Using newborn screening analytes to identify cases of neonatal sepsis

Effect of temperature on presepsin pre-analytical stability in biological fluids of preterm and term newborns

OBJECTIVES

Thermostability is one of the pre-requisites for the reliability of analytes in clinical practice and biomedical research. Although presepsin represents a promising new biomarker for the early diagnosis of sepsis in newborns, data on its stability under different storage conditions are lacking. We aimed to investigate presepsin thermostability in blood, urine and saliva samples after thawing at 4 predetermined monitoring time-points in a cohort of preterm and term infants.

METHODS

We conducted an observational study, where each case served as its own control, in 24 preterm and term infants. Blood, urine and saliva samples were stored at -80 °C for 18 months, and presepsin measured in different biological fluids at thawing (T0), 24 (T1), 48 (T2) and at 72 (T3) hours after thawing.

RESULTS

No significant differences (p>0.05, for all) in presepsin levels were observed at T0-T3 in the different biological fluids. Furthermore, no differences at T0-T3 were observed in presepsin levels between blood and saliva fluids, whilst urine levels were significantly higher (p<0.05, for all) than blood and saliva at T0-T3.

CONCLUSIONS

Results on presepsin pre-analytical thermo-stability in different biological fluids after long-term refrigeration support the reliability of this biomarker in the diagnosis and monitoring of perinatal sepsis.

Newborn screen metabolic panels reflect the impact of common disorders of pregnancy

BACKGROUND

Hypertensive disorders of pregnancy and maternal diabetes profoundly affect fetal and newborn growth, yet disturbances in intermediate metabolism and relevant mediators of fetal growth alterations remain poorly defined. We sought to determine whether there are distinct newborn screen metabolic patterns among newborns affected by maternal hypertensive disorders or diabetes in utero.

METHODS

A retrospective observational study investigating distinct newborn screen metabolites in conjunction with data linked to birth and hospitalization records in the state of California between 2005 and 2010.

RESULTS

A total of 41,333 maternal-infant dyads were included. Infants of diabetic mothers demonstrated associations with short-chain acylcarnitines and free carnitine. Infants born to mothers with preeclampsia with severe features and chronic hypertension with superimposed preeclampsia had alterations in acetylcarnitine, free carnitine, and ornithine levels. These results were further accentuated by size for gestational age designations.

CONCLUSIONS

Infants of diabetic mothers demonstrate metabolic signs of incomplete beta oxidation and altered lipid metabolism. Infants of mothers with hypertensive disorders of pregnancy carry analyte signals that may reflect oxidative stress via altered nitric oxide signaling. The newborn screen analyte composition is influenced by the presence of these maternal conditions and is further associated with the newborn size designation at birth.

IMPACT

Substantial differences in newborn screen analyte profiles were present based on the presence or absence of maternal diabetes or hypertensive disorder of pregnancy and this finding was further influenced by the newborn size designation at birth. The metabolic health of the newborn can be examined using the newborn screen and is heavily impacted by the condition of the mother during pregnancy. Utilizing the newborn screen to identify newborns affected by common conditions of pregnancy may help relate an infant's underlying biological disposition with their clinical phenotype allowing for greater risk stratification and intervention.

Prediction modelling in the early detection of neonatal sepsis

BACKGROUND

Prediction modelling can greatly assist the health-care professionals in the management of diseases, thus sparking interest in neonatal sepsis diagnosis. The main objective of the study was to provide a complete picture of performance of prediction models for early detection of neonatal sepsis.

METHODS

PubMed, Scopus, CINAHL databases were searched and articles which used various prediction modelling measures for the early detection of neonatal sepsis were comprehended. Data extraction was carried out based on Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies checklist. Extricate data consisted of objective, study design, patient characteristics, type of statistical model, predictors, outcome, sample size and location. Prediction model Risk of Bias Assessment Tool was applied to gauge the risk of bias of the articles.

RESULTS

An aggregate of ten studies were included in the review among which eight studies had applied logistic regression to build a prediction model, while the remaining two had applied artificial intelligence. Potential predictors like neonatal fever, birth weight, foetal morbidity and gender, cervicovaginitis and maternal age were identified for the early detection of neonatal sepsis. Moreover, birth weight, endotracheal intubation, thyroid hypofunction and umbilical venous catheter were promising factors for predicting late-onset sepsis; while gestational age, intrapartum temperature and antibiotics treatment were utilised as budding prognosticators for early-onset sepsis detection.

CONCLUSION

Prediction modelling approaches were able to recognise promising maternal, neonatal and laboratory predictors in the rapid detection of early and late neonatal sepsis and thus, can be considered as a novel way for clinician decision-making towards the disease diagnosis if not used alone, in the years to come.

Assessment of hospitalization costs and its determinants in infants with clinical severe infection at a public tertiary hospital in Nepal

Sepsis, an important and preventable cause of death in the newborn, is associated with high out of pocket hospitalization costs for the parents/guardians. The government of Nepal’s Free Newborn Care (FNC) service that covers hospitalization costs has set a maximum limit of Nepalese rupees (NPR) 8000 i.e. USD 73.5, the basis of which is unclear. We aimed to estimate the costs of treatment in neonates and young infants fulfilling clinical criteria for sepsis, defined as clinical severe infection (CSI) to identify determinants of increased cost. This study assessed costs for treatment of 206 infants 3–59 days old, enrolled in a clinical trial, and admitted to the Kanti Children’s Hospital in Nepal through June 2017 to December 2018. Total costs were derived as the sum of direct costs for bed charges, investigations, and medicines and indirect costs calculated by using work time loss of parents. We estimated treatment costs for CSI, the proportion exceeding NPR 8000 and performed multivariable linear regression to identify determinants of high cost. Of the 206 infants, 138 (67%) were neonates (3–28 days). The median (IQR) direct costs for treatment of CSI in neonates and young infants (29–59 days) were USD 111.7 (69.8–155.5) and 65.17 (43.4–98.5) respectively. The direct costs exceeded NPR 8000 (USD 73.5) in 69% of neonates with CSI. Age <29 days, moderate malnutrition, presence of any sign of critical illness and documented treatment failure were found to be important determinants of high costs for treatment of CSI. According to this study, the average treatment cost for a newborn with CSI in a public tertiary level hospital is substantial. The maximum limit offered for free newborn care in public hospitals needs to be revised for better acceptance and successful implementation of the FNC service to avert catastrophic health expenditures in developing countries like Nepal. Trial Registration: CTRI/2017/02/007966 (Registered on: 27/02/2017).

Immunoreactive Trypsinogen and Free Carnitine Changes on Newborn Screening after Birth in Patients Who Develop Type 1 Diabetes

Are free carnitine concentrations on newborn screening (NBS) 48–72 h after birth lower in patients who develop type 1 diabetes than in controls? A retrospective case-control study of patients with type 1 diabetes was conducted. NBS results of patients from a Sydney hospital were compared against matched controls from the same hospital (1:5). Multiple imputation was performed for estimating missing data (gestational age) using gender and birthweight. Conditional logistic regression was used to control for confounding and to generate parameter estimates (α = 0.05). The Hommel approach was used for post-hoc analyses. Results are reported as medians and interquartile ranges. A total of 159 patients were eligible (80 females). Antibodies were detectable in 86. Median age at diagnosis was 8 years. Free carnitine concentrations were lower in patients than controls (25.50 µmol/L;18.98–33.61 vs. 27.26; 21.22–34.86 respectively) (p = 0.018). Immunoreactive trypsinogen was higher in this group (20.24 µg/L;16.15–29–52 vs. 18.71; 13.96–26.92) (p = 0.045), which did not persist in the post-hoc analysis. Carnitine levels are lower and immunoreactive trypsinogen might be higher, within 2–3 days of birth and years before development of type 1 diabetes as compared to controls, although the differences were well within reference ranges and provide insight into the pathogenesis into neonatal onset of type 1 diabetes development rather than use as a diagnostic tool. Given trypsinogen’s use for evaluation of new-onset type 1 diabetes, larger studies are warranted.

Clinical Significance of the Serum lncRNA NORAD Expression in Patients with Neonatal Sepsis and Its Association with miR-410-3p

Purpose

Neonatal sepsis (NS) is one of the most crucial causes of death in newborns. This investigation aimed to validate the expression level of NORAD and the probable mechanism underlying the function of NORAD in NS.

Patients and Methods

The expression of NORAD and miR-410-3p was identified by qRT-PCR. The diagnostic sensitivity and specificity of NORAD were examined by the ROC curve. The NS cell models were established by the treatment of lipopolysaccharide (LPS) in the macrophage RAW264.7 cells. The luciferase report assay was performed to detect the target relationship between NORAD and miR-410-3p and the association between them was revealed by Pearson correlation.

Results

The expression of NORAD was at a higher level in the NS group than in the pneumonia controls. The levels of NORAD could sever as a diagnostic marker on discriminating NS patients from pneumonia neonates. The expression of IL-6, IL-8, and TNF-α was enhanced in the macrophage cells under LPS circumstances, while NORAD knockdown reversed the overexpression of these pro-inflammatory cytokines. Besides, miR-410-3p was a possible ceRNA of NORAD by the finding that the luciferase activity fell in the co-transfection of miR-410-3p mimics and WT-NORAD group. In vitro, LPS management could inhibit the expression of miR-410-3p, while silenced NORAD ameliorated the suppressed miR-410-3p levels. Decreased expression of miR-410-3p was discovered in NS patients and the changes of miR-410-3p expression were correlated with the levels of NORAD in the NS patients.

Conclusion

We found a raised level of NORAD in the NS patients and it might be a diagnostic indicator for NS patients. NORAD elimination meliorated the inflammation actions steered by LPS. MiR-410-3p was a target of NORAD and lowly expressed in the NS patients.

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.

The lipid biology of sepsis

Sepsis, defined as the dysregulated immune response to an infection leading to organ dysfunction, is one of the leading causes of mortality around the globe. Despite the significant progress in delineating the underlying mechanisms of sepsis pathogenesis, there are currently no effective treatments or specific diagnostic biomarkers in the clinical setting. The perturbation of cell signaling mechanisms, inadequate inflammation resolution, and energy imbalance, all of which are altered during sepsis, are also known to lead to defective lipid metabolism. The use of lipids as biomarkers with high specificity and sensitivity may aid in early diagnosis and guide clinical decision making. In addition, identifying the link between specific lipid signatures and their role in sepsis pathology may lead to novel therapeutics. In this review, we discuss the recent evidence on dysregulated lipid metabolism both in experimental and human sepsis focused on bioactive lipids, fatty acids, and cholesterol as well as the enzymes regulating their levels during sepsis. We highlight not only their potential roles in sepsis pathogenesis but also the possibility of using these respective lipid compounds as diagnostic and prognostic biomarkers of sepsis.

Newborn metabolic vulnerability profile identifies preterm infants at risk for mortality and morbidity

BACKGROUND

Identifying preterm infants at risk for mortality or major morbidity traditionally relies on gestational age, birth weight, and other clinical characteristics that offer underwhelming utility. We sought to determine whether a newborn metabolic vulnerability profile at birth can be used to evaluate risk for neonatal mortality and major morbidity in preterm infants.

METHODS

This was a population-based retrospective cohort study of preterm infants born between 2005 and 2011 in California. We created a newborn metabolic vulnerability profile wherein maternal/infant characteristics along with routine newborn screening metabolites were evaluated for their association with neonatal mortality or major morbidity.

RESULTS

Nine thousand six hundred and thirty-nine (9.2%) preterm infants experienced mortality or at least one complication. Six characteristics and 19 metabolites were included in the final metabolic vulnerability model. The model demonstrated exceptional performance for the composite outcome of mortality or any major morbidity (AUC 0.923 (95% CI: 0.917-0.929). Performance was maintained across mortality and morbidity subgroups (AUCs 0.893-0.979).

CONCLUSIONS

Metabolites measured as part of routine newborn screening can be used to create a metabolic vulnerability profile. These findings lay the foundation for targeted clinical monitoring and further investigation of biological pathways that may increase the risk of neonatal death or major complications in infants born preterm.

IMPACT

We built a newborn metabolic vulnerability profile that could identify preterm infants at risk for major morbidity and mortality. Identifying high-risk infants by this method is novel to the field and outperforms models currently in use that rely primarily on infant characteristics. Utilizing the newborn metabolic vulnerability profile for precision clinical monitoring and targeted investigation of etiologic pathways could lead to reductions in the incidence and severity of major morbidities associated with preterm birth.

Serum Newborn Screening Blood Metabolites Are not Associated With Childhood-onset Inflammatory Bowel Disease: A Population-based Matched Case-control Study

BACKGROUND

Originally used for screening of inborn errors of metabolism, routine metabolite profiles of newborns have also been associated with prematurity and some childhood diseases. We sought to determine whether metabolites measured during routine newborn screening could identify infants who develop inflammatory bowel disease (IBD) in childhood.

METHODS

We conducted a population-based matched case-control study using health administrative data from Ontario, Canada. Children born 2006 to 2015 with IBD were identified using a validated algorithm and matched to 5 controls based on birth date, sex, rural/urban household, and mean neighborhood income quintile at birth. Cases and controls were linked deterministically to metabolic profiles from Newborn Screening Ontario. We fit a lasso penalized logistic regression model and used 10-fold cross-validation to obtain internally valid performance measures. Models included metabolites, amino acids, and endocrine markers. Models also included ratios of metabolites, gestational age, birth weight, mode of delivery, age at serum collection, maternal age at delivery, maternal history of IBD, and parity.

RESULTS

Three hundred eight cases of IBD, diagnosed at 5.5 ± 2.8 years, were matched to 1540 controls. No individual metabolites were associated with IBD. The c-statistic was 0.50 for the training data. After 10-fold cross-validation the C statistic was 0.50, indicating no significant association between metabolites and IBD diagnosis.

CONCLUSIONS

Newborn screening serum metabolites could not identify children who will develop IBD in this population-based cohort. Future studies with an expanded panel of metabolites may provide improved prediction of IBD.

Newborn Screening Samples for Diabetes Research: An Underused Resource

Inborn errors of metabolism and diabetes share common derangements in analytes of metabolic networks that are tested for in newborn screening, usually performed 48-72 h after birth. There is limited research examining the metabolic imprint of diabetes on newborn screening results. This paper aims to demonstrate the links between diabetes, biochemical genetics and newborn screening in investigating disease pathophysiology in diabetes, provide possible reasons for the lack of research in diabetes in newborn screening and offer recommendations on potential research areas. We performed a systematic search of the available literature from 1 April 1998 to 31 December 2018 involving newborn screening and diabetes using OVID, MEDLINE, Cochrane and the PROSPERO register, utilizing a modified extraction tool adapted from Cochrane. Eight studies were included after screening 1312 records. Five studies reanalyzed dried blood spots (DBS) on filter paper cards, and three studies utilized pre-existing results. The results of these studies and how they relate to cord blood studies, the use of cord blood versus newborn screening dried blood spots as a sample and considerations on newborn screening and diabetes research is further discussed. The timing of sampling of newborn screening allows insight into neonatal physiology in a catabolic state with minimal maternal and placental influence. This, combined with the wide coverage of newborn screening worldwide, may aid in our understanding of the origins of diabetes.

Association between newborn screening analytes and hypoxic ischemic encephalopathy

Hypoxic ischemic encephalopathy (HIE) is a major cause of neonatal mortality and morbidity. Our study sought to examine whether patterns of newborn screening analytes differed between infants with and without neonatal HIE in order to identify opportunities for potential use of these analytes for diagnosis in routine clinical practice. We linked a population-based newborn screening registry with health databases to identify cases of HIE among term infants (≥37 weeks' gestation) in Ontario from 2010-2015. Correlations between HIE and screening analytes were examined using multivariable logistic regression models containing clinical factors and individual screening analytes (acyl-carnitines, amino acids, fetal-to-adult hemoglobin ratio, endocrine markers, and enzymes). Among 731,841 term infants, 3,010 were diagnosed with HIE during the neonatal period. Multivariable models indicated that clinical variables alone or in combination with hemoglobin values were not associated with HIE diagnosis. Although the model was improved after adding acyl-carnitines and amino acids, the ability of the model to identify infants with HIE was moderate. Our findings indicate that analytes associated with catabolic stress were altered in infants with HIE; however, future research is required to determine whether amino acid and acyl-carnitine profiles could hold clinical utility in the early diagnosis or clinical management of HIE. In particular, further research should examine whether cord blood analyses can be used to identify HIE within a clinically useful timeframe or to guide treatment and predict long-term health outcomes.

Investigation of association between maternal 25-OH vitamin D serum levels and neonatal early onset sepsis in newborns by evaluating key factors

Background

The goal of this study was to evaluate the relationship between maternal 25-OH Vitamin D serum levels and neonatal early-onset sepsis in newborns by the effective factors.

Methods

A case-control study was done and 64 neonates hospitalized in Akbar Abadi Hospital (Tehran- Iran; 2016) and their mothers were enrolled. The case group consisted of 32 NICU term hospitalized neonates due to neonatal early-onset sepsis. Thirty-two term newborns that referred to hospital for rule out hyperbilirubinemia during the first 72 h of life were also considered as the control.

Results

Sixty- four mothers with mean age 28.76 ± 6.60 years and mean gestational age 39.64 ± 1.62 weeks entered the study. There was a significant correlation between sepsis and older age of mothers and low Apgar score (P-value = 0.02, 0.01 respectively). The maternal vitamin D serum level was reversely correlated with neonatal sepsis occurrence (P-value = 0.03). There was a significant correlation between maternal vitamin D supplement intake during pregnancy and lower risk for neonatal sepsis (P-value = 0.003).

Conclusion

The level of maternal serum Vitamin D was inversely correlated with neonatal sepsis occurrence and intake of vitamin D supplement during pregnancy could decrease the risk of early neonatal sepsis.

Association between newborn screening analyte profiles and infant mortality

Objective

To assess whether newborn screening analytes could be utilized beyond their traditional application to identify infants at high risk of mortality within the first 6 months of life.

Methods

We linked a province-wide newborn screening registry with health administrative databases to identify infant deaths within 6 months in a source population of live-born infants between 2010 and 2014. We used a nested case-control study design, in which all infant deaths between 7 days and 6 months of age were included as cases, and a random sample of infants from the source population were selected as controls and were matched to cases at a ratio of 10:1. We examined the association between mortality and screening analytes (acylcarnitines, amino acids, fetal-to-adult hemoglobin ratio, endocrine markers, and enzymes) using lasso regression to fit multivariable models.

Results

Among 350 infant deaths between 7 days and 6 months of age, and 3498 matched controls with complete data, our multivariable model demonstrated only modest ability to identify infant deaths (optimism-corrected c-statistic: 0.61, 95% confidence interval: 0.50–0.71).

Conclusions

We did not find newborn screening analytes to be strongly predictive of infant mortality between 7 days and 6 months of age in the general population of newborns. Future studies should investigate whether predictive modeling within more homogeneous cause-of-death categories could lead to improved predictive ability for infant mortality.

Using Self Organizing Maps to Compare Sepsis Patients from the Neonatal and Adult Intensive Care Unit

Neonatal sepsis, a blood infection occurring in infants younger than 90 days old, represents a significant source of mortality and morbidity among infants.¹ Mortality rates increase with postnatal age and can be as high as 52% (36% in newborns aged 8-14 days and 52% in those aged 15-28 days).² While sepsis in adults has a generally accepted definition, the definition for clinical diagnosis in infants is less well defined. Using the Medical Information Mart for Intensive Care database (MIMIC-III), patient diagnoses and microbiology results records were processed with an artificial neural network trained using unsupervised learning known as a self-organizing map (SOM). The results of this feasibility study suggest a low degree of overlap between the presentation of sepsis in neonate and adult intensive care unit populations. As a consequence, it supports the need for dedicated research in neonatal sepsis, which may manifest differently than adult sepsis.