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Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model

OBJECTIVE: To investigate the prevalence of infections due to carbapenem-resistant Klebsiella pneumoniae (CRKP) among ICU admission patients in central China and develop a reliable prediction model. METHODS: Five hundred and seven consecutive ICU admission patients with Klebsiella pneumoniae (KP) in...

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Autores principales: Li, Yi, Shen, Hui, Zhu, Cheng, Yu, Yuetian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6457282/
https://www.ncbi.nlm.nih.gov/pubmed/31032370
http://dx.doi.org/10.1155/2019/9767313
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author Li, Yi
Shen, Hui
Zhu, Cheng
Yu, Yuetian
author_facet Li, Yi
Shen, Hui
Zhu, Cheng
Yu, Yuetian
author_sort Li, Yi
collection PubMed
description OBJECTIVE: To investigate the prevalence of infections due to carbapenem-resistant Klebsiella pneumoniae (CRKP) among ICU admission patients in central China and develop a reliable prediction model. METHODS: Five hundred and seven consecutive ICU admission patients with Klebsiella pneumoniae (KP) infection were enrolled in this retrospective multicenter case-control study from January 2014 to June 2018. The prevalence and antimicrobial susceptibility pattern were analyzed. Multivariate analysis was performed by logistic regression modeling to determine the risk factors. A prediction model was developed and verified using data from six hospitals in central China. RESULTS: Of the total 507 isolates of KP, 244 (48.1%) strains were carbapenem resistant. The majority of these isolates were from sputum (30.9%) and blood (20.9%) samples. Tigecycline had good activity against CRKP (95.5%). The most common sequence type (ST) of CRKP was ST11 (84.4%), and 98.6% of them had the blaKPC-2 antimicrobial resistance gene. Thirteen variables were identified as independent risk factors for CRKP infection, including KP colonization or infection in the preceding year (OR=3.32, 95% CI 2.01-4.38), CD4/CD8 ratio <1 (OR=2.98, 95% CI 2.02-4.19), and parenteral nutrition ⩾48 h (OR=1.88, 95% CI 1.22-3.04). The model developed to predict CRKP infection was effective, with an area under the receiver-operating characteristic curve of 0.854 (95% CI 0.821-0.884, p<0.001). CONCLUSIONS: ST11 carrying the blaKPC-2 antimicrobial resistance gene was the most common type of CRKP among the ICU admission patients in central China. The model demonstrated excellent predictive performance and exhibited good discrimination.
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spelling pubmed-64572822019-04-28 Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model Li, Yi Shen, Hui Zhu, Cheng Yu, Yuetian Biomed Res Int Research Article OBJECTIVE: To investigate the prevalence of infections due to carbapenem-resistant Klebsiella pneumoniae (CRKP) among ICU admission patients in central China and develop a reliable prediction model. METHODS: Five hundred and seven consecutive ICU admission patients with Klebsiella pneumoniae (KP) infection were enrolled in this retrospective multicenter case-control study from January 2014 to June 2018. The prevalence and antimicrobial susceptibility pattern were analyzed. Multivariate analysis was performed by logistic regression modeling to determine the risk factors. A prediction model was developed and verified using data from six hospitals in central China. RESULTS: Of the total 507 isolates of KP, 244 (48.1%) strains were carbapenem resistant. The majority of these isolates were from sputum (30.9%) and blood (20.9%) samples. Tigecycline had good activity against CRKP (95.5%). The most common sequence type (ST) of CRKP was ST11 (84.4%), and 98.6% of them had the blaKPC-2 antimicrobial resistance gene. Thirteen variables were identified as independent risk factors for CRKP infection, including KP colonization or infection in the preceding year (OR=3.32, 95% CI 2.01-4.38), CD4/CD8 ratio <1 (OR=2.98, 95% CI 2.02-4.19), and parenteral nutrition ⩾48 h (OR=1.88, 95% CI 1.22-3.04). The model developed to predict CRKP infection was effective, with an area under the receiver-operating characteristic curve of 0.854 (95% CI 0.821-0.884, p<0.001). CONCLUSIONS: ST11 carrying the blaKPC-2 antimicrobial resistance gene was the most common type of CRKP among the ICU admission patients in central China. The model demonstrated excellent predictive performance and exhibited good discrimination. Hindawi 2019-03-27 /pmc/articles/PMC6457282/ /pubmed/31032370 http://dx.doi.org/10.1155/2019/9767313 Text en Copyright © 2019 Yi Li et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Li, Yi
Shen, Hui
Zhu, Cheng
Yu, Yuetian
Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model
title Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model
title_full Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model
title_fullStr Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model
title_full_unstemmed Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model
title_short Carbapenem-Resistant Klebsiella pneumoniae Infections among ICU Admission Patients in Central China: Prevalence and Prediction Model
title_sort carbapenem-resistant klebsiella pneumoniae infections among icu admission patients in central china: prevalence and prediction model
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6457282/
https://www.ncbi.nlm.nih.gov/pubmed/31032370
http://dx.doi.org/10.1155/2019/9767313
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