ArticleCritical care explorations2020
Discovery and Validation of Urinary Molecular Signature of Early Sepsis.
Article in Critical care explorations, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- The Diagnostic Utility of Host RNA Biosignatures in Adult Patients With Sepsis: A Systematic Review and Meta-Analysis.Critical care explorations · 2025Pooled it
- Exploring the biomarkers and potential therapeutic drugs for sepsis via integrated bioinformatic analysis.BMC infectious diseases · 2024Article
- Disruption of Kidney-Immune System Crosstalk in Sepsis with Acute Kidney Injury: Lessons Learned from Animal Models and Their Application to Human Health.International journal of molecular sciences · 2022Review
- Identification of Immune-Related Key Genes as Potential Diagnostic Biomarkers of Sepsis in Children.Journal of inflammation research · 2022Article
- Transcriptome-Wide Analysis of Human Liver Reveals Age-Related Differences in the Expression of Select Functional Gene Clusters and Evidence for a PPP1R10-Governed 'Aging Cascade'.Pharmaceutics · 2021Article
- Longitudinal urinary biomarkers of immunological activation in covid-19 patients without clinically apparent kidney disease versus acute and chronic failure.Scientific reports · 2021Article
- Screening of Key Genes of Sepsis and Septic Shock Using Bioinformatics Analysis.Journal of inflammation research · 2021Article
Corrections and comments
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Authors and funding
19 authors at 2 institutions in 1 country.
Funding
Abstract
Identify alterations in gene expression unique to systemic and kidney-specific pathophysiologic processes using whole-genome analyses of RNA isolated from the urinary cells of sepsis patients.
designProspective cohort study.
settingQuaternary care academic hospital. PATIENTS: A total of 266 sepsis and 82 control patients enrolled between January 2015 and February 2018.
interventionsWhole-genome transcriptomic analysis of messenger RNA isolated from the urinary cells of sepsis patients within 12 hours of sepsis onset and from control subjects. MEASUREMENTS AND MAIN
resultsThe differentially expressed probes that map to known genes were subjected to feature selection using multiple machine learning techniques to find the best subset of probes that differentiates sepsis from control subjects. Using differential expression augmented with machine learning ensembles, we identified a set of 239 genes in urine, which show excellent effectiveness in classifying septic patients from those with chronic systemic disease in both internal and independent external validation cohorts. Functional analysis indexes disrupted biological pathways in early sepsis and reveal key molecular networks driving its pathogenesis.
conclusionsWe identified unique urinary gene expression profile in early sepsis. Future studies need to confirm whether this approach can complement blood transcriptomic approaches for sepsis diagnosis and prognostication.
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Registered trials
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