ArticleJournal of the Pediatric Infectious Diseases Society2018
Validation of the Sepsis MetaScore for Diagnosis of Neonatal Sepsis.
Article in Journal of the Pediatric Infectious Diseases Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 2 of them syntheses that pooled it.
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Who cites it
25 citing papers in PubMed, 2 syntheses or guidelines pooled it, 48 citations in OpenAlex.
- Using molecular methods to diagnose, classify, and treat neonatal sepsis: a scoping review.Frontiers in pediatrics · 2025Pooled it
- Multisystem inflammatory syndrome in children: a microcosm of challenges and opportunities for translational bioinformatics in pediatric research.Current opinion in pediatrics · 2021Pooled it
- Integrating host mRNA signatures and clinical trajectories with machine learning for risk stratification and survival prediction in sepsis: an ICU-based prospective cohort study.BMC infectious diseases · 2026Article
- Systems biology approaches to unravelling neonatal sepsis and potential for precision diagnostics and therapeutics.Frontiers in pharmacology · 2026Review
- Article
- Predictive gene expression signature diagnoses neonatal sepsis before clinical presentation.EBioMedicine · 2024Article
- Harnessing artificial intelligence in sepsis care: advances in early detection, personalized treatment, and real-time monitoring.Frontiers in medicine · 2024Review
- The molecular landscape of sepsis severity in infants: enhanced coagulation, innate immunity, and T cell repression.Frontiers in immunology · 2024Article
- Differentiating infection, colonisation, and sterile inflammation in critical illness: the emerging role of host-response profiling.Intensive care medicine · 2023Review
- Bioinformatic Analysis and Machine Learning Methods in Neonatal Sepsis: Identification of Biomarkers and Immune Infiltration.Biomedicines · 2023Article
- Effects of Sepsis on Immune Response, Microbiome and Oxidative Metabolism in Preterm Infants.Children (Basel, Switzerland) · 2023Review
- Transcriptomic profiles of multiple organ dysfunction syndrome phenotypes in pediatric critical influenza.Frontiers in immunology · 2023Article
- Artificial and human intelligence for early identification of neonatal sepsis.Pediatric research · 2023Review
- The 'analysis of gene expression and biomarkers for point-of-care decision support in Sepsis' study; temporal clinical parameter analysis and validation of early diagnostic biomarker signatures for severe inflammation andsepsis-SIRS discrimination.Frontiers in immunology · 2023Article
- A robust gene expression signature for NASH in liver expression data.Scientific reports · 2022Article
- Implications of Using Host Response-Based Molecular Diagnostics on the Management of Bacterial and Viral Infections: A Review.Frontiers in medicine · 2022Review
- Knowledge gaps in late-onset neonatal sepsis in preterm neonates: a roadmap for future research.Pediatric research · 2022Review
- Development of a fixed module repertoire for the analysis and interpretation of blood transcriptome data.Nature communications · 2021Article
- A Precision Medicine Approach to Biomarker Utilization in Pediatric Sepsis-Associated Acute Kidney Injury.Frontiers in pediatrics · 2021Review
- Stratified Management for Bacterial Infections in Late Preterm and Term Neonates: Current Strategies and Future Opportunities Toward Precision Medicine.Frontiers in pediatrics · 2021Review
Corrections and comments
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Authors and funding
8 authors at 5 institutions in 2 countries.
Funding
Abstract
WHAT’S KNOWN ON THIS SUBJECT: Neonates are at increased risk for developing sepsis, but this population often exhibits ambiguous clinical signs that complicate the diagnosis of infection. No biomarker has yet shown enough diagnostic accuracy to rule out sepsis at the time of clinical suspicion. WHAT THIS STUDY ADDS: We show that a gene-expression-based signature is an accurate objective measure of the risk of sepsis in a neonate or preterm infant, and it substantially improves diagnostic accuracy over that of commonly used laboratory-based testing. Implementation might decrease inappropriate antibiotic use.
backgroundNeonatal sepsis can have devastating consequences, but accurate diagnosis is difficult. As a result, up to 200 neonates with suspected sepsis are treated with empiric antibiotics for every 1 case of microbiologically confirmed sepsis. These unnecessary antibiotics enhance bacterial antibiotic resistance, increase economic costs, and alter gut microbiota composition. We recently reported an 11-gene diagnostic test for sepsis (Sepsis MetaScore) based on host whole-blood gene expression in children and adults, but this test has not been evaluated in neonates.
methodsWe identified existing gene expression microarray-based cohorts of neonates with sepsis. We then tested the accuracy of the Sepsis MetaScore both alone and in combination with standard diagnostic laboratory tests in diagnosing sepsis.
resultsWe found 3 cohorts with a total of 213 samples from control neonates and neonates with sepsis. The Sepsis MetaScore had an area under the receiver operating characteristic curve of 0.92-0.93 in all 3 cohorts. We also found that, as a diagnostic test for sepsis, it outperformed standard laboratory measurements alone and, when used in combination with another test(s), resulted in a significant net reclassification index (0.3-0.69) in 5 of 6 comparisons. The mean point estimates for sensitivity and specificity were 95% and 60%, respectively, which, if confirmed prospectively and applied in a high-risk cohort, could reduce inappropriate antibiotic usage substantially.
conclusionsThe Sepsis MetaScore had excellent diagnostic accuracy across 3 separate cohorts of neonates from 3 different countries. Further prospective targeted study will be needed before clinical application.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.