Diagnostic Challenges and Laboratory Considerations for Pediatric Sepsis

Sepsis Recognition by Electronic Health Record Screening in the Pediatric ICU

BACKGROUND

Early recognition and intervention of sepsis in the pediatric population have been shown to decrease hospital length of stay and mortality rates. Stakeholders within a pediatric intensive care unit (PICU) identified a need to improve sepsis recognition in compliance with the Improving Pediatric Sepsis Outcomes Collaborative recommendations.

PURPOSE

The purpose of this study was to identify appropriate screening variables in an electronic health record (EHR)-embedded sepsis screening tool to improve sepsis recognition in the PICU setting.

METHODS

A retrospective data analysis was conducted to test 3 versions of an EHR sepsis screen including triggers based on vital signs and/or laboratory results.

RESULTS

Of the 3 tested versions, the sepsis screen version that triggered based on both vital signs and laboratory findings showed the most promising results with a sensitivity of 83.3% and a specificity of 76%.

CONCLUSIONS

EHR-embedded sepsis screens that monitor documented variables can identify potential sepsis while avoiding over-triggers.

Importance of lactate/albumin ratio in pediatric nosocomial infection and mortality at different times

Aim: To evaluate the lactate/albumin ratio and its relation to mortality in children with nosocomial infections. Materials & methods: One hundred six children were included in this study. Blood gas and albumin levels were analyzed at the first, 24th and 48th h. Results: The types of detected microbial agents, signs of sepsis, development of septic shock and mortality rates were different. The first-, 24th- and 48th h lactate levels of the children who died were higher than those of the living children, but the albumin levels were lower. The highest area under the curve value for the lactate/albumin ratio was detected at the 24th h. Conclusion: Lactate/albumin ratio can be used to predict mortality in children with nosocomial infections.

The Role of Albumin in the Diagnosis of Neonatal Sepsis Over the Last 11 Years: A Retrospective Study

Background

There are many difficulties and uncertainties in the early diagnosis of neonatal sepsis. The aim of this study was to determine whether albumin (ALB) is useful for the early diagnosis of neonatal sepsis using ALB, C-reactive protein (CRP) and procalcitonin (PCT) together.

Methods

ALB, CRP, PCT and white blood cell (WBC) data from 732 patients with neonatal sepsis and 1317 neonatal infection patients hospitalized in Foshan Maternal and Child Health Hospital from 2011 to 2022 were collected. Receiver operating characteristic (ROC) and logistic regression analyses were performed to assess the diagnostic value of ALB, CRP, PCT and the WBC count for neonatal sepsis. The roles of ALB, CRP, PCT and the WBC count in the diagnosis of neonatal sepsis were analysed by using subject working characteristics (ROC) and areas under the curve (AUCs), and the variables were combined to determine which combination had the best diagnostic efficacy.

Results

In the sepsis group, the ALB, CRP, and PCT levels and the WBC count were significantly higher than those in the infection group (P<0.001). In all infants, the sensitivities and specificities of ALB, CRP, PCT, and WBC count were 0.411, 0.596, 0.483 and 0.411, respectively, and 0.833, 0.846, 0.901 and 0.796, respectively. With a sensitivity of 0.646, a specificity of 0.929, and an AUC of 0.834, the best combination was that of ALB, CRP, and PCT, which was better than that of CRP + PCT, CRP + ALB and PCT + ALB.

Conclusion

In neonatal sepsis, in the absence of blood culture results, the combination of ALB, CRP, and PCT is more reliable than CRP, PCT, or CRP+PCT alone. These results suggest that ALB is a useful inflammatory biomarker for the early diagnosis of neonatal sepsis, and can improve the diagnostic efficiency.

Bioinformatic Analysis and Machine Learning Methods in Neonatal Sepsis: Identification of Biomarkers and Immune Infiltration

The disease neonatal sepsis (NS) poses a serious threat to life, and its pathogenesis remains unclear. Using the Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) were identified and functional enrichment analyses were conducted. Three machine learning algorithms containing the least absolute shrinkage and selection operator (LASSO), support vector machine recursive feature elimination (SVM-RFE), and random forest (RF) were applied to identify the optimal feature genes (OFGs). This study conducted CIBERSORT to present the abundance of immune infiltrates between septic and control neonates and assessed the relationship between OFGs and immune cells. In total, 44 DEGs were discovered between the septic and control newborns. Throughout the enrichment analysis, DEGs were primarily related to inflammatory signaling pathways and immune responses. The OFGs derived from machine learning algorithms were intersected to yield four biomarkers, namely Hexokinase 3 (HK3), Cystatin 7 (CST7), Resistin (RETN), and Glycogenin 1 (GYG1). The potential biomarkers were validated in other datasets and LPS-stimulated HEUVCs. Septic infants showed a higher proportion of neutrophils (p < 0.001), M0 macrophages (p < 0.001), and regulatory T cells (p = 0.004). HK3, CST7, RETN, and GYG1 showed significant correlations with immune cells. Overall, the biomarkers offered promising insights into the molecular mechanisms of immune regulation for the prediction and treatment of NS.

Point-of-care diagnostics for sepsis using clinical biomarkers and microfluidic technology

Sepsis is a life-threatening immune response which is caused by a wide variety of sources and is a leading cause of mortality globally. Rapid diagnosis and appropriate antibiotic treatment are critical for successful patient outcomes; however, current molecular diagnostic techniques are time-consuming, costly and require trained personnel. Additionally, there is a lack of rapid point-of-care (POC) devices available for sepsis detection despite the urgent requirements in emergency departments and low-resource areas. Recent advances have been made toward developing a POC test for early sepsis detection that will be more rapid and accurate compared to conventional techniques. Within this context, this review discusses the use of current and novel biomarkers for early sepsis diagnosis using microfluidics devices for POC testing.

Procalcitonin and Pediatric Traumatic Brain Injury: Differentiating Neuro-Storming From Infection

INTRODUCTION

Recurrent febrile episodes represent a diagnostic challenge in the pediatric traumatic brain injury (TBI) population as they may indicate presence of infection versus sterile neuro-storming. Procalcitonin (PCT) is a promising biomarker used in pediatric sepsis; however, data are limited regarding use in TBI. We hypothesized PCT helps discern neuro-storming from sepsis in children with TBI.

MATERIALS AND METHODS

A single-institution retrospective review (2014-2021) identified pediatric patients (aged 0-18 y) with moderate-to-severe TBI and intensive care unit admission > 2 d. Patients with multiple febrile events who underwent infectious evaluation including cultures and PCT drawn within 48 h of fever were included. Demographics, vital signs, infectious biomarkers including PCT, and culture data were captured. Univariate and multivariate analyses were performed to determine variables associated with culture positive status.

RESULTS

One hundred and fifty six patients were admitted to the intensive care unit with moderate-to-severe TBI during the study period. Eighty five patients (54%) experienced recurrent febrile episodes. Twenty four (28%) met inclusion criteria, undergoing 32 total infectious workups. Twenty one workups were culture-positive (66%) in a total of 18 patients. Median PCT levels were not statistically different between culture-positive and culture-negative workups (P = 0.94). In multivariate modeling, neither PCT [odds ratio 0.89 (confidence interval: 0.75-1.05)] nor temperature [odds ratio 7.34 (confidence interval: 0.95-57.16)] correlated with positive bacterial cultures.

CONCLUSIONS

In this small pilot analysis, recurrent febrile episodes were common and PCT did not correlate with sepsis or neuro-storming in pediatric TBI patients. Prospective protocols are needed to better understand the utility of PCT and identify predictors of bacterial infection to improve early diagnosis of sepsis in this population.

Application of a sepsis flow chip (SFC) assay for the molecular diagnosis of paediatric sepsis

A delay in detecting sepsis pathogens is a problematic issue for determining definitive antibiotic therapy for the causative pathogens. The gold standard method for sepsis is blood culture but this requires 3 days to detect the definitive pathogen. Molecular methods offer rapid identification of pathogens. We evaluated the use of sepsis flow chip (SFC) assay for identifying pathogens from children with sepsis. Blood samples from children with sepsis were collected and incubated in a culture device. Positive samples were subjected to amplification-hybridization using SFC assay and culture. A total of 94 samples from 47 patients were recovered, from which 25 isolates were recovered, including Klebsiella pneumoniae (11) and Staphylococcus epidermidis (6). From 25 positive blood culture bottles subjected to SFC assay, 24 genus/species and 18 resistance genes were detected. The sensitivity, specificity and conformity was 80, 94.2 and 94.68 % respectively. SFC assay offers promise to identify pathogens from positive blood culture in paediatric patients with sepsis and may support the antimicrobial stewardship programme in hospitals.

The evolving value of older biomarkers in the clinical diagnosis of pediatric sepsis

Sepsis remains the leading cause of childhood mortality worldwide. The evolving definition of pediatric sepsis is extrapolated from adult studies. Although lacking formal validation in the pediatric population, this working definition has historically proven its clinical utility. Prompt identification of pediatric sepsis is challenging as clinical picture is often variable. Timely intervention is crucial for optimal outcome, thus biomarkers are utilized to aid in immediate, yet judicious, diagnosis of sepsis. Over time, their use in sepsis has expanded with discovery of newer biomarkers that include genomic bio-signatures. Despite recent scientific advances, there is no biomarker that can accurately diagnose sepsis. Furthermore, older biomarkers are readily available in most institutions while newer biomarkers are not. Hence, the latter's clinical value in pediatric sepsis remains theoretical. Albeit promising, scarce data on newer biomarkers have been extracted from research settings making their clinical value unclear. As interest in newer biomarkers continue to proliferate despite their ambiguous clinical use, the literature on older biomarkers in clinical settings continue to diminish. Thus, revisiting the evolving value of these earliest biomarkers in optimizing pediatric sepsis diagnosis is warranted. This review focuses on the four most readily available biomarkers to bedside clinicians in diagnosing pediatric sepsis. IMPACT: The definition of pediatric sepsis remains an extrapolation from adult studies. Older biomarkers that include C-reactive protein, procalcitonin, ferritin, and lactate are the most readily available biomarkers in most pediatric institutions to aid in the diagnosis of pediatric sepsis. Older biomarkers, although in varying levels of reliability, remain to be useful clinical adjuncts in the diagnosis of pediatric sepsis if used in the appropriate clinical context. C-reactive protein and procalcitonin are more sensitive and specific among these older biomarkers in diagnosing pediatric sepsis although evidence varies in different age groups and clinical scenarios.

Metabolomics in pediatric lower respiratory tract infections and sepsis: a literature review

Lower respiratory tract infections (LRTIs) are a leading cause of morbidity and mortality in children. The ability of healthcare providers to diagnose and prognose LRTIs in the pediatric population remains a challenge, as children can present with similar clinical features regardless of the underlying pathogen or ultimate severity. Metabolomics, the large-scale analysis of metabolites and metabolic pathways offers new tools and insights that may aid in diagnosing and predicting the outcomes of LRTIs in children. This review highlights the latest literature on the clinical utility of metabolomics in providing care for children with bronchiolitis, pneumonia, COVID-19, and sepsis. IMPACT: This article summarizes current metabolomics approaches to diagnosing and predicting the course of pediatric lower respiratory infections. This article highlights the limitations to current metabolomics research and highlights future directions for the field.

Metagenomics by next-generation sequencing (mNGS) in the etiological characterization of neonatal and pediatric sepsis: A systematic review

Introduction

Pediatric and neonatal sepsis is one of the main causes of mortality and morbidity in these age groups. Accurate and early etiological identification is essential for guiding antibiotic treatment, improving survival, and reducing complications and sequelae. Currently, the identification is based on culture-dependent methods, which has many limitations for its use in clinical practice, and obtaining its results is delayed. Next-generation sequencing enables rapid, accurate, and unbiased identification of multiple microorganisms in biological samples at the same time. The objective of this study was to characterize the etiology of neonatal and pediatric sepsis by metagenomic techniques.

Methods

A systematic review of the literature was carried out using the PRISMA-2020 guide. Observational, descriptive, and case report studies on pediatric patients were included, with a diagnostic evaluation by clinical criteria of sepsis based on the systemic inflammatory response, in sterile and non-sterile biofluid samples. The risk of bias assessment of the observational studies was carried out with the STROBE-metagenomics instrument and the CARE checklist for case reports.

Results and Discussion

Five studies with a total of 462 patients were included. Due to the data obtained from the studies, it was not possible to perform a quantitative synthesis (meta-analysis). Based on the data from the included studies, the result identified that mNGS improves the etiological identification in neonatal and pediatric sepsis, especially in the context of negative cultures and in the identification of unusual microorganisms (bacteria that are difficult to grow in culture, viruses, fungi, and parasites). The number of investigations is currently limited, and the studies are at high risk of bias. Further research using this technology would have the potential to improve the rational use of antibiotics.

Evaluation Value and Clinical Significance of Cardiac Troponin Level and Pediatric Sequential Organ Failure Score in the Definition of Sepsis 3.0 in Critically Ill Children

Objective

A case-control study was conducted to explore the value and clinical significance of troponin level and pediatric sequential organ failure score in the evaluation of sepsis 3.0 definition in critically ill children.

Methods

180 children with sepsis who were admitted to the ICU from March 2019 to June 2021 were enrolled in our hospital as the research objects. In addition, 100 children with general infection did not meet the diagnostic criteria of systemic inflammatory response syndrome (SIRS) as controls. The creatine kinase MB (CK-MB) and cardiac troponin I (cTnI) data at the 1st and 24-72 h after admission to pediatric intensive care unit (PICU) were enrolled as the observation indexes of myocardial enzymology. In the meantime, the relevant literature was reviewed to obtain the indicators related to sepsis death. The data of the first examination in the medical history data were enrolled for analysis. According to the definition of sepsis 3.0 in critically ill children, they were assigned into sepsis and nonsepsis group. According to the survival outcome of discharge and 30 days after discharge, the patients were assigned into the death subgroup and survival subgroup and were assigned into the sequential organ failure assessment (SOFA) score ≥ 2 subgroup and< 2 subgroup according to SOFA score. COX proportional hazard regression was used to analyze the relationship between CK-MB, cTnI, and SOFA scores and prognosis. ROC curve was adopted to analyze the value of CK-MB, cTnI, and SOFA scores in the evaluation of critical sepsis in children.

Results

Univariate analysis indicated that the prognosis of children with sepsis was correlated with abnormal levels of CK-MB and cTnI, SOFA score, oxygenation index < 200, mean arterial pressure, and Glasgow coma scale (GCS), and the difference was statistically significant (P < 0.05). The results of COX regression analysis indicated that the variables that were remarkably associated with death from sepsis in children were CK-MB, elevated cTnI levels, and SOFA score ≥ 2, and serum cTnI and/or CK-MB levels and SOFA score were remarkably higher correlation (r = 0.453, P < 0.05). In terms of the myocardial enzyme levels in the sepsis group and the nonsepsis group, the levels of CK-MB and (or) cTnI augmented in 121/180 cases (67.22%) in the sepsis group and in 19/100 cases (19.00%) in the nonsepsis group. The levels of CK-MB and (or) cTnI were augmented, and the difference was statistically significant (P < 0.05). The levels of CK-MB and cTnI in the sepsis group at admission to ICU and 24 to 72 hours after admission were remarkably higher compared to the nonsepsis group. The levels of CK-MB and cTnI at 24-72 h were higher compared to ICU. The myocardial enzyme levels of different SOFA scores and survival outcome subgroups in the sepsis group were compared. The subgroup with SFOA score ≥ 2 points had remarkably higher levels of CK-MB and (or) cTnI than the subgroup with <2 points. The survival subgroup of CK-MB and cTnI level was remarkably higher compared to the death subgroup, the CK-MB and cTnI levels in each subgroup at 224-72 hours were remarkably higher compared to the ICU, and the difference was statistically significant (P < 0.05). Kaplan-Meier method and log-rank test indicated that the survival rates of groups 1 to 4 at 30 days were 33.23%, 78.71%, 40.03%, and 100.00%, respectively. The average survival time and their 95% CI were 12.82 d (10.52~ 16.26 d), 22.34 d (18.76~ 25.81 d), 14.65 d (11.62~ 16.38 d), and 30 d (30.00~ 30.00 d), respectively. Pairwise comparison indicated that the survival time of children in group 1 was the shortest, and that in group 4 was the longest. The results of ROC curve research showed that the CK-MB, cTnI, and SOFA scores and AUC for the combination test were 0.778 (95% CI 0.642–0.914), 0.736 (95% CI 0.602–0.890), 0.848 (95% CI 0.733–0.963), and 0.934 (95% CI 0.854–0.999), respectively. The AUC of combined diagnosis was remarkably higher compared to single factor prediction, and the difference was statistically significant (P < 0.05). Predictive value showed the joint test > SOFA score > CK − MB > cTnI.

Conclusion

Troponin level and pediatric SOFA score can be adopted as effective indicators to assess the severity and prognosis of patients with sepsis and can guide the formulation of a reasonable treatment plan.

Biomarker combinations in predicting sepsis in hospitalized children with fever

Sepsis is among the leading causes of critical illness worldwide. It includes physiologic, pathologic, and biochemical abnormalities, induced by infection. Novel methods for recognizing a dysregulated inflammatory response and predicting associated mortality must be developed. Our aim was to investigate biomarkers that characterize a pro-inflammatory and anti-inflammatory response in patients with fever by comparing predictive validity for sepsis. 165 patients with fever were enrolled in this study, 55 of them had sepsis according to pSOFA criteria. All patients had blood samples drawn at the time of inclusion and after 24 h. CRP, PCT and also IL-6, IL-8 and sFAS levels were significantly higher in patients with sepsis. The AUC of CRP to predict sepsis was 0.799, all the other biomarkers had AUC's lower than that. Cytokines, when used as a single marker, did not show a significant diagnostic performance We analyzed various models of biomarker combinations. CRP combined with sFAS showed increase in sensitivity in predicting sepsis (88% vs. 83%). The highest AUC was achieved, when CRP, IL-6, sFAS and sVCAM-1 markers were combined 0.830 (95% CI 0.762-0.884) with a sensitivity of 70% and specificity of 84%. vs. 0.799 for CRP alone.

Association of PAI-1 4G/5G and ACE I/D Polymorphisms with Susceptibility to Pediatric Sepsis: Evidence from a Meta-Analysis

BackgroundSeveral studies have investigated the role of PAI-1 4G/5G and ACE I/D polymorphisms in the etiology of pediatric sepsis, but the results are inconsistent. We performed a meta-analysis to assess for any associations. Methods: A comprehensive literature search on PubMed, web of science, and CNKI database was conducted up to April 15, 2020. Results: There were twelve case-control studies involving seven studies with 860 cases and 1144 controls on PA-1 4G/5G and five studies with 1602 cases and 1585 controls on ACE I/D. PAI-1 4G/5G and ACE I/D polymorphisms were associated with an increased risk of pediatric sepsis in the global population. Stratified analysis by ethnicity showed a significant association in the Caucasians children. Conclusions: The meta-analysis suggests that the PAI-1 4G/5G and ACE I/D polymorphisms may be risk factors for development of pediatric sepsis in the global population.

Identification of potential biomarkers and immune infiltration in pediatric sepsis via multiple-microarray analysis

Immune adjustment has become a sepsis occurring in the development of an important mechanism that cannot be ignored. This article from the perspective of immune infiltration of pediatric sepsis screening markers, and promote the understanding of disease mechanisms. Bioinformatics integrated six data sets of pediatric sepsis by using the surrogate variable analysis package and then analyzed differentially expressed genes (DEGs), immune infiltration and weighted gene co-expression network analysis of characteristics (WGCNA) of immune infiltration between pediatric sepsis and the control. Common genes of WGCNA and DEGs were used to functional annotation, pathway enrichment analysis and protein-protein interaction network. Support vector machine (SVM), least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression were used to confirm the key genes for the diagnosis of pediatric sepsis. Receiver operating characteristic (ROC) curve, C index, principal component analysis (PCA) and GiViTi calibration band were used to evaluate the diagnostic performance of key genes. Decision curve analysis (DCA) was used to evaluate the clinical application value of key genes. Lastly, the correlation between key genes and immune cells was analyze. NK cells Resting and NK cell activated in pediatric sepsis during immune infiltration were significantly lower than those in the control group, while M1 Macrophages were higher than those in the control group. ROC, C-index, PCA, GiViTi calibration band and DCA indicated that MCEMP1, CD177, MMP8 and OLFM4 had high diagnostic performance for pediatric sepsis. There is a negative correlation between 4 key genes and NK cells resting, NK cells activated. Except for MCEMP1, the other 3 genes were positively correlated with M1 Macrophages. This study revealed differences in immune responses in pediatric sepsis and identified four key genes as potential biomarkers. Pediatric sepsis in pathology maybe understood better by learning about how it develops.

Transcript host-RNA signatures to discriminate bacterial and viral infections in febrile children

Traditional laboratory markers, such as white blood cell count, C-reactive protein, and procalcitonin, failed to discriminate viral and bacterial infections in children. The lack of an accurate diagnostic test has a negative impact on child's care, limiting the ability of early diagnosis and appropriate management of children. This, on the one hand, may lead to delayed recognition of sepsis and severe bacterial infections, which still represent the leading causes of child morbidity and mortality. On the other hand, this may lead to overuse of empiric antibiotic therapies, particularly for specific subgroups of patients, such as infants younger than 90 days of life or neutropenic patients. This approach has an adverse effect on costs, antibiotic resistance, and pediatric microbiota. Transcript host-RNA signatures are a new tool used to differentiate viral from bacterial infections by analyzing the transcriptional biosignatures of RNA in host leukocytes. In this systematic review, we evaluate the efficacy and the possible application of this new diagnostic method in febrile children, along with challenges in its implementation. Our review support the growing evidence that the application of these new tools can improve the characterization of the spectrum of bacterial and viral infections and optimize the use of antibiotics in children. IMPACT: Transcript host RNA signatures may allow to better characterize the spectrum of viral, bacterial, and inflammatory illnesses in febrile children and can be used with traditional diagnostic methods to determine if and when to start antibiotic therapy. This is the first review on the use of transcript RNA signatures in febrile children to distinguish viral from bacterial infections. Our review identified a wide variability of target populations and gold standards used to define sepsis and SBIs, limiting the generalization of our findings.

Procalcitonin Use: Variation Across Hospitals and Trends Over Time

OBJECTIVES

Procalcitonin (PCT) is a relatively novel biomarker that may be superior to C-reactive protein (CRP) in identifying bacterial infection. PCT use in pediatric hospitals is relatively unknown. We aimed to evaluate PCT and CRP use, describe PCT testing variability across children's hospitals, and compare temporal rates of PCT and CRP testing for patients admitted with pneumonia, sepsis, or fever in young infants.

METHODS

In this multicenter cohort study, we identified children ≤18 years old hospitalized from 2014-2018 with pneumonia, sepsis, or fever in infants <2 months by using the Pediatric Health Information System. To determine use, we evaluated the proportion of encounters with PCT or CRP testing from 2017-2018. We generated heat maps to describe PCT use across hospitals. We also compared PCT and CRP rates over time from 2014 to 2018.

RESULTS

From 2017-2018, PCT testing occurred in 3988 of 34c231 (12%) hospitalizations. Febrile infants had the highest PCT testing proportion (18%), followed by sepsis (15%) and pneumonia (9%). There was across-hospital variability in PCT testing, particularly for febrile infants. Over time, the odds of PCT testing increased at a significantly greater rate than that of CRP.

CONCLUSIONS

Despite limited guideline recommendations for PCT testing during the study period, PCT use increased over time with across-hospital variability. For pneumonia and sepsis, given the importance of high-value care, we need to understand the impact of PCT on patient outcomes. With recent guidelines recommending PCT in the evaluation of febrile infants, we identified baseline testing behaviors for future studies on guideline impact.

Metabolic responses in neonatal sepsis-A systematic review of human metabolomic studies

AIM

To systematically review human metabolomic studies investigating metabolic responses in septic neonates.

METHODS

A systematic literature search was performed in the databases MEDLINE, EMBASE and Cochrane library up to the 1st of January 2021. We included studies that assessed neonatal sepsis and the following outcomes; (1) change in the metabolism compared to healthy neonates and/or (2) metabolomics compared to traditional diagnostic tools of neonatal sepsis. The screened abstracts were independently considered for eligibility by two researchers.

PROSPERO ID

CRD42020164454.

RESULTS

The search identified in total 762 articles. Fifteen articles were assessed for eligibility. Four studies were included, with totally 78 neonates. The studies used different diagnostic criteria and had between 1 and 16 sepsis cases. All studies with bacterial sepsis found alterations in the glucose and lactate metabolism, reflecting possible redistribution of glucose consumption from mitochondrial oxidative phosphorylation to the lactate and pentose phosphate pathway. We also found signs of increased oxidative stress and fatty acid oxidation in sepsis cases.

CONCLUSION

We found signs of metabolomic signatures in neonatal sepsis. This may lead to better understanding of sepsis pathophysiology and detection of new candidate biomarkers. Results should be validated in large-scale multicentre studies.

Cell-free hemoglobin is a marker of systemic inflammation in mouse models of sepsis: a Raman spectroscopic study

Sepsis is a life-threatening condition caused by heightened host immune responses post infection. Despite intensive research, most of the existing diagnostic methods remain non-specific, labour-intensive, time-consuming or are not sensitive enough for rapid and timely diagnosis of the onset and progression of sepsis. The present work was undertaken to explore the potential of Raman spectroscopy to identify the biomarkers of sepsis in a label-free and minimally invasive manner using different mouse models of inflammation. The sera of BALB/c mice infected with Salmonella Typhimurium reveal extensive hemolysis, as indicated by the Raman bands that are characteristic of the porphyrin ring of hemoglobin (668, 743, 1050, 1253 and 1397 cm-1) which increase in a kinetic manner. These markers are also observed in a lipopolysaccharide-induced endotoxic shock model, but not in a thioglycollate-induced sterile peritonitis model. These data demonstrate that hemolysis is a signature of systemic, but not localised, inflammation. To further validate our observations, sepsis was induced in the nitric oxide synthase 2 (Nos2-/-) deficient strain which is more sensitive to infection. Interestingly, Nos2-/- mice exhibit a higher degree of hemolysis than C57BL/6 mice. Sepsis-induced hemolysis was also confirmed using resonance Raman spectroscopy with 442 nm excitation which demonstrated a pronounced increase in the resonant Raman bands at 670 and 1350 cm-1 in sera of the infected mice. This is the first study to identify inflammation-induced hemolysis in mouse models of sepsis using Raman spectral signatures for hemoglobin. The possible implications of this method in detecting hemolysis in different inflammatory pathologies, such as the ongoing COVID-19 pandemic, are discussed.

Relevance of Biomarkers Currently in Use or Research for Practical Diagnosis Approach of Neonatal Early-Onset Sepsis

Neonatal early-onset sepsis (EOS) is defined as an invasive infection that occurs in the first 72 h of life. The incidence of EOS varies from 0.5–2% live births in developed countries, up to 9.8% live births in low resource settings, generating a high mortality rate, especially in extremely low birth weight neonates. Clinical signs are nonspecific, leading to a late diagnosis and high mortality. Currently, there are several markers used for sepsis evaluation, such as hematological indices, acute phase reactants, cytokines, which by themselves do not show acceptable sensitivity and specificity for the diagnosis of EOS in neonates. Newer and more selective markers have surfaced recently, such as presepsin and endocan, but they are currently only in the experimental research stages. This comprehensive review article is based on the role of biomarkers currently in use or in the research phase from a basic, translational, and clinical viewpoint that helps us to improve the quality of neonatal early-onset sepsis diagnosis and management.

Diagnostic potential of a gradient boosting-based model for detecting pediatric sepsis

Pediatric sepsis is a major cause of mortality of children worldwide. However, there is still a lack of easy-to-use predictive tools that can accurately diagnose sepsis in children. This study aimed to develop an optimal gene model for the diagnosis of pediatric sepsis using statistics and machine learning approaches. Combining gene expression profiles from a training cohort of 364 pediatric samples with a Least Absolute Shrinkage and Selection Operator analysis produced eighteen genes as diagnostic markers. With the implementation of a Gradient Boosting algorithm, a model designated PEDSEPS-GBM, that aggregated these markers was developed with optimal performance for the diagnosis of pediatric samples in the validation and two independent cohorts. Moreover, a web calculator with a user-friendly interface was established for PEDSEPS-GBM. This study presents a diagnostic model that holds great potential for the detection of pediatric sepsis, and demonstrates the biologic and clinical relevance of this model.

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening condition, called Sepsis. Currently, therapeutic protocols through timely antibiotic resuscitation strategies play an important role to fight against the adverse conditions and improve survival. Therefore, timing, and more specifically early diagnosis of the illness, is crucially important for an effective treatment. Studies have indicated that vital signals such as heart rate variability (HRV) could provide potential prognostic biological markers that can help with early detection of sepsis before it is clinically diagnosed through its actual symptoms. Therefore, this study employs neonatal and pediatric electrocardiogram (ECG) to extract 52 hourly sets of linear and non-linear features from the HRV, starting from 24 hours prior to the clinical diagnosis of sepsis in patients with positive blood cultures (n=14). Similar sets of features were also obtained from a non-sepsis control group to create an evaluation benchmark (n=14).In particular, this study initially demonstrates how the variations within the 24 hours values of specific HRV featuresets could effectively reveal prognostic information about the evolution of sepsis, prior to the actual clinical diagnosis. Moreover, this study demonstrates that differences in the values of a particular set of features at 22 hours before the actual clinical diagnosis/symptoms can be reliably used to train a convolutional neural network for automatic classification between the individuals in the sepsis and non-sepsis groups with 88.89±7.86% accuracy.Clinical relevance- Results suggest potential early diagnosis of sepsis through real-time automatic classification of HRV features as prognostic indicators in clinical ECG recordings.

Potential Prognostic Markers in the Heart Rate Variability Features for Early Diagnosis of Sepsis in the Pediatric Intensive Care Unit using Convolutional Neural Network Classifiers

Blood infection due to different circumstances could immediately develop to an extreme body reaction that leads to a serious life-threatening condition, called Sepsis. Currently, therapeutic protocols through timely antibiotic resuscitation strategies play an important role to fight against the adverse conditions and improve survival. Therefore, timing, and more specifically early diagnosis of the illness, is crucially important for an effective treatment. Studies have indicated that vital signals such as heart rate variability (HRV) could provide potential prognostic biological markers that can help with early detection of sepsis before it is clinically diagnosed through its actual symptoms. Therefore, this study employs neonatal and pediatric electrocardiogram (ECG) to extract 52 hourly sets of linear and non-linear features from the HRV, starting from 24 hours prior to the clinical diagnosis of sepsis in patients with positive blood cultures (n=14). Similar sets of features were also obtained from a non-sepsis control group to create an evaluation benchmark (n=14).In particular, this study initially demonstrates how the variations within the 24 hours values of specific HRV feature-sets could effectively reveal prognostic information about the evolution of sepsis, prior to the actual clinical diagnosis. Moreover, this study demonstrates that differences in the values of a particular set of features at 22 hours before the actual clinical diagnosis/symptoms can be reliably used to train a convolutional neural network for automatic classification between the individuals in the sepsis and non-sepsis groups with 88.89±7.86% accuracy.

Relationship Between Resistin Levels and Sepsis Among Children Under 12 Years of Age: A Case Control Study

Objective: The aim of this study was to investigate the level of resistin in children with and without sepsis hospitalized in the pediatric intensive care unit (PICU) and compare them to levels in healthy subjects in order to determine the trend of resistin levels in children in PICUs and also to identify the cut-off values for positive sepsis. Methods: This was a case-control study conducted in 2014 at a children's hospital in Tabriz, Iran. Three groups were investigated, a case group comprised of patients with sepsis admitted to PICU and two control groups; one made up of patients admitted to PICU without sepsis and the other of healthy children. Variables included demographic, anthropometric (growth metric percentile), and clinical factors. Results: Patients were randomized into control group A (n = 12, 48%), control group B (n = 11, 44%), and the sepsis group (n = 24, 47.1%). The difference in the means of resistin levels was significant on the first, fourth, and seventh days (P < 0.0001) in the case and control group A. Means comparisons in the case and control group B revealed significant differences on the fourth and seventh day (P = 0.005 and P < 0.0001, respectively) but not on the first day (P = 0.246). The trend of resistin levels increased in the septic group (F Huynh-Feldt = 37.83, P < 0.0001). The diagnostic accuracy of resistin level was high for discriminating sepsis (area under the receiver operating characteristic curve [AUC] 0.864 [SE = 0.41]). The sensitivity was 0.824 and specificity 0.72 with a cut-off point of 5.2 ng/ml on the first day. Conclusion: In the present study, resistin level can be used as an indicator of sepsis in children admitted to PICU. However, the cut-off point based upon when a prediction could be made is different and is dependent on a variety of factors, such as control group and number of days since the first signs of sepsis.