Cargando…

Prediction of sepsis in trauma patients

Trauma is one of the leading causes of death worldwide. Approximately 39.5% of deaths occur in the hospital, and the mortality rate of delayed death caused by septic complications is still high. Early prediction of the development of sepsis can help promote early intervention and treatment for patie...

Descripción completa

Detalles Bibliográficos
Autores principales: Jin, He, Liu, Zheng, Xiao, Ya, Fan, Xia, Yan, Jun, Liang, Huaping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012019/
https://www.ncbi.nlm.nih.gov/pubmed/27602370
http://dx.doi.org/10.4103/2321-3868.135479
_version_ 1782451939644014592
author Jin, He
Liu, Zheng
Xiao, Ya
Fan, Xia
Yan, Jun
Liang, Huaping
author_facet Jin, He
Liu, Zheng
Xiao, Ya
Fan, Xia
Yan, Jun
Liang, Huaping
author_sort Jin, He
collection PubMed
description Trauma is one of the leading causes of death worldwide. Approximately 39.5% of deaths occur in the hospital, and the mortality rate of delayed death caused by septic complications is still high. Early prediction of the development of sepsis can help promote early intervention and treatment for patients and contribute to improving patient outcomes. Thus so far, biomarkers, patient demographics and injury characteristics are the main methods used for predicting sepsis in trauma patients. However, studies that verify their predictive value are limited, and the results are still controversial. More work should be conducted to explore more efficient and accurate ways to predict post-traumatic sepsis.
format Online
Article
Text
id pubmed-5012019
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-50120192016-09-07 Prediction of sepsis in trauma patients Jin, He Liu, Zheng Xiao, Ya Fan, Xia Yan, Jun Liang, Huaping Burns Trauma Review Article Trauma is one of the leading causes of death worldwide. Approximately 39.5% of deaths occur in the hospital, and the mortality rate of delayed death caused by septic complications is still high. Early prediction of the development of sepsis can help promote early intervention and treatment for patients and contribute to improving patient outcomes. Thus so far, biomarkers, patient demographics and injury characteristics are the main methods used for predicting sepsis in trauma patients. However, studies that verify their predictive value are limited, and the results are still controversial. More work should be conducted to explore more efficient and accurate ways to predict post-traumatic sepsis. BioMed Central 2014-07-28 /pmc/articles/PMC5012019/ /pubmed/27602370 http://dx.doi.org/10.4103/2321-3868.135479 Text en © Author 2014 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, duplication, adaptation, distribution, and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made
spellingShingle Review Article
Jin, He
Liu, Zheng
Xiao, Ya
Fan, Xia
Yan, Jun
Liang, Huaping
Prediction of sepsis in trauma patients
title Prediction of sepsis in trauma patients
title_full Prediction of sepsis in trauma patients
title_fullStr Prediction of sepsis in trauma patients
title_full_unstemmed Prediction of sepsis in trauma patients
title_short Prediction of sepsis in trauma patients
title_sort prediction of sepsis in trauma patients
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5012019/
https://www.ncbi.nlm.nih.gov/pubmed/27602370
http://dx.doi.org/10.4103/2321-3868.135479
work_keys_str_mv AT jinhe predictionofsepsisintraumapatients
AT liuzheng predictionofsepsisintraumapatients
AT xiaoya predictionofsepsisintraumapatients
AT fanxia predictionofsepsisintraumapatients
AT yanjun predictionofsepsisintraumapatients
AT lianghuaping predictionofsepsisintraumapatients