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

Authors :
Jiao Y
Wai Tong CS
Rainer TH
Source :
Heliyon [Heliyon] 2023 Jun 28; Vol. 9 (7), pp. e17770. Date of Electronic Publication: 2023 Jun 28 (Print Publication: 2023).
Publication Year :
2023

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.<br />Methods: We searched PubMed from 2012 to July 2022 using "((sepsis) AND (mice)) AND ((prognosis) OR (prognostic biomarker))".<br />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.<br />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.<br />Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (© 2023 The Authors.)

Details

Language :
English
ISSN :
2405-8440
Volume :
9
Issue :
7
Database :
MEDLINE
Journal :
Heliyon
Publication Type :
Academic Journal
Accession number :
37456011
Full Text :
https://doi.org/10.1016/j.heliyon.2023.e17770