Factors and predictive model for malnutrition in poststroke disabled patients: A multicenter cross-sectional study

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Hongji Zeng , Ang Cai , Weijia Zhao , Junfa Wu , Yu Ding , Xi Zeng
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引用次数: 0

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.

中风后残疾患者营养不良的因素和预测模型:一项多中心横断面研究
尽管营养不良已被证明会影响脑卒中后残疾患者的临床预后,但相关因素和预测模型仍有待揭示。本研究旨在评估目前脑卒中后残疾患者营养不良的发生率及相关因素,并建立预测模型。本研究从 2021 年开始对中国脑卒中后残疾患者(≥18 岁)进行多中心横断面调查。调查收集了患者的基本资料、病史、Barthel指数、吞咽困难和营养状况等信息。采用多变量逻辑回归模型确定影响营养不良的因素。制定了提名图,并使用 5 倍交叉验证进行了内部验证。利用初步调查的数据进行了外部验证。采用接收者操作特征(ROC)分析、校准曲线、决策曲线分析(DCA)来分析提名图的预测价值。共登记了 457 个病例,营养不良发生率为 71.77%。年龄(aOR=1.039,95%CI:1.006-1.078)、肺部感染(aOR=4.301,95%CI:2.268-14.464)、吞咽困难(aOR=24.605,95%CI:4.966-191.058)、总摄入量(aOR=0.997,95%CI:0.995-0.999)、巴特尔指数(aOR=0.965,95%CI:0.951-0.980)、鼻胃管(aOR=16.529,95%CI:7.418-52.518)作为营养支持方式(与口服摄入相比)被认为是脑卒中残疾患者营养不良的相关因素(P<0.05)。ROC分析显示,提名图的曲线下面积(AUC)为0.854(95% CI:0.816-0.892)。5 倍交叉验证显示平均 AUC 为 0.829(95% CI:0.784-0.869)。预测概率和实际概率之间没有明显差异。DCA 显示,当风险阈值介于 0 和 0.4 之间时,模型显示出净效益。年龄、肺部感染、吞咽困难、营养支持模式、总摄入量和 Barthel 指数是中风相关残疾患者营养不良的相关因素。根据该结果绘制的提名图具有良好的准确性、一致性和价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
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