Evidence map›Paper›PMID 36518055›Full record

ArticleJournal of Zhejiang University. Science. B2022

Development and validation of novel inflammatory response-related gene signature for sepsis prognosis.

Shuai Jiang, Wenyuan Zhang, Yuanqiang Lu

Open access · greenAbstract read
In one paragraph

Article in Journal of Zhejiang University. Science. B, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 14% of its field
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

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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

3 authors at 3 institutions in 1 country.

Shuai JiangDepartment of Emergency Medicine, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China.
Wenyuan ZhangDepartment of Anesthesiology and Intensive Care, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China.
Yuanqiang LuDepartment of Emergency Medicine, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China. luyuanqiang@zju.edu.cn.
First Affiliated Hospital Zhejiang University · CNZhejiang Center for Disease Control and Prevention · CNZhejiang University · CN

Funding

the Key Research and Development Program of Zhejiang Province 2019C03076the Opening Foundation of the State Key Laboratory for Diagnosis and Treatment of Infectious Diseases 2018KF02
6 · The paper itself

Abstract

Due to the low specificity and sensitivity of biomarkers in sepsis diagnostics, the prognosis of sepsis patient outcomes still relies on the assessment of clinical symptoms. Inflammatory response is crucial to sepsis onset and progression; however, the significance of inflammatory response-related genes (IRRGs) in sepsis prognosis is uncertain. This study developed an IRRG-based signature for sepsis prognosis and immunological function. The Gene Expression Omnibus (GEO) database was retrieved for two sepsis microarray datasets, GSE64457 and GSE69528, followed by gene set enrichment analysis (GSEA) comparing sepsis and healthy samples. A predictive signature for IRRGs was created using least absolute shrinkage and selection operator (LASSO). To confirm the efficacy and reliability of the new prognostic signature, Cox regression, Kaplan-Meier (K-M) survival, and receiver operating characteristic (ROC) curve analyses were performed. Subsequently, we employed the GSE95233 dataset to independently validate the prognostic signature. A single-sample GSEA (ssGSEA) was conducted to quantify the immune cell enrichment score and immune-related pathway activity. We found that more gene sets were enriched in the inflammatory response in sepsis patient samples than in healthy patient samples, as determined by GSEA. The signature of nine IRRGs permitted the patients to be classified into two risk categories. Patients in the low-risk group showed significantly better 28-d survival than those in the high-risk group. ROC curve analysis corroborated the predictive capacity of the signature, with the area under the curve (AUC) for 28-d survival reaching 0.866. Meanwhile, the ssGSEA showed that the two risk groups had different immune states. The validation set and external dataset showed that the signature was clinically predictive. In conclusion, a signature consisting of nine IRRGs can be utilized to predict prognosis and influence the immunological status of sepsis patients. Thus, intervention based on these IRRGs may become a therapeutic option in the future.

Indexed as

SepsisArea Under CurveHumansLeukocyte CountReproducibility of ResultsROC CurveGene signatureImmune functionInflammatory response-related gene (IRRG)PrognosisSepsis

Identifiers

PMID36518055
PMCPMC9758714
OpenAlexW4312066249

What OpenQuestion holds

Textmetadata
Read underepoch 390

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 OpenQuestion graph.