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...
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Editorial Office of New Medicine
2024-08-01
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| Series: | Yixue xinzhi zazhi |
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| Online Access: | https://yxxz.whuznhmedj.com/futureApi/storage/attach/2408/W0HSY57FD2UMvTgAZ2tvDeEqZ5BCNuEhE7E7cIum.pdf |
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| _version_ | 1846110383222292480 |
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| 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 |