老年维持性血液透析患者蛋白质能量消耗相关因素及风险预测模型的初步构建OA

[Objective]To identify factors associated with protein-energy wasting(PEW)in elderly patients undergoing maintenance hemodialysis(MHD)and to preliminarily develop a risk discrimination model.[Method]This single-center retrospective case-control study included 102 elderly patients with end-stage renal disease who received MHD from January 2023 to December 2025.According to the ISRNM diagnostic criteria for PEW combined with the Mini Nutritional Assessment(MNA),malnutrition-inflammation score(MIS),and anthropometric measurements,51 patients were assigned to the PEW group and 51 to the non-PEW group.Demographic data,dialysis-related information,blood pressure,hematological and biochemical indicators,serum 25-hydroxyvitamin D[25(OH)D],anthropometric parameters,and nutritional assessment scores were collected.Variables with significant between-group differences were screened by univariate analysis,assessed for collinearity,and then entered into a multivariate Logistic regression model.Receiver operating characteristic(ROC)analysis was used to evaluate the apparent discriminative performance of the model in the development sample.[Result]Compared with the non-PEW group,the PEW group had higher age,systolic blood pressure,serum ferritin,and MIS score,but lower BMI,albumin,hemoglobin,total protein,25(OH)D,grip strength,upper arm circumference,triceps skinfold thickness,and MNA score(P<0.05).Multivariate Logistic regression showed that increased age,systolic blood pressure,serum ferritin,and MIS score,together with decreased 25(OH)D,were associated with a higher risk of PEW in elderly MHD patients(P<0.05).The model based on these variables yielded an AUC of 0.858,with a 95％CI of 0.807-0.909,sensitivity of 85.30％,and specificity of 75.67％.[Conclusion]PEW in elderly MHD patients is associated with aging,blood pressure,inflammation and iron metabolic burden,vitamin D status,and malnutrition-inflammation load.The Logistic model showed good apparent discriminative ability in this sample and may support early screening and risk-stratified intervention dur-ing dialysis follow-up,but further internal and external validation is required before clinical implementation.