1. Factors and predictive model for malnutrition in poststroke disabled patients: A multicenter cross-sectional study.
- Author
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Zeng H, Cai A, Zhao W, Wu J, Ding Y, and Zeng X
- Subjects
- Humans, Cross-Sectional Studies, Female, Male, Middle Aged, Aged, Prevalence, China epidemiology, Risk Factors, Disabled Persons statistics & numerical data, Nutritional Status, ROC Curve, Logistic Models, Predictive Value of Tests, Stroke Rehabilitation methods, Stroke Rehabilitation statistics & numerical data, Deglutition Disorders etiology, Deglutition Disorders epidemiology, Adult, Nutrition Assessment, Malnutrition epidemiology, Malnutrition etiology, Malnutrition diagnosis, Stroke complications, Nomograms
- Abstract
Background: Although malnutrition has been shown to influence the clinical outcome of poststroke disabled patients, the associated factors and the prediction model have yet to be uncovered., Objectives: This study aims to assess the current prevalence and factors associated with malnutrition in poststroke disabled patients and establish a prediction model., Methods: A multicenter cross-sectional survey among Chinese poststroke disabled patients (≥18 y old) was conducted in 2021. Information on patients' basic data, medical history, Barthel Index, dysphagia, and nutritional status was collected. A multivariable logistic regression model was used to identify the factors that influence malnutrition. Nomogram was developed and internal validation was conducted using 5-fold cross-validation. External validation was performed using the data from a preliminary survey. Receiver operating characteristic (ROC) analysis, calibration curves, and decision curve analysis (DCA) were used to analyze the predictive value of the nomogram., Results: Four hundred fifty-seven cases were enrolled, with the prevalence of malnutrition as 71.77%. Age (aOR = 1.039, 95% CI: 1.006-1.078), pulmonary infection (aOR = 4.301, 95% CI: 2.268-14.464), dysphagia (aOR = 24.605, 95% CI: 4.966-191.058), total intake volume (aOR = 0.997, 95% CI: 0.995-0.999), Barthel Index (aOR = 0.965, 95% CI: 0.951-0.980), and nasogastric tube (aOR = 16.529, 95% CI: 7.418-52.518) as nutrition support mode (compared to oral intake) were identified as the associated factors of malnutrition in stroke-disabled patients (P < 0.05). ROC analysis showed that the area under the curve (AUC) for nomogram was 0.854 (95% CI: 0.816-0.892). Fivefold cross-validation showed the mean AUC as 0.829 (95% CI: 0.784-0.873). There were no significant differences between predicted and actual probabilities. The DCA revealed that the model exhibited a net benefit when the risk threshold was between 0 and 0.4., Conclusions: Age, pulmonary infection, dysphagia, nutrition support mode, total intake volume, and Barthel Index were factors associated with malnutrition in stroke-related disabled patients. The nomogram based on the result exhibited good accuracy, consistency and values., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Zeng Xi reports financial support was provided by Chinese Academy of Medical Sciences. Zeng Xi reports a relationship with The First Affiliated Hospital of Zhengzhou University that includes: employment. Cai Ang reports a relationship with The First Affiliated Hospital of Zhengzhou University that includes: employment. Zeng Hongji reports a relationship with Zhengzhou University that includes: employment. Wu Junfa reports a relationship with Huashan Hospital Fudan University that includes: employment. Ding Yu reports a relationship with Chinese PLA General Hospital that includes: employment. Zhao Weijia reports a relationship with Zhengzhou University that includes: employment. Zeng Xi has patent #CN109172380A with royalties paid to CN109172380A. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)
- Published
- 2024
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