Risk factors and prediction model construction for malnutrition in long-term bedridden elderly patients

Objective To explore the risk factors for malnutrition (MN) in elderly patients with long-term bed and to construct a risk prediction model for MN.Methods Elderly patients with long-term bed admitted to the Department of Geriatrics of the Fourth People's Hospital of Yaan from January 2016 to Ja...

Full description

Saved in:
Bibliographic Details
Main Authors: ZHANG Qianwei, YANG Xiao, YANG Xuemei
Format: Article
Language:zho
Published: Editorial Office of New Medicine 2024-08-01
Series:Yixue xinzhi zazhi
Subjects:
Online Access:https://yxxz.whuznhmedj.com/futureApi/storage/attach/2408/W0HSY57FD2UMvTgAZ2tvDeEqZ5BCNuEhE7E7cIum.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1846110383222292480
author ZHANG Qianwei
YANG Xiao
YANG Xuemei
author_facet ZHANG Qianwei
YANG Xiao
YANG Xuemei
author_sort ZHANG Qianwei
collection DOAJ
description Objective To explore the risk factors for malnutrition (MN) in elderly patients with long-term bed and to construct a risk prediction model for MN.Methods Elderly patients with long-term bed admitted to the Department of Geriatrics of the Fourth People's Hospital of Yaan from January 2016 to January 2024 were retrospectively selected, and their clinical data were collected. The elderly patients with long-term bed were randomly divided into training set and validation set, according to the ratio of 7∶3. The patients were divided into MN group and non-MN group according to whether MN occurred. In the training set, the differences in clinical data between the groups were compared by univariate analysis (t-test, chi-square test or Fisher's exact test), and the risk factors for MN in patients were analyzed by stepwise multivariate Logistic regression, and a risk prediction model was constructed. The predictive efficiency of the risk prediction model was evaluated and verified by the receiver operating characteristic curve (ROC) and ROC area under curve (AUC), calibration curve and decision curve.Results A total of 896 elderly patients with long-term bed were included, and the incidence of MN was 46.43%. There were 627 cases in the training set and 269 cases in the validation set. Multivariate Logistic regression analysis showed that long bed rest time [OR=1.259, 95%CI (1.197, 1.324)], stroke [OR=2.866, 95%CI (1.621, 5.067)], and anemia [OR=2.479, 95%CI (1.162, 5.288)] were risk factors for MN in elderly patients with long-term bed, and high Barthel index score [OR=0.921, 95%CI (0.905, 0.938)] was a protective factor (P
format Article
id doaj-art-2ec9eeb4909f48c9a66169cfae4a38ec
institution Kabale University
issn 1004-5511
language zho
publishDate 2024-08-01
publisher Editorial Office of New Medicine
record_format Article
series Yixue xinzhi zazhi
spelling doaj-art-2ec9eeb4909f48c9a66169cfae4a38ec2024-12-24T08:38:45ZzhoEditorial Office of New MedicineYixue xinzhi zazhi1004-55112024-08-0134888889610.12173/j.issn.1004-5511.2024050166522Risk factors and prediction model construction for malnutrition in long-term bedridden elderly patientsZHANG QianweiYANG XiaoYANG XuemeiObjective To explore the risk factors for malnutrition (MN) in elderly patients with long-term bed and to construct a risk prediction model for MN.Methods Elderly patients with long-term bed admitted to the Department of Geriatrics of the Fourth People's Hospital of Yaan from January 2016 to January 2024 were retrospectively selected, and their clinical data were collected. The elderly patients with long-term bed were randomly divided into training set and validation set, according to the ratio of 7∶3. The patients were divided into MN group and non-MN group according to whether MN occurred. In the training set, the differences in clinical data between the groups were compared by univariate analysis (t-test, chi-square test or Fisher's exact test), and the risk factors for MN in patients were analyzed by stepwise multivariate Logistic regression, and a risk prediction model was constructed. The predictive efficiency of the risk prediction model was evaluated and verified by the receiver operating characteristic curve (ROC) and ROC area under curve (AUC), calibration curve and decision curve.Results A total of 896 elderly patients with long-term bed were included, and the incidence of MN was 46.43%. There were 627 cases in the training set and 269 cases in the validation set. Multivariate Logistic regression analysis showed that long bed rest time [OR=1.259, 95%CI (1.197, 1.324)], stroke [OR=2.866, 95%CI (1.621, 5.067)], and anemia [OR=2.479, 95%CI (1.162, 5.288)] were risk factors for MN in elderly patients with long-term bed, and high Barthel index score [OR=0.921, 95%CI (0.905, 0.938)] was a protective factor (Phttps://yxxz.whuznhmedj.com/futureApi/storage/attach/2408/W0HSY57FD2UMvTgAZ2tvDeEqZ5BCNuEhE7E7cIum.pdflong-term bedmalnutritionstrokeanemiabarthel indexrisk factorspredictive model
spellingShingle ZHANG Qianwei
YANG Xiao
YANG Xuemei
Risk factors and prediction model construction for malnutrition in long-term bedridden elderly patients
Yixue xinzhi zazhi
long-term bed
malnutrition
stroke
anemia
barthel index
risk factors
predictive model
title Risk factors and prediction model construction for malnutrition in long-term bedridden elderly patients
title_full Risk factors and prediction model construction for malnutrition in long-term bedridden elderly patients
title_fullStr Risk factors and prediction model construction for malnutrition in long-term bedridden elderly patients
title_full_unstemmed Risk factors and prediction model construction for malnutrition in long-term bedridden elderly patients
title_short Risk factors and prediction model construction for malnutrition in long-term bedridden elderly patients
title_sort risk factors and prediction model construction for malnutrition in long term bedridden elderly patients
topic long-term bed
malnutrition
stroke
anemia
barthel index
risk factors
predictive model
url https://yxxz.whuznhmedj.com/futureApi/storage/attach/2408/W0HSY57FD2UMvTgAZ2tvDeEqZ5BCNuEhE7E7cIum.pdf
work_keys_str_mv AT zhangqianwei riskfactorsandpredictionmodelconstructionformalnutritioninlongtermbedriddenelderlypatients
AT yangxiao riskfactorsandpredictionmodelconstructionformalnutritioninlongtermbedriddenelderlypatients
AT yangxuemei riskfactorsandpredictionmodelconstructionformalnutritioninlongtermbedriddenelderlypatients