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Lijuan Xia,1,2,* Fanxing Yang,3,* Naoko Hayashi,2,* Yuan Ma,4 Bin Yan,4 Yingxin Du,5 Sujuan Chen,1 Yuke Xia,4 Fang Feng,6 Zhifang Ma1 1Department of Radiotherapy, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China; 2Department of Oncology Nursing and Palliative Care/ Chronic Illness and Conditions Nursing, St. Luke’s International University, Tokyo, Japan; 3Department of Labor Delivery Recovery Postpartum, People’s Hospital of Zhengzhou, Zhengzhou, Henan, People’s Republic of China; 4Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China; 5Department of Clinical Nutrition, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China; 6Department of Rheumatology and Immunology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, People’s Republic of China*These authors contributed equally to this workCorrespondence: Lijuan Xia, Department of Radiotherapy, General Hospital of Ningxia Medical University, 804 Shengli South Street, Xingqing District, Yinchuan City, Ningxia, 750004, People’s Republic of China, Email 24DN009@slcn.ac.jp; 974286683@qq.com, Fang Feng, Email 13995409352@163.comIntroduction: Nutritional status is a critical indicator of overall health and immune function, significantly influencing treatment outcomes. Despite its importance, the nutritional status of patients with systemic lupus erythematosus (SLE) often receives insufficient attention. This study aims to evaluate the nutritional status of patients with SLE, identify factors associated with malnutrition, and develop a risk prediction model for malnutrition in this population.Methods: We collected clinical data from a convenience sample of SLE patients at a general hospital in Ningxia Province, China, between January and December 2022. Univariate and multivariate logistic regression analyses were performed to determine the independent risk factors for malnutrition. A risk prediction model was constructed and evaluated using the receiver operating characteristic (ROC) curve.Results: This study included 420 patients with SLE (mean age: 41.43 years, 91.7% women), of whom 46.2% were malnourished based on their serum albumin levels. Multivariate logistic regression analysis identified monthly income (OR=0.192, P< 0.05), sleep quality (OR=2.559, P< 0.05), kidney involvement (OR=4.269, P< 0.05), disease activity (OR=2.743, P< 0.05), leukocyte count (OR=1.576, P< 0.05), lymphocyte count (OR=0.393, P< 0.05), hemoglobin (OR=0.972, P< 0.05), complement C3 (OR=0.802, P< 0.05), and complement C4 (OR=0.493, P< 0.05) as independent risk factors for malnutrition. The prediction model showed good predictive value with an area under the ROC curve of 0.895 (95% CI: 0.823– 0.840), sensitivity of 0.907, and specificity of 0.827. The Hosmer-Lemeshow test indicated a good model fit (χ²=10.779, P=0.215).Discussion: Malnutrition is a significant concern among SLE patients, influenced by a range of socioeconomic and clinical factors. Our risk prediction model, with its high sensitivity and specificity, provides a robust tool for early identification of malnutrition in this population. Implementing this model in clinical practice can guide healthcare providers in prioritizing at-risk patients, enabling proactive nutritional interventions that could potentially improve clinical outcomes, enhance quality of life, and reduce healthcare costs associated with SLE.Keywords: systemic lupus erythematosus, nutritional status, associated factors, malnutrition, risk prediction model, nomogram |
