Biomarkers of Neonatal Sepsis: Where We Are and Where We Are Going

The diagnostic accuracy of presepsin for late-onset neonatal sepsis: a multicenter prospective cohort study

BACKGROUND

Antibiotic overtreatment in infants is a significant problem, due to lack of accurate diagnostic tools for late-onset neonatal sepsis (LONS). We aimed to investigate the diagnostic accuracy of presepsin for LONS at initial suspicion.

METHODS

In this multicenter prospective observational cohort study, we consecutively included all term and preterm infants who started on antibiotics empirically for a nosocomial LONS suspicion. Presepsin concentrations were determined at initial LONS suspicion before antibiotic initiation (t = 0), and 12 and 24 h afterwards. Diagnostic accuracy measures for LONS were calculated.

RESULTS

A total of 63 episodes of suspected LONS (32 classified as LONS, including 23 culture-positive and 9 culture-negative episodes) in 50 infants were included. Presepsin concentrations were significantly higher in LONS cases compared with non-LONS at all time-points. The AUC for all LONS cases at t = 0 was 0.77 (95% CI 0.66-0.89) and 0.80 (95% CI 0.67-0.92) for culture-positive LONS cases only.

CONCLUSION

Presepsin seems to have insufficient accuracy as single biomarker to serve as a biomarker for ruling out LONS in infants suspected of LONS. Future larger studies are warranted to validate our findings and to investigate the clinical impact of presepsin, in combination with other biomarkers, as diagnostic tool to facilitate decision-making regarding the initiation of antibiotics, thereby supporting antibiotic stewardship.

IMPACT

Presepsin seems to have insufficient accuracy as single biomarker for the decision to treat or not at initial suspicion of late-onset neonatal sepsis. This is the first prospective observational cohort study on the diagnostic accuracy of presepsin for late-onset neonatal sepsis consecutively recruiting all infants suspected of late-onset neonatal sepsis, minimizing bias. Future larger studies are warranted to investigate the clinical impact of presepsin in facilitating decision-making regarding the initiation of antibiotics in infants, thereby supporting antibiotic stewardship.

Epidemiology and management of infections in critically ill neonates: findings from a cohort study in a Brazilian neonatal intensive care unit

Introduction. Healthcare-associated infections (HAIs) are the leading cause of preventable death in neonatal intensive care units (NICUs), particularly among very low birth weight (VLBW) infants.Hypothesis/Gap Statement: VLBW neonates are at higher risk of HAIs, particularly those caused by Gram-negative bacteria (GNB) and fungi, which can negatively impact their survival and prolong hospitalization.Aim. To determine the risk factors, aetiology, antimicrobial susceptibility and clinical outcomes of HAIs in VLBW neonates in a Brazilian NICU.Methodology. This retrospective cohort study analysed the medical records of VLBW newborns admitted to the NICU from January 2015 to December 2022.Results. Among VLBW neonates, 269/670 (40.1%) developed HAIs and 203/670 (30.3%) developed sepsis. The incidence of HAIs (54.5% vs. 36.2%) and sepsis (49.7% vs. 25%) was higher in neonates weighing less than 750 g. The median birth weight of infected newborns was 960 g, and the median age of infection onset was 16 days. There were 292/456 (64%) infections caused by Gram-positive bacteria, 138/456 (30.3%) by GNB and 26/456 (5.7%) by fungi. Of the isolates, 277/456 (60.7%) were multidrug-resistant. Newborns weighing less than 750 g or infected with GNB and/or fungi had lower survival rates. Previous use of antifungals was the main predictor of infection (P<0.01; odds ratio=4.21). Infections prolonged hospital stay from 25 to 42 days. The mortality rate was 17.6%, with a case lethality rate of 16.4%; 75% of deaths in the infected group were due to sepsis.Conclusion. The high incidence of infection emphasizes the need for infection control and antimicrobial management. Low birth weight is associated with increased risk of infection and decreased survival. The increase in GNB and fungal infections requires prevention and treatment strategies to reduce neonatal morbidity and mortality.

Diagnostic Value of Umbilical Cord Blood Interleukin-6 Level in Premature Infants with Early-Onset Sepsis

OBJECTIVE

Early-onset sepsis (EOS) is a serious, grave, and frequently fatal condition in premature infants. This study aimed to assess the diagnostic value of interleukin-6 (IL-6) levels in umbilical cord blood for identifying EOS in preterm infants.

METHODS

This prospective cohort study was conducted on preterm infants between May 2019 and April 2021. Based on the diagnostic criteria for EOS, the participants were divided into EOS and non-EOS groups. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic efficacy of cord blood IL-6 levels for EOS.

RESULTS

The levels of IL-6 were significantly higher in the EOS group (n = 10) compared to the non-EOS group (n = 178) [617.5 pg/mL (323.3, 1579.8) vs. 49.7 pg/mL (15.8, 142.8), respectively; p = 0.000]. ROC curve analysis demonstrated that a cutoff value of 250.5 pg/mL for cord blood IL-6 yielded a sensitivity of 90%, specificity of 82%, and area under the curve of 0.876, with a confidence interval of 0.753-0.999, indicating its high accuracy as a diagnostic marker for EOS among preterm infants (p < 0.001).

CONCLUSIONS

The detection of IL-6 in the umbilical cord blood offers convenience and exhibits significant diagnostic potential for EOS in preterm infants, thereby providing valuable support for clinical decision-making.

Comparative analysis of inflammatory biomarkers for the diagnosis of neonatal sepsis: IL-6, IL-8, SAA, CRP, and PCT

Neonatal sepsis (NS) is highly likely to cause death; however, early diagnosis of NS is still a great challenge. This study aimed to determine the diagnostic values of IL-6, IL-8, and serum amyloid A (SAA) in NS patients. C-Reactive protein (CRP), procalcitonin (PCT), interleukin (IL)-6, IL-8, and SAA were detected in 120 infants with NS (60 premature infants [NS-PIs] and 60 term infants [NS-TIs]). Sixty noninfected premature infants and 60 noninfected term infants composed the control group. Receiver operating characteristic (ROC) curves were used to determine the sensitivity and specificity of IL-6, IL-8, and SAA alone and in combination with CRP and PCT. The area under the curve (AUC) was calculated to evaluate the diagnostic value. The clinical characteristics of the subjects were recorded. The expression of CRP, PCT, IL-6, IL-8, and SAA was upregulated in patients with NS compared with control subjects. When the SAA cut-off value was 10.18 mg/L, the greatest AUC for the diagnosis of NS-PIs was for SAA (AUC = 0.833, 95% CI 0.762-0.905, P < 0.001). When the CRP cut-off value was 9.562 mg/L, the smallest AUC for the diagnosis of NS-PIs was for CRP (AUC = 0.776, 95% CI 0.684-0.867, P < 0.001). When the IL-8 cut-off value was 52.03 pg/mL, the greatest AUC for the diagnosis of NS-TIs was for IL-8 (0.821). When the IL-8 cut-off value was 52.03 pg/mL, the greatest AUC for the diagnosis of NS-TIs was for IL-8 (AUC = 0.821, 95% CI 0.745-0.898, P < 0.001). When the CRP cut-off value was 13.18 mg/L, the smallest AUC for the diagnosis of NS-TIs was for CRP (AUC = 0.762, 95% CI 0.667-0.857; P < 0.001). Additionally, according to the AUC value, the best combination was SAA and PCT for NS-PI diagnosis, and the best combination was PCT and IL-6 for NS-TI. In conclusion, compared with PCT and CRP, IL-6, IL-8, and SAA are better diagnostic biomarkers. Moreover, PCT combined with SAA is more suitable for diagnosing NS-PIs, and PCT combined with IL-6 is more suitable for diagnosing NS-TIs.

Predictors and outcomes of premature rupture of membranes among pregnant women admitted to a teaching Hospital in Saudi Arabia: a cohort study

BACKGROUND

Premature rupture of the membrane (PROM), refers to rupture of the fetal membranes prior to the onset of regular uterine contractions. When this occurs at term (≥ 37 weeks of gestation), it is classified as PROM, whereas if it occurs before 37 weeks, it is termed preterm premature rupture of membranes (PPROM). PROM and PPROM are linked to adverse outcomes for both mother and newborn.

OBJECTIVES

To investigate the factors associated with PROM and the outcomes of pregnancies complicated with PROM.

METHODS

This was a retrospective cohort study. The participants were divided into three groups; those with PROM, those with PPROM and a control group who had normal onset of membranes rupture. The groups were compared with respect to predictors of PROM (maternal demographic profile, obstetrical history, and comorbidities), in addition to outcomes (postpartum hemorrhage, hospital stay, low APGAR scores, sepsis, low birthweight, preterm rate, and admission to neonatal Intensive care Unit (NICU)). Multivariable logistic regression model was used for predicting risk factors associated with PROM and PPROM.

RESULTS

A total of 1,894 pregnant women were enrolled in the study, 77.6% had normal onset of ruptured membranes, while 382 (20.1%) were diagnosed with a PROM and 43 (2.3%) diagnosed with PPROM. Primiparous mothers were more likely to develop PROM (AOR = 1.56, 95% CI (1.10-2.22)) as compared to multiparous, while obese and overweight mothers were less likely to develop PPROM (AOR = 0.86, 95% CI (0.94 - 0.49)). Significantly more mothers with PPROM were delivered by emergency cesarean Sect. (30.2% vs. 22.9%, P < 0.01), develop chorioamnionitis (4.7% vs. 0.1%, P < 0.01), and stayed in the hospital more than three days (16.3% vs. 2.5%, P < 0.01) compared to the control group. Neonates of mothers who had PPROM were more likely to have low birth weight (35.7% vs. 10.4%, P < 0.01), and NICU admission (67.4% vs. 20.4%, P < 0.01) as compared to the control group. Perinatal death rate was not significantly different between the groups.

CONCLUSION

In this study, nulliparity is a predictor of PROM, while overweight/ obese mothers are less likely to develop PPROM. Despite the relatively low occurrence of PPROM among Saudi women, the condition is associate with increase risk of cesarean section delivery, chorioamnionitis, prolonged hospitalization, and an increase need for neonatal intensive care compare to those with a normal onset of membrane rupture.

Metabolic biomarkers of neonatal sepsis: identification using metabolomics combined with machine learning

Background

Sepsis is a common disease associated with neonatal and infant mortality, and for diagnosis, blood culture is currently the gold standard method, but it has a low positivity rate and requires more than 2 days to develop. Meanwhile, unfortunately, the specific biomarkers for the early and timely diagnosis of sepsis in infants and for the determination of the severity of this disease are lacking in clinical practice.

Methods

Samples from 18 sepsis infants with comorbidities, 25 sepsis infants without comorbidities, and 25 infants with noninfectious diseases were evaluated using a serum metabolomics approach based on liquid chromatography‒mass spectrometry (LC‒MS) technology. Differentially abundant metabolites were screened via multivariate statistical analysis. In addition, least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) analyses were conducted to identify the key metabolites in infants with sepsis and without infections. The random forest algorithm was applied to determine key differentially abundant metabolites between sepsis infants with and without comorbidities. Receiver operating characteristic (ROC) curves were generated for biomarker value testing. Finally, a metabolic pathway analysis was conducted to explore the metabolic and signaling pathways associated with the identified differentially abundant metabolites.

Results

A total of 189 metabolites exhibited significant differences between infectious infants and noninfectious infants, while 137 distinct metabolites exhibited differences between septic infants with and without comorbidities. After screening for the key differentially abundant metabolites using LASSO and SVM-RFE analyses, hexylamine, psychosine sulfate, LysoPC (18:1 (9Z)/0:0), 2,4,6-tribromophenol, and 25-cinnamoyl-vulgaroside were retained for the diagnosis of infant sepsis. ROC curve analysis revealed that the area under the curve (AUC) was 0.9200 for hexylamine, 0.9749 for psychosine sulfate, 0.9684 for LysoPC (18:1 (9Z)/0:0), 0.7405 for 2,4,6-tribromophenol, 0.8893 for 25-cinnamoyl-vulgaroside, and 1.000 for the combination of all metabolites. When the septic infants with comorbidities were compared to those without comorbidities, four endogenous metabolites with the greatest importance were identified using the random forest algorithm, namely, 12-oxo-20-trihydroxy-leukotriene B4, dihydrovaltrate, PA (8:0/12:0), and 2-heptanethiol. The ROC curve analysis of these four key differentially abundant metabolites revealed that the AUC was 1 for all four metabolites. Pathway analysis indicated that phenylalanine, tyrosine, and tryptophan biosynthesis, phenylalanine metabolism, and porphyrin metabolism play important roles in infant sepsis.

Conclusion

Serum metabolite profiles were identified, and machine learning was applied to identify the key differentially abundant metabolites in septic infants with comorbidities, septic infants without comorbidities, and infants without infectious diseases. The findings obtained are expected to facilitate the early diagnosis of sepsis in infants and determine the severity of the disease.

Understanding the Difficulties in Diagnosing Neonatal Sepsis: Assessing the Role of Sepsis Biomarkers

Background

Neonatal sepsis is a serious condition with high rates of morbidity and mortality, caused by the rapid growth of microorganisms that trigger a systemic reaction. Symptoms can range from mild to severe presentations. The causative microorganism is usually transmitted from mothers, especially from the urogenital tract, or can originate from the community or hospital.

Methods

Our retrospective study assessed 121 newborns, including both preterm and term infants, divided into three groups within the first 28 days of life: early-onset sepsis (35), late-onset sepsis (39), and a control group (47). Blood samples and cultures were obtained upon admission or at the onset of sepsis (at 24 and 72 hours). The study aimed to evaluate the limitations of commonly used biomarkers and new markers such as lactate dehydrogenase and ferritin in more accurately diagnosing neonatal sepsis.

Results

Our study revealed a significant difference between the initial and final measures of lactate dehydrogenase (LDH) and ferritin in the early-onset sepsis (EOS) and late-onset sepsis (LOS) groups.

Conclusion

Ferritin and LDH may serve as potential markers associated with systemic response and sepsis in cases of both early and late-onset sepsis. Monitoring these biomarkers can aid in the timely detection and management of sepsis, potentially improving patient outcomes.

Neonatal Sepsis: Aetiology, Pathophysiology, Diagnostic Advances and Management Strategies

Neonatal sepsis, a bloodstream infection in the first 28 days of life, is a leading cause of morbidity and mortality among infants in both developing and developed countries. Additionally, sepsis is distinguished in neonates by unique pathophysiological and presentational factors relating to its development in immature neonatal immune systems. This review focuses on the current understanding of the mechanics and implications of neonatal sepsis, providing a comprehensive overview of the epidemiology, aetiology, pathophysiology, major risk factors, signs and symptoms and recent consensus on the diagnosis and management of both early-onset and late-onset neonatal sepsis. It also includes a discussion on novel biomarkers and upcoming treatment strategies for the condition as well as the potential of COVID-19 infection to progress to sepsis in infants.

Diagnosis and Management of Neonatal Bacterial Sepsis: Current Challenges and Future Perspectives

Sepsis remains the second cause of death among neonates after the pathological consequences of extreme prematurity. In this review we summarized knowledge about pathogens causing early-onset sepsis (EOS) and late-onset sepsis (LOS), the role of perinatal risk factors in determining the EOS risk, and the tools used to reduce unnecessary antibiotics. New molecular assays could improve the accuracy of standard blood cultures, providing the opportunity for a quick and sensitive tool. Different sepsis criteria and biomarkers are available to date, but further research is needed to guide the use of antibiotics according to these tools. Beyond the historical antibiotic regimens in EOS and LOS episodes, antibiotics should be based on the local flora and promptly modulated if specific pathogens are identified. The possibility of an antibiotic lock therapy for central venous catheters should be further investigated. In the near future, artificial intelligence could help us to personalize treatments and reduce the increasing trend of multidrug-resistant bacteria.

Enhancing Early Detection of Sepsis in Neonates through Multimodal Biosignal Integration: A Study of Pulse Oximetry, Near-Infrared Spectroscopy (NIRS), and Skin Temperature Monitoring

Sepsis continues to be challenging to diagnose due to its non-specific clinical signs and symptoms, emphasizing the importance of early detection. Our study aimed to enhance the accuracy of sepsis diagnosis by integrating multimodal monitoring technologies with conventional diagnostic methods. The research included a total of 121 newborns, with 39 cases of late-onset sepsis, 35 cases of early-onset sepsis, and 47 control subjects. Continuous monitoring of biosignals, including pulse oximetry (PO), near-infrared spectroscopy (NIRS), and skin temperature (ST), was conducted. An algorithm was then developed in Python to identify early signs of sepsis. The model demonstrated the capability to detect sepsis 6 to 48 h in advance with an accuracy rate of 87.67 ± 7.42%. Sensitivity and specificity were recorded at 76% and 90%, respectively, with NIRS and ST having the most significant impact on predictive accuracy. Despite the promising results, limitations such as sample size, data variability, and potential biases were noted. These findings highlight the critical role of non-invasive biosensing methods in conjunction with conventional biomarkers and cultures, offering a strong foundation for early sepsis detection and improved neonatal care. Further research should be conducted to validate these results across different clinical settings.

An Overview of Antibiotic Therapy for Early- and Late-Onset Neonatal Sepsis: Current Strategies and Future Prospects

Neonatal sepsis is a clinical syndrome mainly associated with a bacterial infection leading to severe clinical manifestations that could be associated with fatal sequalae. According to the time of onset, neonatal sepsis is categorized as early- (EOS) or late-onset sepsis (LOS). Despite blood culture being the gold standard for diagnosis, it has several limitations, and early diagnosis is not immediate. Consequently, most infants who start empirical antimicrobial therapy do not have an underlying infection. Despite stewardship programs partially reduced this negative trend, in neonatology, antibiotic overuse still persists, and it is associated with several relevant problems, the first of which is the increase in antimicrobial resistance (AMR). Starting with these considerations, we performed a narrative review to summarize the main findings and the future prospects regarding antibiotics use to treat neonatal sepsis. Because of the impact on morbidity and mortality that EOS and LOS entail, it is essential to start an effective and prompt treatment as soon as possible. The use of targeted antibiotics is peremptory as soon as the pathogen in the culture is detected. Although prompt therapy is essential, it should be better assessed whether, when and how to treat neonates with antibiotics, even those at higher risk. Considering that we are certainly in the worrying era defined as the "post-antibiotic era", it is still essential and urgent to define novel strategies for the development of antibacterial compounds with new targets or mechanisms of action. A future strategy could also be to perform well-designed studies to develop innovative algorithms for improving the etiological diagnosis of infection, allowing for more personalized use of the antibiotics to treat EOS and LOS.

Inflammatory biomarkers and physiomarkers of late-onset sepsis and necrotizing enterocolitis in premature infants

Background

Early diagnosis of late-onset sepsis (LOS) and necrotizing enterocolitis (NEC) in very low birth weight (VLBW, <1,500 g) infants is challenging due to non-specific clinical signs. Inflammatory biomarkers increase in response to infection, but non-infectious conditions also cause inflammation. Cardiorespiratory data contain physiological biomarkers, or physiomarkers, of sepsis that may be useful in combination with inflammatory hematologic biomarkers for sepsis diagnosis.

Objectives

To determine whether inflammatory biomarkers measured at the time of LOS or NEC diagnosis differ from times without infection and whether biomarkers correlate with cardiorespiratory sepsis physiomarkers in VLBW infants.

Methods

Remnant plasma sample collection from VLBW infants occurred with blood draws for routine laboratory testing and suspected sepsis. We analyzed 11 inflammatory biomarkers and a pulse oximetry sepsis warning score (POWS). We compared biomarker levels obtained at the time of gram-negative (GN) bacteremia or NEC, gram-positive (GP) bacteremia, negative blood cultures, and no suspected infection.

Results

We analyzed 188 samples in 54 VLBW infants. Several biomarkers were increased at the time of GN LOS or NEC diagnosis compared with all other samples. POWS was higher in patients with LOS and correlated with five biomarkers. IL-6 had 78% specificity at 100% sensitivity to detect GN LOS or NEC and added information to POWS.

Conclusions

Inflammatory plasma biomarkers discriminate sepsis due to GN bacteremia or NEC and correlate with cardiorespiratory physiomarkers.

Biomarkers for Serious Bacterial Infections in Febrile Children

Febrile infections in children are a common cause of presentation to the emergency department (ED). While viral infections are usually self-limiting, sometimes bacterial illnesses may lead to sepsis and severe complications. Inflammatory biomarkers such as C reactive protein (CRP) and procalcitonin are usually the first blood exams performed in the ED to differentiate bacterial and viral infections; nowadays, a better understanding of immunochemical pathways has led to the discovery of new and more specific biomarkers that could play a role in the emergency setting. The aim of this narrative review is to provide the most recent evidence on biomarkers and predictor models, combining them for serious bacterial infection (SBI) diagnosis in febrile children. Literature analysis shows that inflammatory response is a complex mechanism in which many biochemical and immunological factors contribute to the host response in SBI. CRP and procalcitonin still represent the most used biomarkers in the pediatric ED for the diagnosis of SBI. Their sensibility and sensitivity increase when combined, and for this reason, it is reasonable to take them both into consideration in the evaluation of febrile children. The potential of machine learning tools, which represent a real novelty in medical practice, in conjunction with routine clinical and biological information, may improve the accuracy of diagnosis and target therapeutic options in SBI. However, studies on this matter are not yet validated in younger populations, making their relevance in pediatric precision medicine still uncertain. More data from further research are needed to improve clinical practice and decision making using these new technologies.