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Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model
BACKGROUND: Multidrug-resistant organisms (MDROs) have emerged as an important cause of poor prognoses of patients in the intensive care unit (ICU). This study aimed to establish an easy-to-use nomogram for predicting the occurrence of MDRO colonization or infection in ICU patients. METHODS: In this...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236142/ https://www.ncbi.nlm.nih.gov/pubmed/32430043 http://dx.doi.org/10.1186/s13756-020-00726-5 |
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author | Wang, Li Huang, Xiaolong Zhou, Jiating Wang, Yajing Zhong, Weizhang Yu, Qing Wang, Weiping Ye, Zhiqiao Lin, Qiaoyan Hong, Xing Zeng, Ping Zhang, Minwei |
author_facet | Wang, Li Huang, Xiaolong Zhou, Jiating Wang, Yajing Zhong, Weizhang Yu, Qing Wang, Weiping Ye, Zhiqiao Lin, Qiaoyan Hong, Xing Zeng, Ping Zhang, Minwei |
author_sort | Wang, Li |
collection | PubMed |
description | BACKGROUND: Multidrug-resistant organisms (MDROs) have emerged as an important cause of poor prognoses of patients in the intensive care unit (ICU). This study aimed to establish an easy-to-use nomogram for predicting the occurrence of MDRO colonization or infection in ICU patients. METHODS: In this study, we developed a nomogram based on predictors in patients admitted to the ICU in the First Affiliated Hospital of Xiamen University from 2016 to 2018 using univariate and multivariate logistic regression analysis. We externally validated this nomogram in patients from another hospital over a similar period, and assessed its performance by calculating the area under the receiver operating characteristic (ROC) curve (AUC) and performing a decision curve analysis. RESULTS: 331 patients in the primary cohort and 181 patients in the validation cohort were included in the statistical analysis. Independent factors derived from the primary cohort to predict MDRO colonization or infection were male sex, higher C-reactive protein (CRP) levels and higher Pitt bacteremia scores (Pitt scores), which were all assembled in the nomogram. The nomogram yielded good discrimination with an AUC of 0.77 (95% CI 0.70–0.84), and the range of threshold probabilities of decision curves was approximately 30–95%. CONCLUSION: This easy-to-use nomogram is potentially useful for predicting the occurrence of MDRO colonization or infection in ICU patients. |
format | Online Article Text |
id | pubmed-7236142 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-72361422020-05-27 Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model Wang, Li Huang, Xiaolong Zhou, Jiating Wang, Yajing Zhong, Weizhang Yu, Qing Wang, Weiping Ye, Zhiqiao Lin, Qiaoyan Hong, Xing Zeng, Ping Zhang, Minwei Antimicrob Resist Infect Control Research BACKGROUND: Multidrug-resistant organisms (MDROs) have emerged as an important cause of poor prognoses of patients in the intensive care unit (ICU). This study aimed to establish an easy-to-use nomogram for predicting the occurrence of MDRO colonization or infection in ICU patients. METHODS: In this study, we developed a nomogram based on predictors in patients admitted to the ICU in the First Affiliated Hospital of Xiamen University from 2016 to 2018 using univariate and multivariate logistic regression analysis. We externally validated this nomogram in patients from another hospital over a similar period, and assessed its performance by calculating the area under the receiver operating characteristic (ROC) curve (AUC) and performing a decision curve analysis. RESULTS: 331 patients in the primary cohort and 181 patients in the validation cohort were included in the statistical analysis. Independent factors derived from the primary cohort to predict MDRO colonization or infection were male sex, higher C-reactive protein (CRP) levels and higher Pitt bacteremia scores (Pitt scores), which were all assembled in the nomogram. The nomogram yielded good discrimination with an AUC of 0.77 (95% CI 0.70–0.84), and the range of threshold probabilities of decision curves was approximately 30–95%. CONCLUSION: This easy-to-use nomogram is potentially useful for predicting the occurrence of MDRO colonization or infection in ICU patients. BioMed Central 2020-05-19 /pmc/articles/PMC7236142/ /pubmed/32430043 http://dx.doi.org/10.1186/s13756-020-00726-5 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Wang, Li Huang, Xiaolong Zhou, Jiating Wang, Yajing Zhong, Weizhang Yu, Qing Wang, Weiping Ye, Zhiqiao Lin, Qiaoyan Hong, Xing Zeng, Ping Zhang, Minwei Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model |
title | Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model |
title_full | Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model |
title_fullStr | Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model |
title_full_unstemmed | Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model |
title_short | Predicting the occurrence of multidrug-resistant organism colonization or infection in ICU patients: development and validation of a novel multivariate prediction model |
title_sort | predicting the occurrence of multidrug-resistant organism colonization or infection in icu patients: development and validation of a novel multivariate prediction model |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236142/ https://www.ncbi.nlm.nih.gov/pubmed/32430043 http://dx.doi.org/10.1186/s13756-020-00726-5 |
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