Cargando…

Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria

Background: Early recognition of septic patients with poor prognosis is important for clinicians to prescribe personalized therapies which include timely fluid resuscitation therapy and appropriate antimicrobial therapy. We aimed to evaluate the effect of the presepsin level on predicting the progno...

Descripción completa

Detalles Bibliográficos
Autores principales: Wen, Miao-Yun, Huang, Lin-Qiang, Yang, Fan, Ye, Jing-Kun, Cai, Geng-Xin, Li, Xu-Sheng, Ding, Hong-Guang, Zeng, Hong-Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580121/
https://www.ncbi.nlm.nih.gov/pubmed/31354281
http://dx.doi.org/10.2147/TCRM.S209710
_version_ 1783427974481051648
author Wen, Miao-Yun
Huang, Lin-Qiang
Yang, Fan
Ye, Jing-Kun
Cai, Geng-Xin
Li, Xu-Sheng
Ding, Hong-Guang
Zeng, Hong-Ke
author_facet Wen, Miao-Yun
Huang, Lin-Qiang
Yang, Fan
Ye, Jing-Kun
Cai, Geng-Xin
Li, Xu-Sheng
Ding, Hong-Guang
Zeng, Hong-Ke
author_sort Wen, Miao-Yun
collection PubMed
description Background: Early recognition of septic patients with poor prognosis is important for clinicians to prescribe personalized therapies which include timely fluid resuscitation therapy and appropriate antimicrobial therapy. We aimed to evaluate the effect of the presepsin level on predicting the prognosis of patients with sepsis under the sepsis-3 criteria. Methods: Patients who were diagnosed as sepsis under the sepsis-3 criteria were recruited and assigned to the survivor group and the non-survivor group according to their in-hospital mortality. The two groups’ baseline characteristics were analyzed with Pearson’s chi-square (χ(2)) test or Kruskal–Wallis test. Binary logistic regression analysis was performed to determine the independent predictors of in-hospital mortality from sepsis. Receiver operating characteristic analysis was conducted to evaluate the efficacy of presepsin in predicting patients’ in-hospital mortality from sepsis. The correlation between presepsin and the Sequential Organ Failure Assessment (SOFA) score was measured with Spearman’s rank correlation coefficient. P-values of less than 0.05 were considered to indicate statistical significance. Results: Overall, 138 patients were included in this study. The presepsin level of the non-survivor group was significantly higher than that of the other group (P=0.000). Binary logistic regression showed that the presepsin level was an independent risk factor of patients’ in-hospital mortality from sepsis (OR =1.221 P=0.026). The presepsin level was positively associated with the SOFA score (ρ=0.396, P=0.000). ROC curve analysis revealed the presepsin level was highly accurate in predicting patients’ in-hospital mortality from sepsis (AUC =0.703, P=0.000). The AUC value of a combination of presepsin and the SOFA score was significantly larger than that of the SOFA score alone (AUC: 0.817 vs 0.793, P=0.041). Conclusions: Presepsin is a prognostic biomarker with high accuracy in predicting the prognosis of sepsis under the sepsis-3 criteria.
format Online
Article
Text
id pubmed-6580121
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Dove
record_format MEDLINE/PubMed
spelling pubmed-65801212019-07-26 Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria Wen, Miao-Yun Huang, Lin-Qiang Yang, Fan Ye, Jing-Kun Cai, Geng-Xin Li, Xu-Sheng Ding, Hong-Guang Zeng, Hong-Ke Ther Clin Risk Manag Original Research Background: Early recognition of septic patients with poor prognosis is important for clinicians to prescribe personalized therapies which include timely fluid resuscitation therapy and appropriate antimicrobial therapy. We aimed to evaluate the effect of the presepsin level on predicting the prognosis of patients with sepsis under the sepsis-3 criteria. Methods: Patients who were diagnosed as sepsis under the sepsis-3 criteria were recruited and assigned to the survivor group and the non-survivor group according to their in-hospital mortality. The two groups’ baseline characteristics were analyzed with Pearson’s chi-square (χ(2)) test or Kruskal–Wallis test. Binary logistic regression analysis was performed to determine the independent predictors of in-hospital mortality from sepsis. Receiver operating characteristic analysis was conducted to evaluate the efficacy of presepsin in predicting patients’ in-hospital mortality from sepsis. The correlation between presepsin and the Sequential Organ Failure Assessment (SOFA) score was measured with Spearman’s rank correlation coefficient. P-values of less than 0.05 were considered to indicate statistical significance. Results: Overall, 138 patients were included in this study. The presepsin level of the non-survivor group was significantly higher than that of the other group (P=0.000). Binary logistic regression showed that the presepsin level was an independent risk factor of patients’ in-hospital mortality from sepsis (OR =1.221 P=0.026). The presepsin level was positively associated with the SOFA score (ρ=0.396, P=0.000). ROC curve analysis revealed the presepsin level was highly accurate in predicting patients’ in-hospital mortality from sepsis (AUC =0.703, P=0.000). The AUC value of a combination of presepsin and the SOFA score was significantly larger than that of the SOFA score alone (AUC: 0.817 vs 0.793, P=0.041). Conclusions: Presepsin is a prognostic biomarker with high accuracy in predicting the prognosis of sepsis under the sepsis-3 criteria. Dove 2019-06-13 /pmc/articles/PMC6580121/ /pubmed/31354281 http://dx.doi.org/10.2147/TCRM.S209710 Text en © 2019 Wen et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Wen, Miao-Yun
Huang, Lin-Qiang
Yang, Fan
Ye, Jing-Kun
Cai, Geng-Xin
Li, Xu-Sheng
Ding, Hong-Guang
Zeng, Hong-Ke
Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria
title Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria
title_full Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria
title_fullStr Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria
title_full_unstemmed Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria
title_short Presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria
title_sort presepsin level in predicting patients’ in-hospital mortality from sepsis under sepsis-3 criteria
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6580121/
https://www.ncbi.nlm.nih.gov/pubmed/31354281
http://dx.doi.org/10.2147/TCRM.S209710
work_keys_str_mv AT wenmiaoyun presepsinlevelinpredictingpatientsinhospitalmortalityfromsepsisundersepsis3criteria
AT huanglinqiang presepsinlevelinpredictingpatientsinhospitalmortalityfromsepsisundersepsis3criteria
AT yangfan presepsinlevelinpredictingpatientsinhospitalmortalityfromsepsisundersepsis3criteria
AT yejingkun presepsinlevelinpredictingpatientsinhospitalmortalityfromsepsisundersepsis3criteria
AT caigengxin presepsinlevelinpredictingpatientsinhospitalmortalityfromsepsisundersepsis3criteria
AT lixusheng presepsinlevelinpredictingpatientsinhospitalmortalityfromsepsisundersepsis3criteria
AT dinghongguang presepsinlevelinpredictingpatientsinhospitalmortalityfromsepsisundersepsis3criteria
AT zenghongke presepsinlevelinpredictingpatientsinhospitalmortalityfromsepsisundersepsis3criteria