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A novel nomogram for predicting risk of malnutrition in patients with heart failure
BACKGROUND AND AIMS: This study aimed to explore the risk factors of malnutrition in patients with heart failure and construct a novel nomogram model. METHODS AND RESULTS: A cross-sectional study based on the STROBE checklist. Patients with heart failure from July 2020 to August 2021 were included....
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076782/ https://www.ncbi.nlm.nih.gov/pubmed/37034317 http://dx.doi.org/10.3389/fcvm.2023.1162035 |
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author | Liu, Jian Xu, Shengjia Wang, Jiurui Liu, Jing Yan, Zeping Liang, Qian Luan, Xiaorong |
author_facet | Liu, Jian Xu, Shengjia Wang, Jiurui Liu, Jing Yan, Zeping Liang, Qian Luan, Xiaorong |
author_sort | Liu, Jian |
collection | PubMed |
description | BACKGROUND AND AIMS: This study aimed to explore the risk factors of malnutrition in patients with heart failure and construct a novel nomogram model. METHODS AND RESULTS: A cross-sectional study based on the STROBE checklist. Patients with heart failure from July 2020 to August 2021 were included. Patients were divided into a malnutrition group and a normal nutrition group based on the Society's recommended AND-ASPEN standard. Logistic regression was used to analyze the independent risk factors for malnutrition. A new prediction model of nomogram was constructed based on the risk factors, and its fit and prediction performance were evaluated. Of 433 patients, 66 (15.2%) had malnutrition and 367 (84.8%) had normal nutrition, Logistic regression analyses showed that the risk factors for malnutrition were total protein, hemoglobin, triglyceride, and glucose levels. The regression model based on the above four variables showed an area under the curve of 0.858. The novel nomogram model had a sensitivity of 78.5% and a specificity of 77.3%. After 2000 bootstrap resampling iterations, AUC was 0.852. CONCLUSIONS: The novel nomogram model can predict the odds of malnutrition in patients with heart failure at the early stage of admission, and can provide a reference for nursing staff to optimize nutritional care for inpatient with heart failure and to develop a discharge nutritional care plan. |
format | Online Article Text |
id | pubmed-10076782 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100767822023-04-07 A novel nomogram for predicting risk of malnutrition in patients with heart failure Liu, Jian Xu, Shengjia Wang, Jiurui Liu, Jing Yan, Zeping Liang, Qian Luan, Xiaorong Front Cardiovasc Med Cardiovascular Medicine BACKGROUND AND AIMS: This study aimed to explore the risk factors of malnutrition in patients with heart failure and construct a novel nomogram model. METHODS AND RESULTS: A cross-sectional study based on the STROBE checklist. Patients with heart failure from July 2020 to August 2021 were included. Patients were divided into a malnutrition group and a normal nutrition group based on the Society's recommended AND-ASPEN standard. Logistic regression was used to analyze the independent risk factors for malnutrition. A new prediction model of nomogram was constructed based on the risk factors, and its fit and prediction performance were evaluated. Of 433 patients, 66 (15.2%) had malnutrition and 367 (84.8%) had normal nutrition, Logistic regression analyses showed that the risk factors for malnutrition were total protein, hemoglobin, triglyceride, and glucose levels. The regression model based on the above four variables showed an area under the curve of 0.858. The novel nomogram model had a sensitivity of 78.5% and a specificity of 77.3%. After 2000 bootstrap resampling iterations, AUC was 0.852. CONCLUSIONS: The novel nomogram model can predict the odds of malnutrition in patients with heart failure at the early stage of admission, and can provide a reference for nursing staff to optimize nutritional care for inpatient with heart failure and to develop a discharge nutritional care plan. Frontiers Media S.A. 2023-03-23 /pmc/articles/PMC10076782/ /pubmed/37034317 http://dx.doi.org/10.3389/fcvm.2023.1162035 Text en © 2023 Liu, Xu, Wang, Liu, Yan, Liang and Luan. 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) (https://creativecommons.org/licenses/by/4.0/) . 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 | Cardiovascular Medicine Liu, Jian Xu, Shengjia Wang, Jiurui Liu, Jing Yan, Zeping Liang, Qian Luan, Xiaorong A novel nomogram for predicting risk of malnutrition in patients with heart failure |
title | A novel nomogram for predicting risk of malnutrition in patients with heart failure |
title_full | A novel nomogram for predicting risk of malnutrition in patients with heart failure |
title_fullStr | A novel nomogram for predicting risk of malnutrition in patients with heart failure |
title_full_unstemmed | A novel nomogram for predicting risk of malnutrition in patients with heart failure |
title_short | A novel nomogram for predicting risk of malnutrition in patients with heart failure |
title_sort | novel nomogram for predicting risk of malnutrition in patients with heart failure |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076782/ https://www.ncbi.nlm.nih.gov/pubmed/37034317 http://dx.doi.org/10.3389/fcvm.2023.1162035 |
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