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Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study
The aim of this study was to analyze the current situation and risk factors of multi-drug-resistant organism (MDRO) infection in Neuro-intensive care unit (ICU) patients, and to develop the risk predict model. The data was collected from the patients discharged from Neuro-ICU of grade-A tertiary hos...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504308/ https://www.ncbi.nlm.nih.gov/pubmed/37714922 http://dx.doi.org/10.1038/s41598-023-42522-2 |
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author | Jiang, Hu Pu, Hengping Huang, Nanqu |
author_facet | Jiang, Hu Pu, Hengping Huang, Nanqu |
author_sort | Jiang, Hu |
collection | PubMed |
description | The aim of this study was to analyze the current situation and risk factors of multi-drug-resistant organism (MDRO) infection in Neuro-intensive care unit (ICU) patients, and to develop the risk predict model. The data was collected from the patients discharged from Neuro-ICU of grade-A tertiary hospital at Guizhou province from January 2018 to April 2020. Binary Logistics regression was used to analyze the data. The model was examined by receiver operating characteristic curve (ROC). The grouped data was used to verify the sensitivity and specificity of the model. A total of 297 patients were included, 131 patients infected with MDRO. The infection rate was 44.11%. The results of binary Logistics regression showed that tracheal intubation, artery blood pressure monitoring, fever, antibiotics, pneumonia were independent risk factors for MDRO infection in Neuro-ICU (P < 0.05), AUC = 0.887. The sensitivity and specificity of ROC curve was 86.3% and 76.9%. The risk prediction model had a good predictive effect on the risk of MDRO infection in Neuro ICU, which can evaluate the risk and provide reference for preventive treatment and nursing intervention. |
format | Online Article Text |
id | pubmed-10504308 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-105043082023-09-17 Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study Jiang, Hu Pu, Hengping Huang, Nanqu Sci Rep Article The aim of this study was to analyze the current situation and risk factors of multi-drug-resistant organism (MDRO) infection in Neuro-intensive care unit (ICU) patients, and to develop the risk predict model. The data was collected from the patients discharged from Neuro-ICU of grade-A tertiary hospital at Guizhou province from January 2018 to April 2020. Binary Logistics regression was used to analyze the data. The model was examined by receiver operating characteristic curve (ROC). The grouped data was used to verify the sensitivity and specificity of the model. A total of 297 patients were included, 131 patients infected with MDRO. The infection rate was 44.11%. The results of binary Logistics regression showed that tracheal intubation, artery blood pressure monitoring, fever, antibiotics, pneumonia were independent risk factors for MDRO infection in Neuro-ICU (P < 0.05), AUC = 0.887. The sensitivity and specificity of ROC curve was 86.3% and 76.9%. The risk prediction model had a good predictive effect on the risk of MDRO infection in Neuro ICU, which can evaluate the risk and provide reference for preventive treatment and nursing intervention. Nature Publishing Group UK 2023-09-15 /pmc/articles/PMC10504308/ /pubmed/37714922 http://dx.doi.org/10.1038/s41598-023-42522-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Jiang, Hu Pu, Hengping Huang, Nanqu Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study |
title | Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study |
title_full | Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study |
title_fullStr | Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study |
title_full_unstemmed | Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study |
title_short | Risk predict model using multi-drug resistant organism infection from Neuro-ICU patients: a retrospective cohort study |
title_sort | risk predict model using multi-drug resistant organism infection from neuro-icu patients: a retrospective cohort study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10504308/ https://www.ncbi.nlm.nih.gov/pubmed/37714922 http://dx.doi.org/10.1038/s41598-023-42522-2 |
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