Paediatric and neonatal sepsis and inflammation

Relationship between thrombocytopenia and prognosis in children with septic shock: a retrospective cohort study

Septic shock is a life-threatening disease worldwide often associated with thrombocytopenia. Platelets play a crucial role in bridging the gap between immunity, coagulation, and endothelial cell activation, potentially influencing the course of the disease. However, there are few studies specifically evaluating the impact of thrombocytopenia on the prognosis of pediatric patients. Therefore, the study investigates effects of early thrombocytopenia in the prognosis of children with septic shock. Pediatric patients with septic shock from 2015 to 2022 were included monocentrically. Thrombocytopenia was defined as a platelet count of <100 × 109/L during the first 24 hours of septic shock onset. The primary outcome was the 28-day mortality. Propensity score matching was used to pair patients with different platelet counts on admission but comparable disease severity. A total of 419 pediatric patients were included in the analysis. Patients with thrombocytopenia had higher 28-day mortality (55.5% vs. 38.7%, p = .005) compared to patients with no thrombocytopenia. Thrombocytopenia was associated with reduced 28-PICU free days (median value, 0 vs. 13 days, p = .003) and 28-ventilator-free (median value, 0 vs. 19 days, p = .001) days. Among thrombocytopenia patients, those with platelet count ≤50 × 109/L had a higher 28-day mortality rate (63.6% vs. 45%, p = .02). Multiple logistic regression showed that elevated lactate (adjusted odds ratio (OR) = 1.11; 95% confidence interval (CI): 1.04-1.17; P <0.001) and white blood cell (WBC) count (OR = 0.97; 95% CI: 0.95-0.99; p = .003) were independent risk factors for the development of thrombocytopenia. Thrombocytopenia group had increased bleeding events, blood product transfusions, and development of organ failure. In Kaplan-Meier survival estimates, survival probabilities at 28 days were greater in patients without thrombocytopenia (p value from the log-rank test, p = .004). There were no significant differences in the type of pathogenic microorganisms and the site of infection between patients with and without thrombocytopenia. In conclusion, thrombocytopenia within 24 hours of shock onset is associated with an increased risk of 28-day mortality in pediatric patients with septic shock.

Antibiogram of Bacteria Isolated from Bloodstream Infection-Suspected Patients at the University of Gondar Comprehensive Specialized Hospital in Northwest Ethiopia: A Retrospective Study

Background

Bacterial bloodstream infections (BSIs) are the leading cause of sepsis-related morbidity and mortality worldwide. The emergence and spread of antimicrobial resistance (AMR) in bacteria is also a growing global concern. As a result, data on bacterial profile and their antibiogram are essential for strategies to contain drug resistance, improve the quality of patient care, and strengthen health systems.

Methods

Retrospective data from bacteriological results of blood samples of BSI-suspected patients from 2018 to 2021 were collected using a data collection sheet. Standard bacteriological techniques were followed during sample collection, culture preparation, bacterial identification, and antibiotic susceptibility testing (AST). We used Epi Info version 7 to enter and clean the data and then exported it to SPSS version 26 for analysis. Logistic regression models were used to measure the association between variables. A p value <0.05 with a 95% confidence interval was considered as statistically significant.

Result

Of the total 2,795 blood culture records, 455 (16.3%) were culture positive for bacteria, with Klebsiella pneumoniae (26%) and Staphylococcus aureus (24.6%) being the leading isolates. The isolates were highly resistant to common antibiotics, with more than 80% of them being resistant to ceftriaxone and penicillin. Moreover, about 43% of isolates were multidrug resistant (MDR), with Klebsiella pneumoniae (65.5%), Acinetobacter species (56.7%), and Citrobacter species (53.8%) being the most common MDR isolates. Age and diagnosis year were significantly associated with the presence of bacterial BSIs (p value <0.05).

Conclusion

Bacterial BSI and AMR were growing concerns in the study area. Bacteremia was more common in children under the age of five, and it decreased as the patient's age increased. The alarming rate of AMR, such as MDR blood isolates, calls for periodic and continuous monitoring of antibiotic usage in the study area.

Predicting community acquired bloodstream infection in infants using full blood count parameters and C-reactive protein; a machine learning study

Early recognition of bloodstream infection (BSI) in infants can be difficult, as symptoms may be non-specific, and culture can take up to 48 h. As a result, many infants receive unneeded antibiotic treatment while awaiting the culture results. In this study, we aimed to develop a model that can reliably identify infants who do not have positive blood cultures (and, by extension, BSI) based on the full blood count (FBC) and C-reactive protein (CRP) values. Several models (i.e. multivariable logistic regression, linear discriminant analysis, K nearest neighbors, support vector machine, random forest model and decision tree) were trained using FBC and CRP values of 2693 infants aged 7 to 60 days with suspected BSI between 2005 and 2022 in a tertiary paediatric hospital in Dublin, Ireland. All models tested showed similar sensitivities (range 47% - 62%) and specificities (range 85%-95%). A trained decision tree and random forest model were applied to the full dataset and to a dataset containing infants with suspected BSI in 2023 and showed good segregation of a low-risk and high-risk group. Negative predictive values for these two models were high for the full dataset (> 99%) and for the 2023 dataset (> 97%), while positive predictive values were low in both dataset (4%-20%).   Conclusion: We identified several models that can predict positive blood cultures in infants with suspected BSI aged 7 to 60 days. Application of these models could prevent administration of antimicrobial treatment and burdensome diagnostics in infants who do not need them. What is Known: • Bloodstream infection (BSI) in infants cause non-specific symptoms and may be difficult to diagnose. • Results of blood cultures can take up to 48 hours. What is New: • Machine learning models can contribute to clinical decision making on BSI in infants while blood culture results are not yet known.

D-dimer as a Useful Biomarker in Early Diagnosis of Neonatal Sepsis: A Single-Center Study From Romania

BACKGROUND

This study evaluates the role of D-dimer in identifying neonatal sepsis and their potential value in clinical decision-making due to challenges in early detection.

METHODOLOGY

A case-control study was conducted on 102 neonates at the Children's Clinical Hospital "Louis Turcanu" in Timisoara, Romania, from October 2018 to July 2023. The participants were divided into two groups: those with neonatal sepsis and those without sepsis.

RESULTS

The study found that neonates with sepsis were more likely to be delivered by cesarean section and had higher rates of premature ruptured membranes compared to those without sepsis. The D-dimer biomarker's predictive value for sepsis was assessed using a receiver operating characteristic (ROC) curve, with an area under the curve (AUC) exceeding 0.982 and an optimum cutoff value of 342 ng/mL. An increase in neonatal D-dimer significantly increases the likelihood of sepsis by 2.7% per unit increase. A value above 250 ng/mL indicates a 127-fold increased likelihood of sepsis. The D-dimer's ability to predict mortality in newborns with sepsis is unsatisfactory, with an AUC of 0.528.

CONCLUSIONS

D-dimer, a potential biomarker of neonatal sepsis, warrants further clinical investigation to enhance diagnostic sensitivity and specificity, demonstrating its potential in conjunction with other sepsis markers.

Immunotherapy in the context of sepsis-induced immunological dysregulation

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

Antimicrobial peptide LL37 and regulatory T cell associated with late-onset sepsis in very preterm infants

Stem cell therapy may prevent late-onset sepsis (LOS) via antimicrobial peptide LL37 secretion and regulatory T cell (Treg) regulation. The early prediction of LOS is still a challenge. This study evaluated whether immunological state of LL37 or Tregs precedes LOS. We firstly analyzed the LL37 level, Treg proportion, and LOS incidence in very preterm infants treated with autologous cord blood mononuclear cells (ACBMNCs) in our previous trial. Then, we constructed a prediction model and built validation cohort. We found ACBMNC intervention reduced the incidence of LOS from 27.3% to 6.9% (p = 0.021). LL37 and Treg abundances were higher in the ACBMNCs group. The nomogram demonstrated that early-life Treg and LL37 characteristics were closely associated with LOS (area under the curve, AUC 0.936), with implications for early prediction and timely clinical management. This composite model was also helpful to evaluate the beneficial effect of ACBMNCs intervention on LOS, thus promoting translational research.

The molecular landscape of sepsis severity in infants: enhanced coagulation, innate immunity, and T cell repression

Introduction

Sepsis remains a major cause of mortality and morbidity in infants. In recent years, several gene marker strategies for the early identification of sepsis have been proposed but only a few have been independently validated for adult cohorts and applicability to infant sepsis remains unclear. Biomarkers to assess disease severity and risks of shock also represent an important unmet need.

Methods

To elucidate characteristics driving sepsis in infants, we assembled a multi-transcriptomic dataset from public microarray datasets originating from five independent studies pertaining to bacterial sepsis in infant < 6-months of age (total n=335). We utilized a COmbat co-normalization strategy to enable comparative evaluation across multiple studies while preserving the relationship between cases and controls.

Results

We found good concordance with only two out of seven of the published adult sepsis gene signatures (accuracy > 80%), highlighting the narrow utility of adult-derived signatures for infant diagnosis. Pseudotime analysis of individual subjects' gene expression profiles showed a continuum of molecular changes forming tight clusters concurrent with disease progression between healthy controls and septic shock cases. In depth gene expression analyses between bacteremia, septic shock, and healthy controls characterized lymphocyte activity, hemostatic processes, and heightened innate immunity during the molecular transition toward a state of shock.

Discussion

Our analysis revealed the presence of multiple significant transcriptomic perturbations that occur during the progression to septic shock in infants that are characterized by late-stage induction of clotting factors, in parallel with a heightened innate immune response and a suppression of adaptive cell functionality.

Neonatal sepsis and cardiovascular dysfunction I: mechanisms and pathophysiology

The highest incidence of sepsis across all age groups occurs in neonates leading to substantial mortality and morbidity. Cardiovascular dysfunction frequently complicates neonatal sepsis including biventricular systolic and/or diastolic dysfunction, vasoregulatory failure, and pulmonary arterial hypertension. The haemodynamic response in neonatal sepsis can be hyperdynamic or hypodynamic and the underlying pathophysiological mechanisms are heterogeneous. The diagnosis and definition of both neonatal sepsis and cardiovascular dysfunction complicating neonatal sepsis are challenging and not consensus-based. Future developments in neonatal sepsis management will be facilitated by common definitions and datasets especially in neonatal cardiovascular optimisation. IMPACT: Cardiovascular dysfunction is common in neonatal sepsis but there is no consensus-based definition, making calculating the incidence and designing clinical trials challenging. Neonatal cardiovascular dysfunction is related to the inflammatory response, which can directly target myocyte function and systemic haemodynamics.

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.

Risk factors for death caused by early onset sepsis in neonates: a retrospective cohort study

OBJECTIVE

To evaluate the association between traditional laboratory findings and death, and to find risk factors for death in infants with early onset sepsis (EOS).

STUDY DESIGN

This was a single-center, case-control, retrospective trial conducted between January 2020 and August 2021. Infants with EOS were enrolled and divided into two groups based on outcome before hospital discharge: non-survivors (Mortality group) and survivors (Survival group).

RESULTS

Out of 556 eligible neonates, there were 38 (6.8%) deaths. After univariate analysis and ROC curve analysis, there were a total of 12 values with significant differences (p < 0.05) between two groups, which included birth weight (BW), weight on admission, gestational age, age on admission, mode of delivery, septic shock, heart failure, respiratory failure, pulmonary hypertension, hypothermia, serum lactic acid, and aspartate aminotransferase (AST). Moreover, after multivariate analysis performed for those 12 values, the binary logistic regression analysis showed that taking death as a reference, the BW (OR = 1.00, 95% CI[1.001, 1.002], p < 0.001), PPHN (OR = 2.60, 95% CI[1.04, 6.52], p > 0.001), septic shock (OR = 6.15, 95% CI [2.52, 15.00], p < 0.001), heart failure (OR = 6.22, 95% CI[0.90, 43.05], p > 0.001), serum lactic acid (OR = 0.82, 95%CI[0.75, 0.90], p < 0.001), and AST (OR = 1.00, 95% CI[0.99, 1.00], p > 0.001) could be regarded as risk factors for death with 94.0% correct predictions.

CONCLUSIONS

The factors affecting the prognosis of EOS in neonates were BW, PPHN, septic shock, heart failure, serum lactic acid, and AST. Timely correction of these modifiable risk factors for death may decrease the mortality of EOS in neonates.

Kaempferitrin alleviates LPS-induced septic acute lung injury in mice through downregulating NF-κB pathway

BACKGROUND

Acute lung injury (ALI) causes severe and uncontrolled pulmonary inflammation and has high morbidity in dying patients.

OBJECTIVE

This study aimed to evaluate the potential function of Kaempferitrin (Kae) and uncover its mechanisms in ALI.

MATERIAL AND METHODS

We evaluated the role of Kae in ALI through the lipopolysaccharide (LPS)-induced histopathological changes, lung wet/dry (W/D) ratio, total bronchoalveolar lavage fluid (BALF) cells count, pulmonary inflammation, and the levels of interleukin (IL)-6, tumor necrosis factor-α (TNF-α), and IL-1β. The effect of Kae on NF-κB signaling pathway was discovered through the protein expression levels of transcription factors p65, p-p65, IκBα, and p-IκBα by Western blot analysis.

RESULTS

The results showed that Kae could improve lung injury by reducing apoptosis, histopathological changes, and lung W/D ratio; more importantly, Kae enhanced the survival of ALI mice. Moreover, Kae relieved inflammation, as it reduced total BALF cells count, and deceased the levels of TNF-α, IL-6, and IL-1β in serum. In addition, Western blot analysis data suggested that Kae could decrease the protein expression levels of transcription factors p65, p-p65, IκB-α, and p-IκB-α, which were promoted by LPS.

CONCLUSION

The results of this study suggested that Kae could relieve LPS-induced ALI in mice and reduce inflammation and apoptosis through NF-κB pathway.

Analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric sepsis by integrating bioinformatics and machine learning

BACKGROUND

Pediatric sepsis is a complicated condition characterized by life-threatening organ failure resulting from a dysregulated host response to infection in children. It is associated with high rates of morbidity and mortality, and rapid detection and administration of antimicrobials have been emphasized. The objective of this study was to evaluate the diagnostic biomarkers of pediatric sepsis and the function of immune cell infiltration in the development of this illness.

METHODS

Three gene expression datasets were available from the Gene Expression Omnibus collection. First, the differentially expressed genes (DEGs) were found with the use of the R program, and then gene set enrichment analysis was carried out. Subsequently, the DEGs were combined with the major module genes chosen using the weighted gene co-expression network. The hub genes were identified by the use of three machine-learning algorithms: random forest, support vector machine-recursive feature elimination, and least absolute shrinkage and selection operator. The receiver operating characteristic curve and nomogram model were used to verify the discrimination and efficacy of the hub genes. In addition, the inflammatory and immune status of pediatric sepsis was assessed using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT). The relationship between the diagnostic markers and infiltrating immune cells was further studied.

RESULTS

Overall, after overlapping key module genes and DEGs, we detected 402 overlapping genes. As pediatric sepsis diagnostic indicators, CYSTM1 (AUC = 0.988), MMP8 (AUC = 0.973), and CD177 (AUC = 0.986) were investigated and demonstrated statistically significant differences (P < 0.05) and diagnostic efficacy in the validation set. As indicated by the immune cell infiltration analysis, multiple immune cells may be involved in the development of pediatric sepsis. Additionally, all diagnostic characteristics may correlate with immune cells to varying degrees.

CONCLUSIONS

The candidate hub genes (CD177, CYSTM1, and MMP8) were identified, and the nomogram was constructed for pediatric sepsis diagnosis. Our study could provide potential peripheral blood diagnostic candidate genes for pediatric sepsis patients.

Lymphocyte to C-Reactive Protein Ratio as an Early Biomarker to Distinguish Sepsis from Pneumonia in Neonates

Background

Neonatal sepsis is an acute and severe disease that seriously threatens the life and health of newborns. Neonates with pneumonia may also have unrecognized neonatal sepsis. Early diagnosis of neonatal sepsis is beneficial for early treatment. This study aimed to evaluate the clinical significance of the lymphocyte-to-C-reactive protein ratio (LCR) as an early biomarker to distinguish sepsis from pneumonia.

Methods

This retrospective study enrolled 1635 neonates with pneumonia from February 2016 to March 2022. Among them, 182 cases were diagnosed with sepsis based on the positive blood culture results. Clinical and laboratory data were extracted from the electronic medical records. LCR was calculated as the ratio of the total lymphocyte count (×109 cells/L) to the C-reactive protein level (mg/L). Binary logistic regression analysis was conducted to evaluate the clinical significance of LCR as an early biomarker in distinguishing sepsis from pneumonia. Receiver operating characteristic (ROC) analysis was performed to assess the diagnostic value of LPCR in sepsis cases. All statistical analyses were conducted using Statistical Product and Service Solutions, version 24.0.

Results

The neonates with pneumonia combined with sepsis had a lower LCR than that of the neonates with pneumonia. Further analysis showed that the prevalence of neonatal pneumonia combined with sepsis was significantly higher in the low-LCR group than in the high-LCR group (20.7% vs 5.5%, P < 001). Binary logistic regression revealed that LCR was an independent risk factor for identifying pneumonia combined with sepsis. The ROC curve analysis revealed that LCR had better power than the lymphocyte count and CRP level individually in diagnosing neonatal pneumonia combined with sepsis (0.72 vs 0.65 vs 0.66, P < 0.001), with 62% sensitivity and 72% specificity.

Conclusion

LCR can be a potential early biomarker in distinguishing neonates with sepsis from those with pneumonia.

Effect of neonatal and adult sepsis on inflammation-related diseases in multiple physiological systems: a Mendelian randomization study

Background

Long-term impact of sepsis on whole body systems is not well investigated. The aim of the study was to explore the potential association of neonatal/adult sepsis with several inflammation-related diseases in multiple physiological systems.

Methods

Instrumental variables for neonatal and adult sepsis were collected from the public genome-wide association studies, which must satisfy the correlation, exclusivity and independence assumptions. Mendelian randomization methods (including random-effect inverse-variance weighted, MR-PRESSO, weighted median and MR-Egger) were used to determine the genetic association of neonatal/adult sepsis with asthma, allergy, rheumatoid arthritis, body mass index/obesity, type 1/type 2 diabetes and intelligence/dementia. Sensitivity analyses were conducted to assess heterogeneity and horizontal pleiotropy. The study was performed by TwoSampleMR in R software.

Results

The inverse-variance weighted method reported that neonatal sepsis was related to the decreased level of body mass index (OR = 0.988, 95%CI = 0.980 ~ 0.997, P = 0.007), and adult sepsis was related to the decreased risk of obesity (OR = 0.785, 95%CI = 0.655 ~ 0.940, P = 0.009). These results were supported by the other Mendelian randomization methods. In addition, the study did not find any association of neonatal/adult sepsis with the other inflammation-related diseases. No heterogeneity and horizontal pleiotropy were found using sensitivity analyses.

Conclusion

Sepsis had the potential to reduce the risk of obesity or body mass index level at a genetic level, both in neonates and in adults.

Vital sign-based detection of sepsis in neonates using machine learning

AIM

Sepsis is a leading cause of morbidity and mortality in neonates. Early diagnosis is key but difficult due to non-specific signs. We investigate the predictive value of machine learning-assisted analysis of non-invasive, high frequency monitoring data and demographic factors to detect neonatal sepsis.

METHODS

Single centre study, including a representative cohort of 325 infants (2866 hospitalisation days). Personalised event timelines including interventions and clinical findings were generated. Time-domain features from heart rate, respiratory rate and oxygen saturation values were calculated and demographic factors included. Sepsis prediction was performed using Naïve Bayes algorithm in a maximum a posteriori framework up to 24 h before clinical sepsis suspicion.

RESULTS

Twenty sepsis cases were identified. Combining multiple vital signs improved algorithm performance compared to heart rate characteristics alone. This enabled a prediction of sepsis with an area under the receiver operating characteristics curve of 0.82, up to 24 h before clinical sepsis suspicion. Moreover, 10 h prior to clinical suspicion, the risk of sepsis increased 150-fold.

CONCLUSION

The present algorithm using non-invasive patient data provides useful predictive value for neonatal sepsis detection. Machine learning-assisted algorithms are promising novel methods that could help individualise patient care and reduce morbidity and mortality.

Imbalanced Inflammatory Responses in Preterm and Term Cord Blood Monocytes and Expansion of the CD14+CD16+ Subset upon Toll-like Receptor Stimulation

Developmentally regulated features of innate immunity are thought to place preterm and term infants at risk of infection and inflammation-related morbidity. Underlying mechanisms are incompletely understood. Differences in monocyte function including toll-like receptor (TLR) expression and signaling have been discussed. Some studies point to generally impaired TLR signaling, others to differences in individual pathways. In the present study, we assessed mRNA and protein expression of pro- and anti-inflammatory cytokines in preterm and term cord blood (CB) monocytes compared with adult controls stimulated ex vivo with Pam3CSK4, zymosan, polyinosinic:polycytidylic acid, lipopolysaccharide, flagellin, and CpG oligonucleotide, which activate the TLR1/2, TLR2/6, TLR3, TLR4, TLR5, and TLR9 pathways, respectively. In parallel, frequencies of monocyte subsets, stimulus-driven TLR expression, and phosphorylation of TLR-associated signaling molecules were analyzed. Independent of stimulus, pro-inflammatory responses of term CB monocytes equaled adult controls. The same held true for preterm CB monocytes-except for lower IL-1β levels. In contrast, CB monocytes released lower amounts of anti-inflammatory IL-10 and IL-1ra, resulting in higher ratios of pro-inflammatory to anti-inflammatory cytokines. Phosphorylation of p65, p38, and ERK1/2 correlated with adult controls. However, stimulated CB samples stood out with higher frequencies of intermediate monocytes (CD14⁺CD16⁺). Both pro-inflammatory net effect and expansion of the intermediate subset were most pronounced upon stimulation with Pam3CSK4 (TLR1/2), zymosan (TR2/6), and lipopolysaccharide (TLR4). Our data demonstrate robust pro-inflammatory and yet attenuated anti-inflammatory responses in preterm and term CB monocytes, along with imbalanced cytokine ratios. Intermediate monocytes, a subset ascribed pro-inflammatory features, might participate in this inflammatory state.

The accuracy of soluble urokinase-type plasminogen activator receptor for the diagnosis of neonatal sepsis: a meta-analysis

Background

Neonatal sepsis is one of the major causes of morbidity and mortality in newborns. However, atypical clinical manifestations and symptoms make the early diagnosis of neonatal sepsis a challenge. Relatively high-serum soluble urokinase-type plasminogen activator receptor (suPAR) has been implicated as a diagnostic biomarker for adult sepsis. Therefore, the meta-analysis is intended to explore the diagnostic value of suPAR for neonatal sepsis.

Methods

The PubMed, Cochrane Library, Embase, Web of Science, China National Knowledge Infrastructure, China Biological Medicine Disk, and Wanfang databases were retrieved from inception to 31 December 2022 to collect diagnostic accuracy studies about suPAR for neonatal sepsis. Two reviewers independently screened the literature, extracted data, and assessed the risk of bias in the included studies using the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) tool. Then, a meta-analysis was performed using Stata 15.0 software.

Results

A total of six articles involving eight studies were included. The results of the meta-analysis showed that the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.89 [95%CI (0.83-0.93)], 0.94 [95%CI (0.77-0.98)], 14 [95%CI (3.5-55.2)], 0.12 [95%CI (0.08-0.18)], and 117 [95%CI (24-567)], respectively. The area under the curve (AUC) of summary receiver operator characteristic (SROC) curves was 0.92 [95%CI (0.90-0.94)]. Sensitivity analysis confirmed the stability of the results, and publication bias was not observed. Fagan's nomogram results demonstrated the clinical availability of the findings.

Conclusion

Current evidence suggests that suPAR has potential diagnostic value for neonatal sepsis. Owing to the limited quality of the included studies, more high-quality studies are needed to verify the above conclusion.

Clinical Value of Serum Interleukin-18 in Neonatal Sepsis Diagnosis and Mortality Prediction

Purpose

Previous studies have demonstrated that interleukin-18 (IL-18) levels were elevated in adult patients with sepsis. However, its role in neonatal sepsis remains unknown. The current research was conducted to assess the clinical value of serum IL-18 level as a candidate biomarker in neonatal sepsis diagnosis and prediction of mortality.

Patients and Methods

From July 2022 to September 2022, we prospectively enrolled 91 septic neonates and 31 non-sepsis neonates in the intensive care unit of neonates at Henan Children's Hospital in Zhengzhou, China. Neonatal peripheral blood serum was collected at admission and levels of serum IL-18 were assessed. Employing multivariate logistic regression analysis, the evaluation of the potential of IL-18 as an independent biomarker for sepsis was executed. Furthermore, employing the receiver operating characteristic (ROC) curve analysis, the diagnostic value of IL-18 in sepsis and the ability of IL-18 in predicting the mortality of neonatal sepsis was measured. The statistical package SPSS 24.0 was employed to conduct all statistical analyses.

Results

Serum IL-18 levels in neonates in the sepsis group were elevated compared to the control group, reaching the highest levels in the non-survival sepsis group (P < 0.001). Correlation analysis exhibited a positive relationship between IL-18 levels and age, body temperature, respiratory rate, and C-reactive protein levels. IL-18 was identified as an independent biomarker in identifying sepsis (OR = 4.747, 95% CI 1.493-15.092, P = 0.008) by multiple logistic regression. ROC curve analysis exhibited that IL-18 was good in identifying neonatal sepsis (area under curve (AUC) = 0.77, 95% CI = 0.68-0.85, P < 0.001) and predicting neonatal mortality (AUC = 0.80, 95% CI = 0.63-0.96, P = 0.003).

Conclusion

IL-18 was a potential biomarker for identifying neonatal sepsis and neonatal mortality prediction.