Evidence map›Paper›PMID 34836493›Full record

ArticleBMC infectious diseases2021

Identification of transcriptomics biomarkers for the early prediction of the prognosis of septic shock from pneumopathies.

Songchang Shi, Xiaobin Pan, Hangwei Feng, Shujuan Zhang, Songjing Shi, Wei Lin

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2021. 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
1.1field-weighted citation impact, top 22% 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

4 citing papers in PubMed, 7 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

6 authors at 2 institutions in 1 country.

Songchang Shi *Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital South Branch, Fujian Provincial Hospital Jinshan Branch, Fuzhou, 350001, Fujian, People's Republic of China.
Xiaobin Pan *Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital South Branch, Fujian Provincial Hospital Jinshan Branch, Fuzhou, 350001, Fujian, People's Republic of China.
Hangwei FengDepartment of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital South Branch, Fujian Provincial Hospital Jinshan Branch, Fuzhou, 350001, Fujian, People's Republic of China.
Shujuan ZhangDepartment of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital South Branch, Fujian Provincial Hospital Jinshan Branch, Fuzhou, 350001, Fujian, People's Republic of China.
Songjing ShiDepartment of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, No.134 East Street, Gulou District, Fuzhou, 350001, Fujian, People's Republic of China. songjingshifz@163.com.
Wei LinDepartment of Endocrinology, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, No.134 East Street, Gulou District, Fuzhou, 350001, Fujian, People's Republic of China. caolalin0929@163.com.
Fujian Provincial Hospital · CNFujian Medical University · CN

Funding

Natural Science Foundation of Fujian Province 2019J01175Natural Science Foundation of Fujian Province 2020J011068Startup Fund for scientific research, Fujian Medical University 2018QH1160Young and Middle-aged Talents Training Project of Fujian Provincial Health Commission 2018-ZQN-1
6 · The paper itself

Abstract

backgroundIdentifying the biological subclasses of septic shock might provide specific targeted therapies for the treatment and prognosis of septic shock. It might be possible to find biological markers for the early prediction of septic shock prognosis.

methodsThe data were obtained from the Gene Expression Omnibus databases (GEO) in NCBI. GO enrichment and KEGG pathway analyses were performed to investigate the functional annotation of up- and downregulated DEGs. ROC curves were drawn, and their areas under the curves (AUCs) were determined to evaluate the predictive value of the key genes.

results117 DEGs were obtained, including 36 up- and 81 downregulated DEGs. The AUC for the MME gene was 0.879, as a key gene with the most obvious upregulation in septic shock. The AUC for the THBS1 gene was 0.889, as a key downregulated gene with the most obvious downregulation in septic shock.

conclusionsThe upregulation of MME via the renin-angiotensin system pathway and the downregulation of THBS1 through the PI3K-Akt signaling pathway might have implications for the early prediction of prognosis of septic shock in patients with pneumopathies.

Indexed as

Shock, SepticTranscriptomeBiomarkersComputational BiologyHumansPhosphatidylinositol 3-KinasesPrognosisBiomarkersPhosphatidylinositol 3-KinasesBiomarkersPredictionPrognosisSeptic shockTranscriptomics

Identifiers

PMID34836493
PMCPMC8619650
OpenAlexW3214912602

What OpenQuestion holds

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Registered trials

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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.