Evidence map›Paper›PMID 34675320›Full record

ArticleScientific reports2021

A panel of urine-derived biomarkers to identify sepsis and distinguish it from systemic inflammatory response syndrome.

Yao Tang, Ning Ling, Shiying Li, Juan Huang, Wenyue Zhang, An Zhang, Hong Ren, Yixuan Yang, Huaidong Hu, Xiaohao Wang

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 28% 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

5 citing papers in PubMed, 9 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

10 authors at 3 institutions in 1 country.

Yao Tang *Department of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Ning Ling *Key Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Shiying LiKey Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Juan HuangDepartment of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Wenyue ZhangDepartment of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
An ZhangIntensive Care Unit, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Hong RenKey Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Yixuan YangKey Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Huaidong HuDepartment of Infectious Diseases, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China.
Xiaohao WangKey Laboratory of Molecular Biology for Infectious Diseases (Ministry of Education), Institute for Viral Hepatitis, The Second Affiliated Hospital, Chongqing Medical University, Chongqing, China. xiaohao_wang@foxmail.com.
Dalian Medical University · CNChongqing Medical University · CNSecond Affiliated Hospital of Chongqing Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sepsis is a potentially fatal condition caused by infection. It is frequently difficult to distinguish sepsis from systemic inflammatory response syndrome (SIRS), often resulting in poor prognoses and the misuse of antibiotics. Hence, highly sensitive and specific biomarkers are needed to differentiate sepsis from SIRS. Urine samples were collected and segregated by group (a sepsis group, a SIRS group, and a healthy control group). iTRAQ was used to identify the differentially expressed proteins among the three groups. The identified proteins were measured by ELISA in urine samples. Finally, all the acquired data were analyzed in SPSS. C-reactive protein, leucine-rich alpha glycoprotein-1 and serum amyloid A (SAA) protein were differentially expressed among the three groups. The adjusted median concentrations of urinary C-reactive protein were 1337.6, 358.7, and 2.4 in the sepsis, SIRS, and healthy control groups, respectively. The urinary leucine-rich alpha glycoprotein-1 levels in these three groups were 1614.4, 644.5, and 13.6, respectively, and the levels of SAA were 6.3, 2.9, and 0.07, respectively. For all three of these measures, the sepsis group had higher levels than the SIRS group (P < 0.001), and the SIRS group had higher levels than the healthy control group. When combined, the three biomarkers had a sensitivity of 0.906 and a specificity of 0.896 in distinguishing sepsis from SIRS. Urinary C-reactive protein, urinary leucine-rich alpha glycoprotein-1 and urinary SAA have diagnostic value in cases of sepsis. This initial study suggests the possibility of improved differential diagnosis between sepsis and systemic inflammatory response syndrome; additional confirmation is necessary to corroborate the findings.

Indexed as

AgedBiomarkersCase-Control StudiesDiagnosis, DifferentialEnzyme-Linked Immunosorbent AssayFemaleHumansMaleMiddle AgedSensitivity and SpecificitySepsisSystemic Inflammatory Response SyndromeBiomarkers

Identifiers

PMID34675320
PMCPMC8531286
OpenAlexW3205932347

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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.