ArticleNature communications2020
A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers, 4 of them syntheses that pooled it.
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Who cites it
72 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- A consensus blood transcriptomic framework for sepsis.Nature medicine · 2025Guideline
- Comprehensive multi-cohort transcriptional meta-analysis of muscle diseases identifies a signature of disease severity.Scientific reports · 2022Pooled it
- Increasing reproducibility, robustness, and generalizability of biomarker selection from meta-analysis using Bayesian methodology.PLoS computational biology · 2022Pooled it
- Multisystem inflammatory syndrome in children: a microcosm of challenges and opportunities for translational bioinformatics in pediatric research.Current opinion in pediatrics · 2021Pooled it
- A 6-mRNA host response classifier in whole blood predicts outcomes in COVID-19 and other acute viral infections.Scientific reports · 2022Trial
- Patient representation in RNA signature studies for detecting and predicting the outcomes of febrile illnesses: a scoping review.BMC infectious diseases · 2026Article
- An 11-gene blood transcriptomic signature reflects a sepsis-associated host-response pattern across public cohorts.Frontiers in medicine · 2026Article
- Blood Host-Response mRNA Assays in Adult Acute Care: Diagnostic Performance, Translational Evidence, and the Clinical Implementation Gap.Infection and drug resistance · 2026Review
- Clinical validation of an AI-based blood testing device for diagnosis and prognosis of acute infection and sepsis.Nature medicine · 2025Observational
- Metagenomic fingerprints in bronchoalveolar lavage differentiate pulmonary diseases.NPJ digital medicine · 2025Article
- Molecular dynamics of the host response to Streptococcus pneumoniae pneumonia in baboons.Animal models and experimental medicine · 2025Article
- Novel methods for temporally varying gene identification in longitudinal studies reveal bleeding and clotting pathway activation caused by blood draws.Briefings in bioinformatics · 2025Article
- Real-World Utility of the Host-Response MeMed BV Test in a Pediatric Emergency Department: A Non-Randomized Study with Optimized Antimicrobial and Diagnostic Stewardship.Children (Basel, Switzerland) · 2025Article
- Towards novel BIOmarkers to diagnose SEPsis (BIOSEP) in the emergency room: a protocol for a multicentre, prospective cohort study.BMJ open · 2025Article
- Rapid, Amplification-free, RNA-based Uropathogen Detection With LbuCas13a.Open forum infectious diseases · 2025Article
- 29-mRNA host response signatures for classification of bacterial infection, viral infection and disease progression in COVID-19 pneumonia: a post hoc analysis of the SAVE-MORE randomized clinical trial.Intensive care medicine experimental · 2025Article
- Prediction of lung overdistension during mechanical ventilation using micro-RNA and gene expression.Intensive care medicine experimental · 2025Article
- Spatial transcriptomics identifies novel Pseudomonas aeruginosa virulence factors.Cell genomics · 2025Article
- Solving the diagnostic dilemma in bone infections: metagenomic next generation sequencing enhances pathogen identification accuracy.Frontiers in medicine · 2025Article
- A Rapid Host Response Blood Test for Bacterial/Viral Infection Discrimination Using a Portable Molecular Diagnostic Platform.Open forum infectious diseases · 2025Article
12 more citing papers are in PubMed but not listed here.
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Authors and funding
15 authors.
Funding
Abstract
Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90-0.93) and a viral-vs-other AUROC 0.92 (95% CI 0.90-0.93). We then apply this classifier, inflammatix-bacterial-viral-noninfected-version 1 (IMX-BVN-1), without retraining, to an independent cohort (N = 163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77-0.93), and viral-vs.-other 0.85 (95% CI 0.76-0.93). In patients enrolled within 36 h of hospital admission (N = 70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83-0.99), and viral-vs.-other 0.91 (95% CI 0.82-0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission.
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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.