ArticleEBioMedicine2021
VB
Article in EBioMedicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 28 citations in OpenAlex.
- Host gene expression analysis in the detection of bacterial and viral etiology in children hospitalized with a suspected severe infection.Communications medicine · 2026Article
- A new algorithm Precision OncoPanels (PrOPs) identifies short individualized actionable panels that can guide cancer treatment: a pan-cancer analysis of TCGA cohorts.NAR genomics and bioinformatics · 2025Article
- Interferon-Stimulated Genes and Immune Metabolites as Broad-Spectrum Biomarkers for Viral Infections.Viruses · 2025Review
- Development of a host-signature-based machine learning model to diagnose bacterial and viral infections in febrile children.Frontiers in pediatrics · 2025Article
- SARS-CoV-2 human challenge reveals biomarkers that discriminate early and late phases of respiratory viral infections.Nature communications · 2024Article
- Protein and transcriptional biomarker profiling may inform treatment strategies in lower respiratory tract infections by indicating bacterial-viral differentiation.Microbiology spectrum · 2024Article
- Deep learning model to discriminate diverse infection types based on pairwise analysis of host gene expression.iScience · 2024Article
- Systems-level profiling of early peripheral host-response landscape variations across COVID-19 severity states in an Indian cohort.Genes and immunity · 2023Article
- A comprehensive analysis of gene expression profiling data in COVID-19 patients for discovery of specific and differential blood biomarker signatures.Scientific reports · 2023Article
- MORC2 and MAX contributes to the expression of glycolytic enzymes, breast cancer cell proliferation and migration.Medical oncology (Northwood, London, England) · 2023Article
- Systematic comparison of published host gene expression signatures for bacterial/viral discrimination.Genome medicine · 2022Article
- A new blood-based RNA signature (RiScience · 2022Article
- Article
- Bioinformatics analysis of potential pathogenesis and risk genes of immunoinflammation-promoted renal injury in severe COVID-19.Frontiers in immunology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPrecise differential diagnosis between acute viral and bacterial infections is important to enable appropriate therapy, avoid unnecessary antibiotic prescriptions and optimize the use of hospital resources. A systems view of host response to infections provides opportunities for discovering sensitive and robust molecular diagnostics.
methodsWe combine blood transcriptomes from six independent datasets (n = 756) with a knowledge-based human protein-protein interaction network, identifies subnetworks capturing host response to each infection class, and derives common response cores separately for viral and bacterial infections. We subject the subnetworks to a series of computational filters to identify a parsimonious gene panel and a standalone diagnostic score that can be applied to individual samples. We rigorously validate the panel and the diagnostic score in a wide range of publicly available datasets and in a newly developed Bangalore-Viral Bacterial (BL-VB) cohort. FINDING: We discover a 10-gene blood-based biomarker panel (Panel-VB) that demonstrates high predictive performance to distinguish viral from bacterial infections, with a weighted mean AUROC of 0.97 (95% CI: 0.96-0.99) in eleven independent datasets (n = 898). We devise a new stand-alone patient-wise score (VB
interpretationOur results point to the promise of VB
fundingGrand Challenges India, Biotechnology Industry Research Assistance Council (BIRAC), Department of Biotechnology, Govt. of India.
Indexed as
Identifiers
What OpenQuestion holds
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.