Evidence map›Paper›PMID 39888601›Full record

SynthesisCritical care explorations2025

The Diagnostic Utility of Host RNA Biosignatures in Adult Patients With Sepsis: A Systematic Review and Meta-Analysis.

Mervin V Loi, Rehena Sultana, Tuong Minh Nguyen, Shi Ting Tia, Jan Hau Lee, Daniel O'Connor

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Critical care explorations, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mervin V LoiDepartment of Paediatric Subspecialties, Children's Intensive Care Unit, KK Women's and Children's Hospital, Singapore, Singapore.
Rehena SultanaCenter for Quantitative Medicine, Duke-NUS Medical School, Singapore, Singapore.
Tuong Minh NguyenDepartment of Industrial Systems Engineering and Management, College of Design and Engineering, National University of Singapore, Singapore, Singapore.
Shi Ting TiaDepartment of Biological Sciences, National University of Singapore, Singapore, Singapore.
Jan Hau LeeDepartment of Paediatric Subspecialties, Children's Intensive Care Unit, KK Women's and Children's Hospital, Singapore, Singapore.
Daniel O'ConnorOxford Vaccine Group, Department of Paediatrics, University of Oxford, Oxford, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesSepsis is a life-threatening medical emergency, with a profound healthcare burden globally. Its pathophysiology is complex, heterogeneous and temporally dynamic, making diagnosis challenging. Medical management is predicated on early diagnosis and timely intervention. Transcriptomics is one of the novel "-omics" technologies being evaluated for recognition of sepsis. Our objective was to evaluate the performance of host gene expression biosignatures for the diagnosis of all-cause sepsis in adults. DATA SOURCES: PubMed/Ovid Medline, Ovid Embase, and Cochrane databases from inception to June 2023. STUDY SELECTION: We included studies evaluating the performance of host gene expression biosignatures in adults who were diagnosed with sepsis using existing clinical definitions. Controls where applicable were patients without clinical sepsis. DATA EXTRACTION: Data including population demographics, sample size, study design, tissue specimen, type of transcriptome, health status of comparator group, and performance of transcriptomic biomarkers were independently extracted by at least two reviewers. DATA SYNTHESIS: Meta-analysis to describe the performance of host gene expression biosignatures for the diagnosis of sepsis in adult patients was performed using the random-effects model. Risk of bias was assessed according to the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A total of 117 studies (n = 17,469), comprising 132 separate patient datasets, were included in our final analysis. Performance of transcriptomics for the diagnosis of sepsis against pooled controls showed area under the receiver operating characteristic curve (AUC, 0.86; 95% CI, 0.84-0.88). Studies using healthy controls showed AUC 0.87 (95% CI, 0.84-0.89), while studies using controls with systemic inflammatory response syndrome (SIRS) had AUC 0.84 (95% CI, 0.78-0.90). Transcripts with excellent discrimination against SIRS controls include UrSepsisModel, a 210 differentially expressed genes biosignature, microRNA-143, and Septicyte laboratory.

conclusionsTranscriptomics is a promising approach for the accurate diagnosis of sepsis in adults and demonstrates good discriminatory ability against both healthy and SIRS control subjects.

Indexed as

RNASepsisAdultBiomarkersGene Expression ProfilingHumansTranscriptomeBiomarkersRNA

Identifiers

PMID39888601
PMCPMC11789890

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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 Socratic graph.