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Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients
BACKGROUND: Protein-energy wasting (PEW) has been reported to be pretty common in maintenance dialysis patients. However, the existing PEW diagnostic standard is limited in clinical use due to the complexity of it. Bioelectrical impedance analysis (BIA), as a non-invasive nutritional assessment meth...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10633946/ https://www.ncbi.nlm.nih.gov/pubmed/37940938 http://dx.doi.org/10.1186/s12937-023-00890-5 |
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author | Wang, Weina Meng, Xinxuan Liu, Jiaojiao Lou, Xiaowei Zhang, Ping He, Peipei Chen, Jianghua Yuan, Jing |
author_facet | Wang, Weina Meng, Xinxuan Liu, Jiaojiao Lou, Xiaowei Zhang, Ping He, Peipei Chen, Jianghua Yuan, Jing |
author_sort | Wang, Weina |
collection | PubMed |
description | BACKGROUND: Protein-energy wasting (PEW) has been reported to be pretty common in maintenance dialysis patients. However, the existing PEW diagnostic standard is limited in clinical use due to the complexity of it. Bioelectrical impedance analysis (BIA), as a non-invasive nutritional assessment method, can objectively and quantitatively analyze the changes of body tissue components under different nutritional states. We aim to explore the association between PEW and BIA and establish a reliable diagnostic model of PEW. METHODS: We collected cross-sectional data of 609 maintenance dialysis patients at the First Affiliated Hospital, College of Medicine, Zhejiang University. PEW was diagnosed according to International Society of Renal Nutrition and Metabolism (ISRNM) criteria. Among them, 448 consecutive patients were included in the training set for the establishment of a diagnostic nomogram. 161 consecutive patients were included for internal validation. 52 patients from Zhejiang Hospital were included for external validation of the diagnostic model. Correlation analysis of BIA indexes with other nutritional indicators was performed. Logistic regression was used to examine the association of BIA indexes with PEW. 12 diagnostic models of PEW in maintenance dialysis patients were developed and the performance of them in terms of discrimination and calibration was evaluated using C statistics and Hosmer–Lemeshow-type χ2 statistics. After comparing to existing diagnostic models, and performing both internal and external validation, we finally established a simple but reliable PEW diagnostic model which may have great value of clinical application. RESULTS: A total of 609 individuals from First Affiliated Hospital, College of Medicine, Zhejiang University and 52 individuals from Zhejiang Hospital were included. After full adjustment, age, peritoneal dialysis (compared to hemodialysis), subjective global assessment (SGA, compared to non-SGA) and water ratio were independent risk factors, while triglyceride, urea nitrogen, calcium, ferritin, BCM, VFA and phase angle were independent protective factors of PEW. The model incorporated water ratio, VFA, BCM, phase angle and cholesterol revealed best performance. A nomogram was developed according to the results of model performance. The model achieved high C-indexes of 0.843 in the training set, 0.841 and 0.829 in the internal and external validation sets, respectively, and had a well-fitted calibration curve. The net reclassification improvement (NRI) showed 8%, 13%, 2%, 38%, 36% improvement of diagnostic accuracy of our model compared with “PEW score model”, “modified PEW score model”, “3-index model”, “SGA model” and “BIA decision tree model”, respectively. CONCLUSIONS: BIA can be used as an auxiliary tool to evaluate PEW risk and may have certain clinical application value. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12937-023-00890-5. |
format | Online Article Text |
id | pubmed-10633946 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-106339462023-11-10 Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients Wang, Weina Meng, Xinxuan Liu, Jiaojiao Lou, Xiaowei Zhang, Ping He, Peipei Chen, Jianghua Yuan, Jing Nutr J Research BACKGROUND: Protein-energy wasting (PEW) has been reported to be pretty common in maintenance dialysis patients. However, the existing PEW diagnostic standard is limited in clinical use due to the complexity of it. Bioelectrical impedance analysis (BIA), as a non-invasive nutritional assessment method, can objectively and quantitatively analyze the changes of body tissue components under different nutritional states. We aim to explore the association between PEW and BIA and establish a reliable diagnostic model of PEW. METHODS: We collected cross-sectional data of 609 maintenance dialysis patients at the First Affiliated Hospital, College of Medicine, Zhejiang University. PEW was diagnosed according to International Society of Renal Nutrition and Metabolism (ISRNM) criteria. Among them, 448 consecutive patients were included in the training set for the establishment of a diagnostic nomogram. 161 consecutive patients were included for internal validation. 52 patients from Zhejiang Hospital were included for external validation of the diagnostic model. Correlation analysis of BIA indexes with other nutritional indicators was performed. Logistic regression was used to examine the association of BIA indexes with PEW. 12 diagnostic models of PEW in maintenance dialysis patients were developed and the performance of them in terms of discrimination and calibration was evaluated using C statistics and Hosmer–Lemeshow-type χ2 statistics. After comparing to existing diagnostic models, and performing both internal and external validation, we finally established a simple but reliable PEW diagnostic model which may have great value of clinical application. RESULTS: A total of 609 individuals from First Affiliated Hospital, College of Medicine, Zhejiang University and 52 individuals from Zhejiang Hospital were included. After full adjustment, age, peritoneal dialysis (compared to hemodialysis), subjective global assessment (SGA, compared to non-SGA) and water ratio were independent risk factors, while triglyceride, urea nitrogen, calcium, ferritin, BCM, VFA and phase angle were independent protective factors of PEW. The model incorporated water ratio, VFA, BCM, phase angle and cholesterol revealed best performance. A nomogram was developed according to the results of model performance. The model achieved high C-indexes of 0.843 in the training set, 0.841 and 0.829 in the internal and external validation sets, respectively, and had a well-fitted calibration curve. The net reclassification improvement (NRI) showed 8%, 13%, 2%, 38%, 36% improvement of diagnostic accuracy of our model compared with “PEW score model”, “modified PEW score model”, “3-index model”, “SGA model” and “BIA decision tree model”, respectively. CONCLUSIONS: BIA can be used as an auxiliary tool to evaluate PEW risk and may have certain clinical application value. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12937-023-00890-5. BioMed Central 2023-11-09 /pmc/articles/PMC10633946/ /pubmed/37940938 http://dx.doi.org/10.1186/s12937-023-00890-5 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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, Weina Meng, Xinxuan Liu, Jiaojiao Lou, Xiaowei Zhang, Ping He, Peipei Chen, Jianghua Yuan, Jing Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients |
title | Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients |
title_full | Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients |
title_fullStr | Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients |
title_full_unstemmed | Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients |
title_short | Study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients |
title_sort | study on the correlation between bioelectrical impedance analysis index and protein energy consumption in maintenance dialysis patients |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10633946/ https://www.ncbi.nlm.nih.gov/pubmed/37940938 http://dx.doi.org/10.1186/s12937-023-00890-5 |
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