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Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection

Background: Procalcitonin (PCT) is a promising biomarker for predicting infection. Bloodstream infection (BSI) is usually a deteriorating stage of sepsis. The purpose of this study was to explore the predictive value of intense serial PCT assays for BSI in the intensive care unit (ICU). Methods: Thi...

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Autores principales: Jiang, Zhiyi, Liu, Ning, Wang, Luhao, Wu, Jianfeng, Guan, Xiangdong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526537/
https://www.ncbi.nlm.nih.gov/pubmed/34692716
http://dx.doi.org/10.3389/fmed.2021.691793
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author Jiang, Zhiyi
Liu, Ning
Wang, Luhao
Wu, Jianfeng
Guan, Xiangdong
author_facet Jiang, Zhiyi
Liu, Ning
Wang, Luhao
Wu, Jianfeng
Guan, Xiangdong
author_sort Jiang, Zhiyi
collection PubMed
description Background: Procalcitonin (PCT) is a promising biomarker for predicting infection. Bloodstream infection (BSI) is usually a deteriorating stage of sepsis. The purpose of this study was to explore the predictive value of intense serial PCT assays for BSI in the intensive care unit (ICU). Methods: This study was a retrospective study based on a clinical database. We analyzed the data of critically ill patients from February 2016 to May 2020. The patients who received PCT assays and blood cultures (BCs) were classified into four groups according to the BCs: (i) BC negative, (ii) bacteria positive, (iii) fungi-positive, and (iv) combined-positive, and the patients with bacteremia were further subdivided into Gram+ and Gram– bacteremia. Results: The database included 11,219 patients. There were 3,593 patients who met the criteria for the analysis. The PCT concentration differed significantly across BC groups (p < 0.0001). The fluctuation of PCT significantly increased in the BC positive groups (p < 0.0001). According to the receiver operating characteristic (ROC), the optimum cutoff of the fluctuation of PCT was around 8 ng/ml for predicting BSI. Conclusion: Our study indicated that the fluctuation of PCT could be an indicator for screening BSI, but less accurate for Gram-positive infections. With a fluctuation of PCT less than 8 ng/ml, BSI should not be a rational cause for sepsis exacerbating.
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spelling pubmed-85265372021-10-21 Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection Jiang, Zhiyi Liu, Ning Wang, Luhao Wu, Jianfeng Guan, Xiangdong Front Med (Lausanne) Medicine Background: Procalcitonin (PCT) is a promising biomarker for predicting infection. Bloodstream infection (BSI) is usually a deteriorating stage of sepsis. The purpose of this study was to explore the predictive value of intense serial PCT assays for BSI in the intensive care unit (ICU). Methods: This study was a retrospective study based on a clinical database. We analyzed the data of critically ill patients from February 2016 to May 2020. The patients who received PCT assays and blood cultures (BCs) were classified into four groups according to the BCs: (i) BC negative, (ii) bacteria positive, (iii) fungi-positive, and (iv) combined-positive, and the patients with bacteremia were further subdivided into Gram+ and Gram– bacteremia. Results: The database included 11,219 patients. There were 3,593 patients who met the criteria for the analysis. The PCT concentration differed significantly across BC groups (p < 0.0001). The fluctuation of PCT significantly increased in the BC positive groups (p < 0.0001). According to the receiver operating characteristic (ROC), the optimum cutoff of the fluctuation of PCT was around 8 ng/ml for predicting BSI. Conclusion: Our study indicated that the fluctuation of PCT could be an indicator for screening BSI, but less accurate for Gram-positive infections. With a fluctuation of PCT less than 8 ng/ml, BSI should not be a rational cause for sepsis exacerbating. Frontiers Media S.A. 2021-10-06 /pmc/articles/PMC8526537/ /pubmed/34692716 http://dx.doi.org/10.3389/fmed.2021.691793 Text en Copyright © 2021 Jiang, Liu, Wang, Wu and Guan. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Jiang, Zhiyi
Liu, Ning
Wang, Luhao
Wu, Jianfeng
Guan, Xiangdong
Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection
title Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection
title_full Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection
title_fullStr Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection
title_full_unstemmed Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection
title_short Mining of a Clinical Database: The Interpretation of Intense Serial Procalcitonin in the Prediction for Bloodstream Infection
title_sort mining of a clinical database: the interpretation of intense serial procalcitonin in the prediction for bloodstream infection
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526537/
https://www.ncbi.nlm.nih.gov/pubmed/34692716
http://dx.doi.org/10.3389/fmed.2021.691793
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