsis, diagnosis of sepsis at the time of clinical suspicion and monitoring of sepsis treatment efficacy.

An overview of the mechanisms and potential roles of extracellular vesicles in septic shock

Septic shock, a subset of sepsis, is a fatal condition associated with high morbidity and mortality. However, the pathophysiology of septic shock is not fully understood. Moreover, the diagnostic markers employed for identifying septic shock lack optimal sensitivity and specificity. Current treatment protocols for septic shock have not been effective in lowering the mortality rate of patients. Most cells exhibit the capability to release extracellular vesicles (EVs), nanoscale vesicles that play a vital role in intercellular communication. In recent years, researchers have investigated the potential role of EVs in the pathogenesis, diagnosis, and treatment of different diseases, such as oncological, neurological, and cardiovascular diseases, as well as diabetes and septic shock. In this article, we present an overview of the inhibitory and facilitative roles that EVs play in the process of septic shock, the potential role of EVs in the diagnosis of septic shock, and the potential therapeutic applications of both native and engineered EVs in the management of septic shock.

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.

Micromotor-based dual aptassay for early cost-effective diagnosis of neonatal sepsis

Given the long-life expectancy of the newborn, research aimed at improving sepsis diagnosis and management in this population has been recognized as cost-effective, which at early stages continues to be a tremendous challenge. Despite there is not an ideal-specific biomarker, the simultaneous detection of biomarkers with different behavior during an infection such as procalcitonin (PCT) as high specificity biomarker with one of the earliest biomarkers in sepsis as interleukin-6 (IL-6) increases diagnostic performance. This is not only due to their high positive predictive value but also, since it can also help the clinician to rule out infection and thus avoid the use of antibiotics, due to their high negative predictive value. To this end, we explore a cutting-edge micromotor (MM)-based OFF-ON dual aptassay for simultaneous determination of both biomarkers in 15 min using just 2 μL of sample from low-birth-weight neonates with gestational age less than 32 weeks and birthweight below 1000 g with clinical suspicion of late-onset sepsis. The approach reached the high sensitivities demanded in the clinical scenario (LODPCT = 0.003 ng/mL, LODIL6 = 0.15 pg/mL) with excellent correlation performance (r > 0.9990, p < 0.05) of the MM-based approach with the Hospital method for both biomarkers during the analysis of diagnosed samples and reliability (Er < 6% for PCT, and Er < 4% for IL-6). The proposed approach also encompasses distinctive technical attributes in a clinical scenario since its minimal sample volume requirements and expeditious results compatible with few easy-to-obtain drops of heel stick blood samples from newborns admitted to the neonatal intensive care unit. This would enable the monitoring of both sepsis biomarkers within the initial hours after the manifestation of symptoms in high-risk neonates as a valuable tool in facilitating prompt and well-informed decisions about the initiation of antibiotic therapy.These results revealed the asset behind micromotor technology for multiplexing analysis in diagnosing neonatal sepsis, opening new avenues in low sample volume-based diagnostics.

Bioinformatics reveals diagnostic potential of cuproptosis-related genes in the pathogenesis of sepsis

Background

Multiple modes of cell death occur during the development of sepsis. Among these patterns, cuproptosis has recently been identified as a regulated form of cell death. However, its impact on the onset and progression of sepsis remains unclear.

Method

We screened a dataset of gene expression profiles from patients with sepsis using the GEO database. Survival analysis was performed to analyze the relationship between cuproptosis-related genes (CRGs) and prognosis. Hub genes were identified through univariate Cox regression analysis. The diagnostic value of hub genes in sepsis was tested in both training sets (GSE65682) and validation sets (GSE134347). To examine the association between hub genes and immune cells, single-sample gene set enrichment analysis (ssGSEA) and Pearson correlation analysis were employed. Additionally, the CRGs were validated in a septic mouse model using real-time quantitative PCR (qRT-PCR) and immunohistochemistry (IHC).

Results

In sepsis, most CRGs were upregulated, with only DLD and MTF1 downregulated. High expression of three genes (GLE, LIAS, and PDHB) was associated with better prognosis, but only two hub genes (LIAS, PDHB) reached statistical significance. The receiver operating characteristic (ROC) analysis for diagnosing sepsis showed LIAS had a range of 0.793-0.906, while PDHB achieved values of 0.882 and 0.975 in the training and validation sets, respectively. ssGSEA analysis revealed a lower number of immune cells in the sepsis group, and there was a correlation between immune cell population and CRGs (LIAS, PDHB). Analysis in the septic mouse model demonstrated no significant difference in mRNA expression levels and IHC staining between LIAS and PDHB in heart and liver tissues, but up-regulation was observed in lung tissues. Furthermore, the mRNA expression levels and IHC staining of LIAS and PDHB were down-regulated in renal tissues.

Conclusions

Cuproptosis is emerging as a significant factor in the development of sepsis. LIAS and PDHB, identified as potential diagnostic biomarkers for cuproptosis-associated sepsis, are believed to play crucial roles in the initiation and progression of cuproptosis-induced sepsis.

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.

The critical role of neutrophil-endothelial cell interactions in sepsis: new synergistic approaches employing organ-on-chip, omics, immune cell phenotyping and in silico modeling to identify new therapeutics

Sepsis is a global health concern accounting for more than 1 in 5 deaths worldwide. Sepsis is now defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis can develop from bacterial (gram negative or gram positive), fungal or viral (such as COVID) infections. However, therapeutics developed in animal models and traditional in vitro sepsis models have had little success in clinical trials, as these models have failed to fully replicate the underlying pathophysiology and heterogeneity of the disease. The current understanding is that the host response to sepsis is highly diverse among patients, and this heterogeneity impacts immune function and response to infection. Phenotyping immune function and classifying sepsis patients into specific endotypes is needed to develop a personalized treatment approach. Neutrophil-endothelium interactions play a critical role in sepsis progression, and increased neutrophil influx and endothelial barrier disruption have important roles in the early course of organ damage. Understanding the mechanism of neutrophil-endothelium interactions and how immune function impacts this interaction can help us better manage the disease and lead to the discovery of new diagnostic and prognosis tools for effective treatments. In this review, we will discuss the latest research exploring how in silico modeling of a synergistic combination of new organ-on-chip models incorporating human cells/tissue, omics analysis and clinical data from sepsis patients will allow us to identify relevant signaling pathways and characterize specific immune phenotypes in patients. Emerging technologies such as machine learning can then be leveraged to identify druggable therapeutic targets and relate them to immune phenotypes and underlying infectious agents. This synergistic approach can lead to the development of new therapeutics and the identification of FDA approved drugs that can be repurposed for the treatment of sepsis.

Association Between Plasma Levels of Monocyte Chemoattractant Protein-1 (MCP-1) and 28-Day Mortality in Elderly Patients with Sepsis: A Retrospective Single-Center Study

BACKGROUND Previous studies have identified an association between plasma levels of the inflammatory cytokine, monocyte chemoattractant protein-1 (MCP-1), and outcomes for patients with sepsis. This retrospective single-center study assessed the association between plasma levels of MCP-1 and 28-day mortality in 136 patients ≥65 years diagnosed with sepsis between October 2020 and October 2021. MATERIAL AND METHODS The objective was to compare and analyze the parameters in the survival group (n=35) and the 28-day mortality group (n=101), including Sequential Organ Failure Assessment (SOFA), Acute Physiology and Chronic Health Evaluation II (APACHE II), plasma MCP-1, and laboratory test results. Plasma MCP-1 was quantified by cytokine test kit (LKTM014B, R&D). Statistical analysis was carried out in SPSS 26.0 and MedCalc 92.1.0 software. RESULTS The 28-day mortality group exhibited higher levels of SOFA, APACHEII, and plasma MCP-1 (all P<0.001), as well as lower levels of albumin, compared to the survival group (P<0.05). The logistic regression analysis findings indicated that SOFA, APACHEII, plasma MCP-1, and SBP are all independent risk factors for 28-day mortality. The area under the curve for SOFA, APACHEII, MCP-1, MCP-1+ SOFA, and MCP-1+APACHEII were 0.845, 0.744, 0.712, 0.879, and 0.822, respectively. MCP-1+SOFA exhibited higher sensitivity than SOFA alone. Furthermore, the assessment values of plasma MCP-1 combined with SOFA were superior to those of APACHE II or plasma MCP-1 (Z₁=2.661, Z₂=3.272, both P<0.01). CONCLUSIONS The findings from this study from a single center support those of previous studies that increased plasma levels of MCP-1 are significantly associated with 28-day mortality in patients with sepsis.

Prognostication of the development of septic complications in children with burn injuries

OBJECTIVE

Aim: To determine the prognostic criteria for the development of septic complications in children with thermal injury.

PATIENTS AND METHODS

Materials and Methods: A single-center retrospective-prospective cohort study included a retrospective analysis of 98 medical histories of children of different ages with severe burns who were treated from 2007 to 2017. A prospective study was conducted among children (n=63) from 1 to 5 years old, who received various degrees severity burn injury, according to an open comparative method in the period from 2018 to 2021.

RESULTS

Results: Indicators of a high risk of developing sepsis were burns by flames of any etiology, damage severity index ≥75 units, total burn surface ≥25 %, deep burn area ≥ 5%. The threshold value of procalcitonin (PCT) ≥ 0.86 ng/ml on the 1st-3rd day and PCT > 0.51 ng/ml on the 7th day of burn disease, had a prognostic value for assessing the probability of sepsis. On the 1st day of hospitalization, the development of sepsis was predicted if the C-reactive protein (CRP) value was higher than 6.98 ng/ml, on the 3rd - the CRP level was above 7.43 ng/ml, on the 7th day - above 7.28 ng/ml.

CONCLUSION

Conclusions: Based on the obtained data, we selected the criteria with the best prognostic characteristics, which allows us to predict and prevent the development of sepsis in the early stages of burn disease in children.

Pediatric Sepsis Diagnosis, Management, and Sub-phenotypes

Sepsis and septic shock are major causes of morbidity, mortality, and health care costs for children worldwide, including >3 million deaths annually and, among survivors, risk for new or worsening functional impairments, including reduced quality of life, new respiratory, nutritional, or technological assistance, and recurrent severe infections. Advances in understanding sepsis pathophysiology highlight a need to update the definition and diagnostic criteria for pediatric sepsis and septic shock, whereas new data support an increasing role for automated screening algorithms and biomarker combinations to assist earlier recognition. Once sepsis or septic shock is suspected, attention to prompt initiation of broad-spectrum empiric antimicrobial therapy, fluid resuscitation, and vasoactive medications remain key components to initial management with several new and ongoing studies offering new insights into how to optimize this approach. Ultimately, a key goal is for screening to encompass as many children as possible at risk for sepsis and trigger early treatment without increasing unnecessary broad-spectrum antibiotics and preventable hospitalizations. Although the role for adjunctive treatment with corticosteroids and other metabolic therapies remains incompletely defined, ongoing studies will soon offer updated guidance for optimal use. Finally, we are increasingly moving toward an era in which precision therapeutics will bring novel strategies to improve outcomes, especially for the subset of children with sepsis-induced multiple organ dysfunction syndrome and sepsis subphenotypes for whom antibiotics, fluid, vasoactive medications, and supportive care remain insufficient.

Evidence from Machine Learning, Diagnostic Hub Genes in Sepsis and Diagnostic Models based on Xgboost Models, Novel Molecular Models for the Diagnosis of Sepsis

BACKGROUND

Systemic multi-organ dysfunction resulting from dysregulated immune responses in the host triggered by microbial infection or other factors is a major cause of death in sepsis, and secretory pathways play an important role in it.

METHODS

GSE57065, GSE65682, GSE145227, and GSE54514 from Gene Expression Omnibus (GEO) were derived for this study. Secretory pathways single sample gene set enrichment analysis (ssGSEA) scores in sepsis and normal samples were exposed. Gene modules associated with secretory pathways were selected by weighted gene coexpression network analysis (WGCNA) for Protein-Protein Interaction Networks (PPI) assessment, and crossover genes in both were evaluated by eXtreme Gradient Boosting (XGBoost) model in feature selection to identify hub genes in sepsis. In addition, we explored the immune cells and signaling pathways regulated by hub genes.

RESULTS

Remarkable dysregulation of secretory pathways was demonstrated in sepsis. The secretory pathways-associated gene modules were intimately involved in cytokine and immune responses in infection. Four crossover genes (CD163, FCER1G, C3AR1, ARG1) were present in WGCNA and PPI, and training in the XGBoost model revealed the best diagnostic performance of these 4 genes, meaning that these genes were the hub genes for sepsis. The 4-hub genes showed a significant negative correlation with T cell activity and a significant positive correlation with inflammatory immune cells. In addition, we found that the 4-hub genes markedly positively regulated INFLAMMATORY RESPONSE, IL6 JAK STAT3 SIGNALING.

CONCLUSION

Based on WGCNA, PPI, and XGBoost models, we identified hub genes that play an important regulatory role in sepsis. We also developed novel molecular models for the diagnosis of sepsis.

ADAR1 protects pulmonary macrophages from sepsis-induced pyroptosis and lung injury through miR-21/A20 signaling

Acute lung injury is a serious complication of sepsis with high morbidity and mortality. Pyroptosis is a proinflammatory form of programmed cell death that leads to immune dysregulation and organ dysfunction during sepsis. We previously found that adenosine deaminase acting on double-stranded RNA 1 (ADAR1) plays regulatory roles in the pathology of sepsis, but the mechanism of ADAR1 in sepsis-induced pyroptosis and lung injury remains unclear. Here, we mainly investigated the regulatory effects and underlying mechanism of ADAR1 in sepsis-induced lung injury and pyroptosis of pulmonary macrophages through RNA sequencing of clinical samples, caecal ligation and puncture (CLP)-induced septic mouse models, and in vitro cellular experiments using RAW264.7 cells with lipopolysaccharide (LPS) stimulation. The results showed that pyroptosis was activated in peripheral blood mononuclear cells (PBMCs) from patients with sepsis. In the CLP-induced septic mouse model, pyroptosis was mainly activated in pulmonary macrophages. LPS-stimulated RAW264.7 cells showed significantly increased activation of the NLRP3 inflammasome. ADAR1 was downregulated in PMBCs of patients with sepsis, and overexpression of ADAR1 alleviated CLP-induced lung injury and NLRP3 inflammasome activation. Mechanistically, the regulatory effects of ADAR1 on macrophage pyroptosis were mediated by the miR-21/A20/NLRP3 signalling cascade. ADAR1 attenuated sepsis-induced lung injury and hindered the activation of pyroptosis in pulmonary macrophages in sepsis through the miR-21/A20/NLRP3 axis. Our study highlights the role of ADAR1 in protecting pulmonary macrophages against pyroptosis and suggests targeting ADAR1/miR-21 signalling as a therapeutic opportunity in sepsis-related lung injury.

Vitexin along with verapamil downregulates efflux pump P-glycoprotein in macrophages and potentiate M1 to M2 switching via TLR4-NF-κB-TNFR2 pathway in lipopolysaccharide treated mice

The lipopolysaccharide, a microbial toxin, is one of the major causative agents of sepsis. P-gp expression and its functions are altered during inflammation. LPS has been known to impair the functions of P-gp, an efflux transporter. But the effect of LPS on P-gp expression in murine peritoneal macrophages is poorly understood. Molecular docking studies reveal that vitexin is a potent substrate and verapamil a potent inhibitor of P-gp. In the present experimental study, the curative potential of vitexin as a fruit component and verapamil treated as a control inhibitor of P-gp was examined in a murine LPS sepsis model. The effects of vitexin and verapamil on P-gp expression in macrophages correlating with changes in macrophage polarization and associated functional responses during LPS induced sepsis were studied. Peritoneal macrophages of LPS (10 mg/kg body weight) challenged mice exhibited elevated levels of H2O2, superoxide, and NO in parallel with lower antioxidant activity. LPS treatment increased P-gp expression through increased TLR4/expression. However, LPS challenged mice treated with vitexin (5 mg/kg body weight) + verapamil (5 mg/kg body weight) showed higher anti-oxidant enzyme activity (SOD, CAT and GRx) resulting in reduced oxidative stress. This combination treatment also elevated TNFR2, concomitant with down-regulation of TLR4, NF-κB and P-gp expression in murine peritoneal macrophages, resulting in a switch from M1 to M2 polarisation of macrophages and reduced inflammatory responses. In conclusion, combined vitexin and verapamil treatment could be used as a promising therapy to regulate P-gp expression and protection against LPS mediated sepsis and inflammatory damages.

Role of LncRNAs in the Pathogenesis of Sepsis and their Clinical Significance

Sepsis is a fatal organ dysfunction caused by the host's uncontrolled response to infection, with high morbidity and mortality. Early diagnosis and intervention are the most effective methods to reduce the mortality due to sepsis. However, there is still a lack of definite biomarkers or intervention targets for the diagnosis, evaluation, prognosis, and treatment of sepsis. Long non-coding RNAs (lncRNAs) are a type of noncoding transcript with a length ranging from 200 to 100,000 nucleotides. LncRNAs mainly locate in the cytoplasm and nucleus and participate in various signaling pathways related to inflammatory reactions and organ dysfunction. Recent studies have reported that lncRNAs are involved in regulating the pathophysiological process of sepsis. Some classical lncRNAs have been confirmed as promising biomarkers to evaluate the severity and prognosis of sepsis. This review summarizes the mechanical studies on lncRNAs in sepsis-induced acute lung, kidney, myocardial, and liver injuries, analyzes the role of lncRNAs in the pathogenesis of sepsis, and explores the possibility of lncRNAs as potential biomarkers and intervention targets for sepsis-induced multiple organ dysfunction.

Game changer or gimmick: inflammatory markers to guide antibiotic treatment decisions in neonatal early-onset sepsis

BACKGROUND

The diagnosis of neonatal early-onset sepsis (EOS) is challenging, and inflammatory markers are widely used to guide decision-making and therapies.

OBJECTIVES

This narrative review presents the current state of knowledge regarding the diagnostic value and potential pitfalls in the interpretation of inflammatory markers for EOS.

SOURCES

PubMed until October 2022 and searched references in identified articles using the search terms: neonatal EOS, biomarker or inflammatory marker, and antibiotic therapy or antibiotic stewardship.

CONTENT

In situations with a high or low probability of sepsis, the measurements of inflammatory markers have no impact on the decision to start or stop antibiotics and are just gimmick, whereas they may be a game changer for neonates with intermediate risk and therefore an unclear situation. There is no single or combination of inflammatory markers that can predict EOS with high probability, allowing us to make decisions regarding the start of antibiotics based only on inflammatory markers. The main reason for the limited accuracy is most probably the numerous noninfectious conditions that influence the levels of inflammatory markers. However, there is evidence that C-reactive protein and procalcitonin have good negative predictive accuracy to rule out sepsis within 24 to 48 hours. Nevertheless, several publications have reported more investigations and prolonged antibiotic treatments with the use of inflammatory markers. Given the limitations of current strategies, using an algorithm with only moderate diagnostic accuracy may have a positive impact, as reported for the EOS calculator and the NeoPInS algorithm.

IMPLICATIONS

As the decision regarding the start of antibiotic therapy is different from the process of stopping antibiotics, the accuracy of inflammatory markers needs to be evaluated separately. Novel machine learning-based algorithms are required to improve accuracy in the diagnosis of EOS. In the future, inflammatory markers included in algorithms may be a game changer reducing bias and noise in the decision-making process.

The identification of novel stroke-related sphingolipid biomarkers using UPLC-MS/MS

BACKGROUND

Stroke is a prominent contributor to global mortality and morbidity, thus necessitating the establishment of dependable diagnostic indicators. The objective of this study was to ascertain metabolites linked to sphingolipid metabolism and assess their viability as diagnostic markers for stroke.

METHODS

Two cohorts, consisting of 56 S patients and 56 healthy volunteers, were incorporated into this investigation. Metabolite data was obtained through the utilization of Ultra Performance Liquid Chromatography and Tandem Mass Spectrometry (UPLC-MS/MS). The mass spectrometry data underwent targeted analysis and quantitative evaluation utilizing the multiple reaction monitoring mode of triple quadrupole mass spectrometry. Various data analysis techniques, including Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA), least absolute shrinkage and selection operator (LASSO) regression, Support Vector Machine (SVM), logistic regression, and Receiver Operating Characteristic (ROC) curves were employed.

RESULTS

A comprehensive analysis detected a total of 129 metabolites related to sphingolipid metabolism, encompassing ceramides, 1-phosphoceramides, phytoceramides, glycosphingolipids, sphingomyelins, and sphingomyelins. The implementation of OPLS-DA analysis revealed significant disparities between individuals with stroke and controls, as it successfully identified 31 metabolites that exhibited significant differential expression between the two groups. Furthermore, functional enrichment analysis indicated the participation of these metabolites in diverse biological processes. Six metabolic markers, namely CerP(d18:1/20:3), CerP(d18:1/18:1), CerP(d18:1/18:0), CerP(d18:1/16:0), SM(d18:1/26:1), and Cer(d18:0/20:0), were successfully validated as potential diagnostic markers for stroke. The utilization of ROC analysis further confirmed their diagnostic potential, while a logistic regression model incorporating these markers demonstrated robust efficacy in distinguishing stroke patients from healthy controls.

CONCLUSION

these identified metabolic markers exhibit clinical significance and hold promise as valuable tools for the diagnosis of stroke.

Diagnostic and prognostic value of MR-pro ADM, procalcitonin, and copeptin in sepsis

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. There is a need for biomarkers that can be used for the diagnosis of sepsis and the early identification of patients at high risk of death. In this study, we aimed to investigate the relationship between Mid-regional pro-adrenomedullin (MR-proADM), procalcitonin (PCT), and copeptin in sepsis. A total of 28 sepsis, 32 septic shock, and 30 control patients were included in our prospective study. Patients' MR-proADM, PCT, and copeptin levels were recorded. Sequential organ failure assessment scores, length of hospital stay, and 30-day mortality were also recorded. These values were compared between the sepsis, septic shock, and control groups. The mean age of all participants was 64.04 ± 15.83 years. In the study, 37 (61.6%) patients were female and 23 (39.3%) were male. There was no statistically significant difference in gender/age between all patient groups and the control group (for all, p > 0.05). We found a significant difference between the survivors and nonsurvivors in terms of MR-proADM, PCT, and copeptin levels. There was a significant difference between the sepsis and septic shock groups in terms of MR-proADM and PCT. A significant correlation was found between the length of hospital stay and MR-proADM and copeptin. MR-proADM, PCT, and copeptin may be useful in the prognosis of sepsis and to predict the length of stay in hospital and mortality.

National consensus survey on management approaches for upper urinary tract obstruction: A comparative analysis of retrograde ureteric stent and percutaneous nephrostomy

To the Editor, Upper urinary tract obstruction (UUTO) is a common scenario in clinical practice, and it is caused by a variety of diseases. Lithiasis, tumours and strictures are some of the principal aetiologies. Multiple factors may influence both the need for decompression of the obstructed collecting system and the urgency of procedure...

Aquaporin Expression and Regulation in Clinical and Experimental Sepsis

Sepsis is an inflammatory disorder caused by the host's dysfunctional response to infection. Septic patients present diverse clinical characteristics, and in the recent years, it has been the main cause of death in intensive care units (ICU). Aquaporins, membrane proteins with a role in water transportation, have been reported to participate in numerous biological processes. Their role in sepsis progression has been studied extensively. This review aims to examine recent literature on aquaporin expression and regulation in clinical sepsis, as well as established experimental models of sepsis. We will present how sepsis affects aquaporin expression at the molecular and protein level. Moreover, we will delve into the importance of aquaporin regulation at transcriptional, post-transcriptional, translational, and post-translational levels in sepsis by presenting data on aquaporin regulation by non-coding RNAs and selected chemical molecules. Finally, we will focus on the importance of aquaporin single-nucleotide polymorphisms in the setting of sepsis.

Plasma Insulin-like Growth Factor-Binding Protein-2 of Critically Ill Patients Is Related to Disease Severity and Survival

Insulin-like growth factor-binding protein (IGFBP)-2 regulates the bioactivity of the anabolic hormone's insulin-like growth factors, which are decreased in sepsis and contribute to the catabolic status of severely ill patients. The circulating levels of IGFBP-2 in critical illness have been rarely studied; therefore, we evaluated IGFBP-2 plasma levels in patients with systemic inflammatory response syndrome (SIRS) or sepsis as well as healthy controls. Our analysis of 157 SIRS/sepsis patients revealed higher plasma IGFBP-2 levels compared to 22 healthy controls. Plasma IGFBP-2 levels correlated positively with procalcitonin but not with C-reactive protein, interleukin-6, or the leukocyte count. Septic shock patients exhibited higher IGFBP-2 levels than those with SIRS. Bacterial or SARS-CoV-2 infection did not influence plasma IGFBP-2 levels. There was no difference in the IGFBP-2 levels between ventilated and non-ventilated SIRS/sepsis patients, and vasopressor therapy did not alter these levels. Dialysis patients had elevated plasma IGFBP-2 levels. Survivors had lower plasma IGFBP-2 levels than non-survivors. In conclusion, our study indicates that plasma IGFBP-2 levels are associated with disease severity, renal failure, and mortality in SIRS/sepsis patients.

Development of early prediction model of in-hospital cardiac arrest based on laboratory parameters

BACKGROUND

In-hospital cardiac arrest (IHCA) is an acute disease with a high fatality rate that burdens individuals, society, and the economy. This study aimed to develop a machine learning (ML) model using routine laboratory parameters to predict the risk of IHCA in rescue-treated patients.

METHODS

This retrospective cohort study examined all rescue-treated patients hospitalized at the First Medical Center of the PLA General Hospital in Beijing, China, from January 2016 to December 2020. Five machine learning algorithms, including support vector machine, random forest, extra trees classifier (ETC), decision tree, and logistic regression algorithms, were trained to develop models for predicting IHCA. We included blood counts, biochemical markers, and coagulation markers in the model development. We validated model performance using fivefold cross-validation and used the SHapley Additive exPlanation (SHAP) for model interpretation.

RESULTS

A total of 11,308 participants were included in the study, of which 7779 patients remained. Among these patients, 1796 (23.09%) cases of IHCA occurred. Among five machine learning models for predicting IHCA, the ETC algorithm exhibited better performance, with an AUC of 0.920, compared with the other four machine learning models in the fivefold cross-validation. The SHAP showed that the top ten factors accounting for cardiac arrest in rescue-treated patients are prothrombin activity, platelets, hemoglobin, N-terminal pro-brain natriuretic peptide, neutrophils, prothrombin time, serum albumin, sodium, activated partial thromboplastin time, and potassium.

CONCLUSIONS

We developed a reliable machine learning-derived model that integrates readily available laboratory parameters to predict IHCA in patients treated with rescue therapy.

Nrf2/PHB2 alleviates mitochondrial damage and protects against Staphylococcus aureus-induced acute lung injury

Staphylococcus aureus (SA) is a major cause of sepsis, leading to acute lung injury (ALI) characterized by inflammation and oxidative stress. However, the role of the Nrf2/PHB2 pathway in SA-induced ALI (SA-ALI) remains unclear. In this study, serum samples were collected from SA-sepsis patients, and a SA-ALI mouse model was established by grouping WT and Nrf2-/- mice after 6 h of intraperitoneal injection. A cell model simulating SA-ALI was developed using lipoteichoic acid (LTA) treatment. The results showed reduced serum Nrf2 levels in SA-sepsis patients, negatively correlated with the severity of ALI. In SA-ALI mice, downregulation of Nrf2 impaired mitochondrial function and exacerbated inflammation-induced ALI. Moreover, PHB2 translocation from mitochondria to the cytoplasm was observed in SA-ALI. The p-Nrf2/total-Nrf2 ratio increased in A549 cells with LTA concentration and treatment duration. Nrf2 overexpression in LTA-treated A549 cells elevated PHB2 content on the inner mitochondrial membrane, preserving genomic integrity, reducing oxidative stress, and inhibiting excessive mitochondrial division. Bioinformatic analysis and dual-luciferase reporter assay confirmed direct binding of Nrf2 to the PHB2 promoter, resulting in increased PHB2 expression. In conclusion, Nrf2 plays a role in alleviating SA-ALI by directly regulating PHB2 transcription and maintaining mitochondrial function in lung cells.

Aspartate Aminotransferase/Platelet Ratio Index Upon Admission Predicts 24-Week Mortality in Patients With HIV-Associated Talaromyces marneffei

Background

A high aspartate aminotransferase/platelet ratio index (APRI) predicts mortality in patients with severe infection. This study aims to assess the potential of APRI as a predictor for mortality in patients with HIV-associated Talaromyces marneffei (HTM).

Methods

Associations between APRI and CD4 count, white blood cell count, C-reactive protein (CRP) level, procalcitonin (PCT) level, and cytokines were assessed in 119 patients. Univariate and multivariate Cox regression models were used to predict APRI on 24-week mortality.

Results

APRI was positively associated with CRP (r = 0.190, P = .039), PCT (r = 0.220, P = .018), interleukin 6 (r = 0.723, P < .001), interleukin 10 (r = 0.416, P = .006), and tumor necrosis factor α (r = 0.575, P < .001) and negatively associated with CD4 count (r = -0.234, P = .011). In total, 20.2% (24/119) of patients died within the 24-week follow-up. The 24-week survival rate was 88.0% for patients with APRI <5.6% and 61.1% for those with APRI ≥5.6 (log-rank P < .001). After adjustment for sex, age, body mass index, and CD4 count, as well as serum levels of hemoglobin, APRI ≥5.6 (adjusted hazard ratio [95% CI]; 3.0 [1.2-7.1], P = .015), PCT ≥1.7 ng/mL (3.7 [1.5-9.6], P = .006), and non-amphotericin B deoxycholate treatment (2.8 [1.2-6.6], P = .018) were independent risk factors for 24-week mortality.

Conclusions

For patients with HTM, APRI is associated with severity and is an independent risk factor for 24-week mortality.