School of Public Health, Zhengzhou University, Zhengzhou, China.
Department of Rehabilitation Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Nutrition. 2024 Jul;123:112423. doi: 10.1016/j.nut.2024.112423. Epub 2024 Mar 14.
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.
This study aims to assess the current prevalence and factors associated with malnutrition in poststroke disabled patients and establish a prediction model.
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.
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.
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.
虽然营养不良已被证明会影响脑卒中后残疾患者的临床结局，但相关因素和预测模型仍有待揭示。
本研究旨在评估脑卒中后残疾患者营养不良的现患率及相关因素，并建立预测模型。
2021 年进行了一项多中心、横断面调查，纳入中国脑卒中后残疾患者（≥18 岁）。收集患者的基本资料、病史、巴氏指数、吞咽困难和营养状况等信息。采用多变量逻辑回归模型识别影响营养不良的因素。建立并采用 5 折交叉验证对内进行验证。采用初步调查数据进行外部验证。采用受试者工作特征（ROC）曲线分析、校准曲线和决策曲线分析（DCA）评估列线图的预测价值。
共纳入 457 例患者，营养不良的现患率为 71.77%。年龄（OR = 1.039，95%CI：1.006-1.078）、肺部感染（OR = 4.301，95%CI：2.268-14.464）、吞咽困难（OR = 24.605，95%CI：4.966-191.058）、总摄入量（OR = 0.997，95%CI：0.995-0.999）、巴氏指数（OR = 0.965，95%CI：0.951-0.980）和鼻饲管（OR = 16.529，95%CI：7.418-52.518）（与口服摄入相比）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，列线图的曲线下面积（AUC）为 0.854（95%CI：0.816-0.892）。5 折交叉验证显示平均 AUC 为 0.829（95%CI：0.784-0.873）。预测概率与实际概率之间无显著差异。DCA 显示，当风险阈值在 0 到 0.4 之间时，模型具有净收益。
年龄、肺部感染、吞咽困难、营养支持方式、总摄入量和巴氏指数是脑卒中相关残疾患者营养不良的相关因素。基于研究结果建立的列线图具有较好的准确性、一致性和临床价值。
