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An early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in China
BACKGROUND: Previous reports suggest that the attributes of frailty are multidimensional and include nutrition, cognition, mentality, and other aspects. We aim to develop an early warning model of frailty based on nutritional risk screening and apply the frailty early warning model in the clinic to...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371757/ https://www.ncbi.nlm.nih.gov/pubmed/34407755 http://dx.doi.org/10.1186/s12877-021-02396-3 |
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author | Liu, Hongpeng Jiao, Jing Zhu, Minglei Wen, Xianxiu Jin, Jingfen Wang, Hui Lv, Dongmei Zhao, Shengxiu Chen, Wei Wu, Xinjuan Xu, Tao |
author_facet | Liu, Hongpeng Jiao, Jing Zhu, Minglei Wen, Xianxiu Jin, Jingfen Wang, Hui Lv, Dongmei Zhao, Shengxiu Chen, Wei Wu, Xinjuan Xu, Tao |
author_sort | Liu, Hongpeng |
collection | PubMed |
description | BACKGROUND: Previous reports suggest that the attributes of frailty are multidimensional and include nutrition, cognition, mentality, and other aspects. We aim to develop an early warning model of frailty based on nutritional risk screening and apply the frailty early warning model in the clinic to screen high-risk patients and provide corresponding intervention target information. METHODS: The proposed study includes two stages. In the first stage, we aim to develop a prediction model of frailty among older inpatients with nutritional risk. Study data were collected from a population-based aging cohort study in China. A prospective cohort study design will be used in the second stage of the study. We will recruit 266 older inpatients (age 65 years or older) with nutritional risk, and we will apply the frailty model in the clinic to explore the predictive ability of the model in participants, assess patients’ health outcomes with implementation of the frailty model, and compare the model with existing frailty assessment tools. Patients’ health outcomes will be measured at admission and at 30-day follow-up. DISCUSSION: This project is the first to develop an early prediction model of frailty for older inpatients according to nutritional risk in a nationally representative sample of Chinese older inpatients of tertiary hospitals. The results will hopefully help to promote the development of more detailed frailty assessment tools according to nutritional risk, which may ultimately lead to reduced health care costs and improvement in independence and quality of life among geriatric patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR1800017682, registered August 9, 2018; and ChiCTR2100044148, registered March 11, 2021. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-021-02396-3. |
format | Online Article Text |
id | pubmed-8371757 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-83717572021-08-18 An early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in China Liu, Hongpeng Jiao, Jing Zhu, Minglei Wen, Xianxiu Jin, Jingfen Wang, Hui Lv, Dongmei Zhao, Shengxiu Chen, Wei Wu, Xinjuan Xu, Tao BMC Geriatr Study Protocol BACKGROUND: Previous reports suggest that the attributes of frailty are multidimensional and include nutrition, cognition, mentality, and other aspects. We aim to develop an early warning model of frailty based on nutritional risk screening and apply the frailty early warning model in the clinic to screen high-risk patients and provide corresponding intervention target information. METHODS: The proposed study includes two stages. In the first stage, we aim to develop a prediction model of frailty among older inpatients with nutritional risk. Study data were collected from a population-based aging cohort study in China. A prospective cohort study design will be used in the second stage of the study. We will recruit 266 older inpatients (age 65 years or older) with nutritional risk, and we will apply the frailty model in the clinic to explore the predictive ability of the model in participants, assess patients’ health outcomes with implementation of the frailty model, and compare the model with existing frailty assessment tools. Patients’ health outcomes will be measured at admission and at 30-day follow-up. DISCUSSION: This project is the first to develop an early prediction model of frailty for older inpatients according to nutritional risk in a nationally representative sample of Chinese older inpatients of tertiary hospitals. The results will hopefully help to promote the development of more detailed frailty assessment tools according to nutritional risk, which may ultimately lead to reduced health care costs and improvement in independence and quality of life among geriatric patients. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR1800017682, registered August 9, 2018; and ChiCTR2100044148, registered March 11, 2021. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12877-021-02396-3. BioMed Central 2021-08-18 /pmc/articles/PMC8371757/ /pubmed/34407755 http://dx.doi.org/10.1186/s12877-021-02396-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/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/ (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 | Study Protocol Liu, Hongpeng Jiao, Jing Zhu, Minglei Wen, Xianxiu Jin, Jingfen Wang, Hui Lv, Dongmei Zhao, Shengxiu Chen, Wei Wu, Xinjuan Xu, Tao An early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in China |
title | An early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in China |
title_full | An early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in China |
title_fullStr | An early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in China |
title_full_unstemmed | An early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in China |
title_short | An early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in China |
title_sort | early predictive model of frailty for older inpatients according to nutritional risk: protocol for a cohort study in china |
topic | Study Protocol |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8371757/ https://www.ncbi.nlm.nih.gov/pubmed/34407755 http://dx.doi.org/10.1186/s12877-021-02396-3 |
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