Evidence map›Paper›PMID 37456011›Full record

ReviewHeliyon2023

An appraisal of studies using mouse models to assist the biomarker discovery for sepsis prognosis.

Yaqing Jiao, Cindy See Wai Tong, Timothy H Rainer

Open access · goldAbstract readReview
In one paragraph

Review in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.7field-weighted citation impact, top 15% 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

2 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
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 1 institution in 1 country.

Yaqing JiaoDepartment of Emergency Medicine, School of Clinical Medicine, The University of Hong Kong, China.
Cindy See Wai TongDepartment of Emergency Medicine, School of Clinical Medicine, The University of Hong Kong, China.
Timothy H RainerDepartment of Emergency Medicine, School of Clinical Medicine, The University of Hong Kong, China.
Chinese University of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Clinicians need reliable outcome predictors to improve the prognosis of septic patients. Mouse models are widely used in sepsis research. We aimed to review how mouse models were used to search for novel prognostic biomarkers of sepsis in order to optimize their use for future biomarker discovery. Methods: We searched PubMed from 2012 to July 2022 using "((sepsis) AND (mice)) AND ((prognosis) OR (prognostic biomarker))". Results: A total of 412 publications were retrieved. We selected those studies in which mouse sepsis was used to demonstrate prognostic potential of biomarker candidates and/or assist the subsequent evaluation in human sepsis for further appraisal. The most frequent models were lipopolysaccharide (LPS) injection and caecal ligation and puncture (CLP) using young male mice. Discovery technologies applied on mice include setting survival and nonsurvivable groups, detecting changes of biomarker levels and measuring physiological parameters during sepsis. None of the biomarkers achieved sufficient clinical performance for clinical use. Conclusions: The number of studies and strategies using mouse models to discover prognostic biomarkers of sepsis are limited. Current mouse models need to be further optimized to better conform to human sepsis. Current biomarker platforms do not achieve predictive performance for clinical use.

Indexed as

MicePrognosisPrognostic biomarkerSepsis

Identifiers

PMID37456011
PMCPMC10344760
OpenAlexW4382358134

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.